GenOMICC COVID-19 Study

Genomics England requires access to NHS England data for the purpose of the following work programme:

The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole Genome Sequencing (WGS) of patients severely affected by COVID-19.

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS England and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people)

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England National Genomics Research Library (NGRL) to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and its outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By utilising the GenOMICC consortium’s prospective study design that leverages existing recruitment infrastructure in critical care, Genomics England will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

The following NHS England Data will be accessed:

• Hospital Episode Statistics

o Admitted Patient Care

o Accident & Emergency

o Critical Care

o Outpatients

• Emergency Care Data Set (ECDS)

These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

• Diagnostic Imaging Dataset (DID) necessary to provide invaluable, detailed information to build on participants' phenotypes, e.g., tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

• Civil Registrations of Death- Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

• Cancer Registration - necessary to see the incidence of cancer within the cohort

• Covid-19 SGSS First Positives (Second Generation Surveillance System)

• Covid-19 Vaccination Status

• Covid-19 Hospitalization in England Surveillance System

These datasets, including vaccination, SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus. These will remain only for COVID based research only.

• Mental Health Services Data Set- The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

• Covid-19 General Practise Extraction Service assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings. Genomics England understand this dataset will be used only for COVID research going forward.

The level of the Data will be

• Identifiable- many indirect identifiable Data items have been requested because they provide valuable Data that can help researchers make new scientific and medical discoveries. All directly identifiable Data items will either be removed or transformed according to best practice agreed with NHSE. De-identification is a key facet of the Genomics England resource. De-identified data are uploaded to the NGRL hosted by Genomics England on a monthly basis, where they are linked to participant genomes and primary clinical data

The Data will be minimised as follows.

• Limited to a study cohort identified by Genomics England of;

• ~100,000 patients who consented to participate. ~30,000 of which recruited by Geonomics meeting the study's COVID-19 eligibility criteria, and ~71,243 as a control cohort.

• Genomics England request full history of patient Data to provide maximum insight, and therefore maximum value to the researchers accessing the Data. Because of the wide scope of the proposal, there are no other alternative or less intrusive ways of achieving the purpose described.

Genomics England is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above. Genomics England also process the Data.

The University of Edinburgh is responsible for acquisition of primary clinical data. That relates to data acquired at patient registration. Genomics England in its provision of whole genome sequencing are applying to NHS England for secondary clinical data to link to the genomic data.

Staff and academics from the University of Edinburgh are required to join a Genomics England Clinical Interpretation Partnership (GeCIP) to access the secondary clinical data from NHS England within the NGRL. Please see the processing activities of this DSA for further detail on GeCIP.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party.

It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

The funding is provided the Department of Health and Social Care. The funding is specifically for the purposes described.

The funder will have no ability to suppress or otherwise limit the publication of findings.

Lifebit provides IT support to Genomics England.

Amazon Web Services (AWS) provides IT back up services to Genomics England and will store copies of the Data as contracted by Genomics England.

SUB-LICENCING:

Genomics Clinical Interpretation Partners (GeCIP) members (Academic research organisations), and members of the Discovery Forum (Commercial organisations) will also have access to the pseudonymised Data within the NGRL, subject to internal approval by Genomics England. NHS England Data is combined with the genomic and sample data within the NGRL, providing a more comprehensive medical history, and going forward, a more comprehensive patient journey which will be a valuable resource for medical research. All applications have to provide health and social care benefits and are reviewed by a panel (the Access Review Committee (ARC)) before access is granted.

It is anticipated that the volume of sub-licences will be 150-200 per year. The GeCIP sub licence agreement is indefinite, until it is terminated by either the GeCIP member or Genomics.

The Data Access Agreement for Discovery Forum Members has a specified term, normally 12 months, at which point the company and Genomics can choose to renew or not.

All requests for data access will be subject to the following considerations:

• Protection of data subjects (honouring commitments made to them, acting within the scope of consent and according to conditions of Research Ethics Committee approval).

• Compliance with legal and regulatory requirements General Data Protection Regulation 2018, Data Protection Bill 2017, Freedom of Information Act 2000, NHS Act 2006, Health and Social Care Act 2012, the Common Law Duty of Confidentiality, Human Tissue Act 2004 and applicable requirements from organisations affiliated with the Health Research Authority, including Research Ethics Committees and the Confidentiality Advisory Group (CAG).

• Provision of a signed Genomics England data access agreement to the Access Review Committee.

• Prioritisation of access according to resource availability.

• Facilitation of high-quality health research

Commercial partnerships are crucial to achieving the aims of the NGRL and are achieved through the Discovery Forum. As with the non-commercial academic research led by GeCIP, commercial research aims to bring benefit to the patients and, through the use of the Data, inform development of platforms and tools for future diagnostic discovery. Commercial research can be broadly categorised into four themes that answer different questions along the typical Research and Discovery Biopharmaceutical Pipeline. At a high level they are divided into:

• Diagnostic discovery

• Pre-clinical research

• Clinical Trials Referral

• Real World Evidence / Market Access

Approval process for Commercial organisations for access to the NGRL:

Discovery Forum applications from a commercial organisation would be reviewed for suitability by the Partnership Development (PD)Team. The PD Team consider the credentials of the applying organisation including consideration of adverse public perception and reputational risk from approving data access for that organisation. If the PD Team feel appropriate, they are then passed on to be scrutinised by the independent Access Review Committee (ARC). ARC is constituted of Participant Panel members and senior individuals from various scientific and medical backgrounds. ARC assess the company’s research proposal, including patient/participant involvement, potential future value to patients/the NHS and the ethics of the proposal.

The ARC will assess whether there has been any Patient and Public Involvement and Engagement (PPIE) informing the research questions and design. For many commercial applications that are exploring early-stage research and development (R&D), for example, target identification and validation, there will not have been any PPIE because the research may be tied to exploring fundamental biological mechanisms and pathways rather than particular conditions or phenotypes. If there has been PPIE, the ARC will determine whether it has adequately informed the research questions and design, and whether there is a commitment to ongoing PPIE and transparency following the outcomes of the research. Although PPIE is not a requirement of applications, ARC encourage applicants to consider at what stage in their R&D process it would be appropriate to consult with patient advocacy and participation groups.

Genomics England will only work with companies that are aligned with its strategy and mission to bring the benefits of genomic medicine to everyone. The Partnerships Development team will assess whether a company seeking access to NGRL data is working in the cancer or rare disease diagnostics and therapeutics space, or supporting UK Government strategic scientific initiatives – if not, Genomics England would not permit an application to ARC in the first place. All applications must conform to the acceptable uses set out in the REC-approved NGRL protocol. If the research proposal is for later stage research that has a clear pathway to intended patient or health system benefit, the ARC would expect to see this articulated as part of the rationale for seeking access to NGRL data. Given the early stage of much commercial genomics research, not all accepted applications will be able to demonstrate a clear explanation of the expected healthcare benefits.

Approval process for GeCIP users (academic) of the NGRL:

• Researcher visits Genomics England website to enrol as a GECIP member

• Completion of onboarding process; Verification by their institution (institution will be required to sign a Genomics participation agreement and appoint a membership secretary), verification of their self-stated qualifications and areas of research interest by the GEL Scientific Manager to join their domain of choice, take the IG and GECIP rules training course and pass test with at least 80%. They are then able to access the NGRL and the Research Portal (the area where prospective GeCIP applicants can apply and register their research project)

• Within 3 months of gaining access they need to either submit a research proposal for Genomics England approval, which currently has to fit with the Detailed Research Plan for their domain, or join another registered project. Otherwise they will lose access.

• On an annual basis, complete a survey sent out by Genomics England giving details of their research progress and any outputs, to aid reporting to ARC.

• Any data they wish to either import or export to/from the NGRL has to be approved by Airlock (Airlock policy is described below) as not being personally identifiable.

• If a researcher has not accessed the NGRL, the Research Portal, or logged into their GEL account to gain access to either of the previous for 6 months their account will be deactivated.

All research activities undertaken in the NGRL aim to enrich the existing dataset via one or multiple routes:

• Identification of diagnoses originally missed by the standardised pipeline

• Feedback of new diagnoses to patients

• Mobilising samples which can help to identify diagnoses that were missed through analyses of WGS alone

Researchers can access pseudonymised Data through NGRL under sub licence. The only Data allowed to be exported are summary results. An airlock policy has been established which enables material (data, files, tools etc) to be moved in or out of the NGRL in a controlled and supervised manner; facilitating research and discovery, while maintaining control of security and access.

Data accessed under sub licence is only granted to named individuals identified to Genomics England who agree to comply with the Airlock policy, Information Governance and IT Security Policy. Before being provided with credentials necessary to access the NGRL a Company Researcher must complete information governance training which shall be provided by Genomics England.

AIRLOCK POLICY:

The following rules are applied to all airlock requests:

1. All relevant details of the summary results to be transferred must be provided with every request.

2. All summary results transferred must be checked by Genomics England to ensure compliance with the relevant policies. Users will be notified of any summary results rejected along with the reason for the rejection.

3. All imports will be checked for viruses and malware and those failing this test will be rejected. It is the responsibility of the requestors to resolve such issues before re-submitting the file for transfer.

4. Summary results requested for transfer are assessed using the following criteria:

a. whether the request aligns with the users ARC approval in full;

b. whether the request can clearly be demonstrated to be aligned with a registered project in the NGRL;

c. any data security implications;

d. any disclosure risks;

e. the technical feasibility and associated cost of the request;

f. when importing data, its scientific value to the community of researchers within the NGRL, and when and how it will be shared;

g. when importing data, checks will be performed to ensure that the data importer owns the data and holds the correct consents and approvals.

The Airlock Manager has formal delegated approval to approve requests where there is precedent from previous Airlock Review Committees. For more complicated requests or where no precedent has been set these will go to the airlock committee for review and a decision. The airlock committee is a delegation of the Genomics England Chief Scientist who responsible for oversight of all airlock requests in accordance with the airlock policy. The committee comprises of:

• Technical Lead

• User Community Representative

• Bioinformatics Director

• Caldicott Guardian

• Chief Scientist representative

Access is restricted to substantive employees of Genomics England, Genomics Clinical Interpretation Partners (GeCIP) members, and members of the Discovery Forum, who have authorisation from the Principal Investigator.

GeCIP membership is open to any individual, student or member of staff, who is affiliated with a host institution which include the following:

• UK academic research institutions (e.g., universities, research institutions etc.)

• NHS trusts or authorities

• UK and foreign charitable organisations directly related to the focus of the 100,000 Genomes Project

• Foreign universities and research institutions that carry out significant research activity

• UK and foreign governmental departments that carry out significant research activity (e.g., Medical Research Council (MRC), National Institute of Health (NIH), Public Health England (PHE))

• Foreign healthcare organisations (private or public) that undertake significant research activity

To be eligible for data access as a GeCIP member, applicants must meet these requirements:

• Their host institution has signed a GeCIP Participation Agreement, which outlines the key principles that members of each institution must adhere to, including the Intellectual Property and Publication Policy.

• Their host institution has verified that they are affiliated with that institution.

• The applicant’s GeCIP domain has submitted a detailed research plan and it has been approved by the Genomics England Access Review Committee (see below).

• The GeCIP domain lead has approved the application.

• Following approval, GeCIP researchers must sign a specific agreement (‘GeCIP rules’) covering their behaviour and working practice within the data infrastructure.

• Data access will not then be granted until a researcher has successfully passed mandatory information governance training.

All applications have to provide health and social care benefits in England and are reviewed by a panel (the Access Review Committee (ARC)).

The ARC provides an independent examination of requests for data access. The ARC comprises external scientific experts, patient representatives and members of Genomics England’s Participant Panel.

GeCIP users will be granted access to all data and knowledge held within the NGRL. Each GeCIP domain will have access to its own private shared area of the NGRL for data storage and collaboration. The secure virtual desktop infrastructure will provide the ‘workspace’ for clinical teams, research groups and trainees to undertake their work.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will be linked at person record level with the patient’s genetic data within the NGRL. This includes the following data:

> National Cancer Registration and Analysis Service (NCRAS)

and uncurated NCRAS data

> Secure Anonymised Information Linkage (SAIL) data; Welsh data

> Patient samples (e.g., blood, saliva, tissue, RNA, plasma and serum)

> NHS Trusts data

> Data feeds from the Intensive Care National Audit Registry (ICNARC)

> The UK Health Security Agency (UKHSA) viral genomic data and associated metadata

The Data will not be linked with any other data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised Dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised Dataset.

To protect patient confidentiality, access to the NGRL will be granted only for specific, approved purposes in accordance with informed consent. Any attempted use beyond the specified purpose may lead to exclusion and possible legal action, where appropriate.

Data accessed under sub licence will not be re-identified.

Genomics England rely on GDPR Article 6 (1)(f) for the personal data and Article 9(2)(j) for the special category data shared within the NGRL.

Data shared through the Airlock process is aggregate data only and is therefore not personal data so does not require a legal basis under the UK GDPR.

A release register detailing any sub licences and onward sharing can be found here: https://research.genomicsengland.co.uk/research-registry/browse

Genomics will take responsibility for the actions and omissions of all sub licences and breach of a sub licence will automatically be regarded as breach of the Data Sharing Framework Contract.

In the event of termination or expiry of the Data Sharing Framework Contract between NHS England and the applicant, Data from NHS England will be removed from the NGRL, preventing access to the Data for all users.

NHS England will require the ability to audit the sub licensee.

Combining genomic sequence data from COVID participants together with their medical records has created a ground-breaking research resource. Researchers are currently studying this data to be able to deliver outputs that will have tangible benefits to healthcare and patients. Understanding the symptoms and impact of COVID on people with differing genetic make-ups is hoped to lead to successful treatment of the disease being investigated.

Specific outputs for Genomics England are to continue to release updated genomic and clinical data into the NGRL to support this ongoing research. Each research group who accesses this data will have their own defined output strategy and expectations which they will aim to deliver against. Specific examples of journal outputs are as follows:

• A first update on mapping the human genetic architecture of COVID-19 (2022) Nature 608(7921):E1-E10. doi: 10.1038/s41586-022-04826-7

• Mapping the human genetic architecture of COVID-19 (2021) Nature 600(7889):472-477. doi: 10.1038/s41586-021-03767-x

• Whole-genome sequencing reveals host factors underlying critical COVID-19 (2022) Nature 607(7917):97-103. doi: 10.1038/s41586-022-04576-6

• Genetic mechanisms of critical illness in COVID-19 (2021) Nature 591(7848):92-98. doi: 10.1038/s41586-020-03065-y

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS England. Understanding this significant value is why Genomics England are so keen to add NHS England data to its clinical data source for the GenOMICC study.

This proposal has already enabled Genomics England to discover new rare and common variants alongside new multi-omic biomarkers that underpin host response to infection, allowing investigation of the impact of viral genomic features on outcomes. The ongoing prospective component could allow nested clinical trials or case-control resources to add value to this study by detecting variants, which stratify response or predict outcomes. Benefits thus far stated below.

Summary of publications and value of study updated August 2022:

Genome wide studies (GWAS) of first 2244 GenOMICC participants admitted with severe COVID

May 2021:

• Identified 4 targets that can utilise and repurpose currently used medications for treatment and management of severe covid.

• Found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. This mechanism may also be amenable to targeted treatment with existing drugs.

These results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19.

Mapping the human genetic architecture of COVID-19

Dec 2021

• Contributed to the meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries.

• Identified 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases.

• They represent potentially actionable mechanisms in response to infection.

• There is evidence of a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes.

This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

May 2022

• Identified TMPRSS2 variant has a protective effect against severe COVID-19

• This is a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID-19

Whole genome sequencing of 7,491 GenOMICC participants admitted with severe COVID

Jul 2022

• Identified 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2)

• Found evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease.

• Found evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets.

The results show that comparisons between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Aug 2022

• Contributed to the meta-analyses bringing together 60 studies from 25 countries for 3 COVID-19 phenotypes.

• Between-study heterogeneity rather than differences across ancestries are a more likely explanation for the observed heterogeneity in the effect sizes across studies

• Identified that the variant rs35705950:G>T located in the promoter of MUC5B (11p15.5) is protective against hospitalization

• Identified that rs190509934:T>C, which is upstream of ACE2, is associated with decreased susceptibility risk. Recent results have shown that the rs190509934:T>C variant lowers ACE2 expression, which in turn confers protection against SARS-CoV-2 infection12.

The biological insights gained by this expansion of the COVID-19 Host Genetic Initiative showed that increasing sample size and diversity remain a fruitful activity to better understand the human genetic architecture of COVID-19.

The first genomes from severe volunteers came through in June 2020.

By June 2021, interim findings from the study were published. These findings have already helped doctors make better decisions when treating patients with COVID-19, resulting in better outcomes. In addition, two therapeutic drug trials have also commenced.

By March 2022 some 16 new genetic variants associated with severe Covid-19, including some related to blood clotting, immune response and intensity of inflammation, have been identified. These findings will act as a roadmap for future efforts, opening new fields of research focused on potential new therapies and diagnostics with pinpoint accuracy.

Determining the whole genome sequence for all participants in the study allowed the team to create a precise map and identify genetic variation linked to severity of Covid-19. The team found key differences in 16 genes in the ICU patients when compared with the DNA of the other groups. They also confirmed the involvement of seven other genetic variations already associated with severe Covid-19 discovered in earlier studies from the same team. The findings included how a single gene variant that disrupts a key messenger molecule in immune system signalling – called interferon alpha-10 – was enough to increase a patient’s risk of severe disease. This highlights the gene’s key role in the immune system and suggests that treating patients with interferon – proteins released by immune cells to defend against viruses – may help manage disease in the early stages. The study also found that variations in genes that control the levels of a central component of blood clotting – known as Factor 8 – were associated with critical illness in Covid-19. This may explain some of the clotting abnormalities that are seen in severe cases of Covid-19. Factor 8 is the gene underlying the most common type of haemophilia.

Genomics England requires access to NHS England data for the purpose of the following work programme:

The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole Genome Sequencing (WGS) of patients severely affected by COVID-19.

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS England and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people)

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England National Genomics Research Library (NGRL) to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and its outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By utilising the GenOMICC consortium’s prospective study design that leverages existing recruitment infrastructure in critical care, Genomics England will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

The following NHS England Data will be accessed:

• Hospital Episode Statistics

o Admitted Patient Care

o Accident & Emergency

o Critical Care

o Outpatients

• Emergency Care Data Set (ECDS)

These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

• Diagnostic Imaging Dataset (DID) necessary to provide invaluable, detailed information to build on participants' phenotypes, e.g., tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

• Civil Registrations of Death- Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

• Cancer Registration - necessary to see the incidence of cancer within the cohort

• Covid-19 SGSS First Positives (Second Generation Surveillance System)

• Covid-19 Vaccination Status

• Covid-19 Hospitalization in England Surveillance System

These datasets, including vaccination, SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus. These will remain only for COVID based research only.

• Mental Health Services Data Set- The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

• Covid-19 General Practise Extraction Service assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings. Genomics England understand this dataset will be used only for COVID research going forward.

The level of the Data will be

• Identifiable- many indirect identifiable Data items have been requested because they provide valuable Data that can help researchers make new scientific and medical discoveries. All directly identifiable Data items will either be removed or transformed according to best practice agreed with NHSE. De-identification is a key facet of the Genomics England resource. De-identified data are uploaded to the NGRL hosted by Genomics England on a monthly basis, where they are linked to participant genomes and primary clinical data

The Data will be minimised as follows.

• Limited to a study cohort identified by Genomics England of;

• ~100,000 patients who consented to participate. ~30,000 of which recruited by Geonomics meeting the study's COVID-19 eligibility criteria, and ~71,243 as a control cohort.

• Genomics England request full history of patient Data to provide maximum insight, and therefore maximum value to the researchers accessing the Data. Because of the wide scope of the proposal, there are no other alternative or less intrusive ways of achieving the purpose described.

Genomics England is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above. Genomics England also process the Data.

The University of Edinburgh is responsible for acquisition of primary clinical data. That relates to data acquired at patient registration. Genomics England in its provision of whole genome sequencing are applying to NHS England for secondary clinical data to link to the genomic data.

Staff and academics from the University of Edinburgh are required to join a Genomics England Clinical Interpretation Partnership (GeCIP) to access the secondary clinical data from NHS England within the NGRL. Please see the processing activities of this DSA for further detail on GeCIP.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party.

It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

The funding is provided the Department of Health and Social Care. The funding is specifically for the purposes described.

The funder will have no ability to suppress or otherwise limit the publication of findings.

Lifebit provides IT support to Genomics England.

Amazon Web Services (AWS) provides IT back up services to Genomics England and will store copies of the Data as contracted by Genomics England.

SUB-LICENCING:

Genomics Clinical Interpretation Partners (GeCIP) members (Academic research organisations), and members of the Discovery Forum (Commercial organisations) will also have access to the pseudonymised Data within the NGRL, subject to internal approval by Genomics England. NHS England Data is combined with the genomic and sample data within the NGRL, providing a more comprehensive medical history, and going forward, a more comprehensive patient journey which will be a valuable resource for medical research. All applications have to provide health and social care benefits and are reviewed by a panel (the Access Review Committee (ARC)) before access is granted.

It is anticipated that the volume of sub-licences will be 150-200 per year. The GeCIP sub licence agreement is indefinite, until it is terminated by either the GeCIP member or Genomics.

The Data Access Agreement for Discovery Forum Members has a specified term, normally 12 months, at which point the company and Genomics can choose to renew or not.

All requests for data access will be subject to the following considerations:

• Protection of data subjects (honouring commitments made to them, acting within the scope of consent and according to conditions of Research Ethics Committee approval).

• Compliance with legal and regulatory requirements General Data Protection Regulation 2018, Data Protection Bill 2017, Freedom of Information Act 2000, NHS Act 2006, Health and Social Care Act 2012, the Common Law Duty of Confidentiality, Human Tissue Act 2004 and applicable requirements from organisations affiliated with the Health Research Authority, including Research Ethics Committees and the Confidentiality Advisory Group (CAG).

• Provision of a signed Genomics England data access agreement to the Access Review Committee.

• Prioritisation of access according to resource availability.

• Facilitation of high-quality health research

Commercial partnerships are crucial to achieving the aims of the NGRL and are achieved through the Discovery Forum. As with the non-commercial academic research led by GeCIP, commercial research aims to bring benefit to the patients and, through the use of the Data, inform development of platforms and tools for future diagnostic discovery. Commercial research can be broadly categorised into four themes that answer different questions along the typical Research and Discovery Biopharmaceutical Pipeline. At a high level they are divided into:

• Diagnostic discovery

• Pre-clinical research

• Clinical Trials Referral

• Real World Evidence / Market Access

Approval process for Commercial organisations for access to the NGRL:

Discovery Forum applications from a commercial organisation would be reviewed for suitability by the Partnership Development (PD)Team. The PD Team consider the credentials of the applying organisation including consideration of adverse public perception and reputational risk from approving data access for that organisation. If the PD Team feel appropriate, they are then passed on to be scrutinised by the independent Access Review Committee (ARC). ARC is constituted of Participant Panel members and senior individuals from various scientific and medical backgrounds. ARC assess the company’s research proposal, including patient/participant involvement, potential future value to patients/the NHS and the ethics of the proposal.

The ARC will assess whether there has been any Patient and Public Involvement and Engagement (PPIE) informing the research questions and design. For many commercial applications that are exploring early-stage research and development (R&D), for example, target identification and validation, there will not have been any PPIE because the research may be tied to exploring fundamental biological mechanisms and pathways rather than particular conditions or phenotypes. If there has been PPIE, the ARC will determine whether it has adequately informed the research questions and design, and whether there is a commitment to ongoing PPIE and transparency following the outcomes of the research. Although PPIE is not a requirement of applications, ARC encourage applicants to consider at what stage in their R&D process it would be appropriate to consult with patient advocacy and participation groups.

Genomics England will only work with companies that are aligned with its strategy and mission to bring the benefits of genomic medicine to everyone. The Partnerships Development team will assess whether a company seeking access to NGRL data is working in the cancer or rare disease diagnostics and therapeutics space, or supporting UK Government strategic scientific initiatives – if not, Genomics England would not permit an application to ARC in the first place. All applications must conform to the acceptable uses set out in the REC-approved NGRL protocol. If the research proposal is for later stage research that has a clear pathway to intended patient or health system benefit, the ARC would expect to see this articulated as part of the rationale for seeking access to NGRL data. Given the early stage of much commercial genomics research, not all accepted applications will be able to demonstrate a clear explanation of the expected healthcare benefits.

Approval process for GeCIP users (academic) of the NGRL:

• Researcher visits Genomics England website to enrol as a GECIP member

• Completion of onboarding process; Verification by their institution (institution will be required to sign a Genomics participation agreement and appoint a membership secretary), verification of their self-stated qualifications and areas of research interest by the GEL Scientific Manager to join their domain of choice, take the IG and GECIP rules training course and pass test with at least 80%. They are then able to access the NGRL and the Research Portal (the area where prospective GeCIP applicants can apply and register their research project)

• Within 3 months of gaining access they need to either submit a research proposal for Genomics England approval, which currently has to fit with the Detailed Research Plan for their domain, or join another registered project. Otherwise they will lose access.

• On an annual basis, complete a survey sent out by Genomics England giving details of their research progress and any outputs, to aid reporting to ARC.

• Any data they wish to either import or export to/from the NGRL has to be approved by Airlock (Airlock policy is described below) as not being personally identifiable.

• If a researcher has not accessed the NGRL, the Research Portal, or logged into their GEL account to gain access to either of the previous for 6 months their account will be deactivated.

All research activities undertaken in the NGRL aim to enrich the existing dataset via one or multiple routes:

• Identification of diagnoses originally missed by the standardised pipeline

• Feedback of new diagnoses to patients

• Mobilising samples which can help to identify diagnoses that were missed through analyses of WGS alone

Researchers can access pseudonymised Data through NGRL under sub licence. The only Data allowed to be exported are summary results. An airlock policy has been established which enables material (data, files, tools etc) to be moved in or out of the NGRL in a controlled and supervised manner; facilitating research and discovery, while maintaining control of security and access.

Data accessed under sub licence is only granted to named individuals identified to Genomics England who agree to comply with the Airlock policy, Information Governance and IT Security Policy. Before being provided with credentials necessary to access the NGRL a Company Researcher must complete information governance training which shall be provided by Genomics England.

AIRLOCK POLICY:

The following rules are applied to all airlock requests:

1. All relevant details of the summary results to be transferred must be provided with every request.

2. All summary results transferred must be checked by Genomics England to ensure compliance with the relevant policies. Users will be notified of any summary results rejected along with the reason for the rejection.

3. All imports will be checked for viruses and malware and those failing this test will be rejected. It is the responsibility of the requestors to resolve such issues before re-submitting the file for transfer.

4. Summary results requested for transfer are assessed using the following criteria:

a. whether the request aligns with the users ARC approval in full;

b. whether the request can clearly be demonstrated to be aligned with a registered project in the NGRL;

c. any data security implications;

d. any disclosure risks;

e. the technical feasibility and associated cost of the request;

f. when importing data, its scientific value to the community of researchers within the NGRL, and when and how it will be shared;

g. when importing data, checks will be performed to ensure that the data importer owns the data and holds the correct consents and approvals.

The Airlock Manager has formal delegated approval to approve requests where there is precedent from previous Airlock Review Committees. For more complicated requests or where no precedent has been set these will go to the airlock committee for review and a decision. The airlock committee is a delegation of the Genomics England Chief Scientist who responsible for oversight of all airlock requests in accordance with the airlock policy. The committee comprises of:

• Technical Lead

• User Community Representative

• Bioinformatics Director

• Caldicott Guardian

• Chief Scientist representative

Access is restricted to substantive employees of Genomics England, Genomics Clinical Interpretation Partners (GeCIP) members, and members of the Discovery Forum, who have authorisation from the Principal Investigator.

GeCIP membership is open to any individual, student or member of staff, who is affiliated with a host institution which include the following:

• UK academic research institutions (e.g., universities, research institutions etc.)

• NHS trusts or authorities

• UK and foreign charitable organisations directly related to the focus of the 100,000 Genomes Project

• Foreign universities and research institutions that carry out significant research activity

• UK and foreign governmental departments that carry out significant research activity (e.g., Medical Research Council (MRC), National Institute of Health (NIH), Public Health England (PHE))

• Foreign healthcare organisations (private or public) that undertake significant research activity

To be eligible for data access as a GeCIP member, applicants must meet these requirements:

• Their host institution has signed a GeCIP Participation Agreement, which outlines the key principles that members of each institution must adhere to, including the Intellectual Property and Publication Policy.

• Their host institution has verified that they are affiliated with that institution.

• The applicant’s GeCIP domain has submitted a detailed research plan and it has been approved by the Genomics England Access Review Committee (see below).

• The GeCIP domain lead has approved the application.

• Following approval, GeCIP researchers must sign a specific agreement (‘GeCIP rules’) covering their behaviour and working practice within the data infrastructure.

• Data access will not then be granted until a researcher has successfully passed mandatory information governance training.

All applications have to provide health and social care benefits in England and are reviewed by a panel (the Access Review Committee (ARC)).

The ARC provides an independent examination of requests for data access. The ARC comprises external scientific experts, patient representatives and members of Genomics England’s Participant Panel.

GeCIP users will be granted access to all data and knowledge held within the NGRL. Each GeCIP domain will have access to its own private shared area of the NGRL for data storage and collaboration. The secure virtual desktop infrastructure will provide the ‘workspace’ for clinical teams, research groups and trainees to undertake their work.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will be linked at person record level with the patient’s genetic data within the NGRL. This includes the following data:

> National Cancer Registration and Analysis Service (NCRAS)

and uncurated NCRAS data

> Secure Anonymised Information Linkage (SAIL) data; Welsh data

> Patient samples (e.g., blood, saliva, tissue, RNA, plasma and serum)

> NHS Trusts data

> Data feeds from the Intensive Care National Audit Registry (ICNARC)

> The UK Health Security Agency (UKHSA) viral genomic data and associated metadata

The Data will not be linked with any other data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised Dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised Dataset.

To protect patient confidentiality, access to the NGRL will be granted only for specific, approved purposes in accordance with informed consent. Any attempted use beyond the specified purpose may lead to exclusion and possible legal action, where appropriate.

Data accessed under sub licence will not be re-identified.

Genomics England rely on GDPR Article 6 (1)(f) for the personal data and Article 9(2)(j) for the special category data shared within the NGRL.

Data shared through the Airlock process is aggregate data only and is therefore not personal data so does not require a legal basis under the UK GDPR.

A release register detailing any sub licences and onward sharing can be found here: https://research.genomicsengland.co.uk/research-registry/browse

Genomics will take responsibility for the actions and omissions of all sub licences and breach of a sub licence will automatically be regarded as breach of the Data Sharing Framework Contract.

In the event of termination or expiry of the Data Sharing Framework Contract between NHS England and the applicant, Data from NHS England will be removed from the NGRL, preventing access to the Data for all users.

NHS England will require the ability to audit the sub licensee.

Combining genomic sequence data from COVID participants together with their medical records has created a ground-breaking research resource. Researchers are currently studying this data to be able to deliver outputs that will have tangible benefits to healthcare and patients. Understanding the symptoms and impact of COVID on people with differing genetic make-ups is hoped to lead to successful treatment of the disease being investigated.

Specific outputs for Genomics England are to continue to release updated genomic and clinical data into the NGRL to support this ongoing research. Each research group who accesses this data will have their own defined output strategy and expectations which they will aim to deliver against. Specific examples of journal outputs are as follows:

• A first update on mapping the human genetic architecture of COVID-19 (2022) Nature 608(7921):E1-E10. doi: 10.1038/s41586-022-04826-7

• Mapping the human genetic architecture of COVID-19 (2021) Nature 600(7889):472-477. doi: 10.1038/s41586-021-03767-x

• Whole-genome sequencing reveals host factors underlying critical COVID-19 (2022) Nature 607(7917):97-103. doi: 10.1038/s41586-022-04576-6

• Genetic mechanisms of critical illness in COVID-19 (2021) Nature 591(7848):92-98. doi: 10.1038/s41586-020-03065-y

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS Digital. Understanding this significant value is why Genomics England are so keen to add NHS Digital data to its clinical data source for the GenOMICC study.

This proposal has already enabled Genomics England to discover new rare and common variants alongside new multi-omic biomarkers that underpin host response to infection, allowing investigation of the impact of viral genomic features on outcomes. The ongoing prospective component could allow nested clinical trials or case-control resources to add value to this study by detecting variants, which stratify response or predict outcomes. Benefits thus far stated below.

Summary of publications and value of study updated August 2022:

Genome wide studies (GWAS) of first 2244 GenOMICC participants admitted with severe COVID

May 2021:

• Identified 4 targets that can utilise and repurpose currently used medications for treatment and management of severe covid.

• Found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. This mechanism may also be amenable to targeted treatment with existing drugs.

These results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19.

Mapping the human genetic architecture of COVID-19

Dec 2021

• Contributed to the meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries.

• Identified 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases.

• They represent potentially actionable mechanisms in response to infection.

• There is evidence of a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes.

This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

May 2022

• Identified TMPRSS2 variant has a protective effect against severe COVID-19

• This is a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID-19

Whole genome sequencing of 7,491 GenOMICC participants admitted with severe COVID

Jul 2022

• Identified 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2)

• Found evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease.

• Found evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets.

The results show that comparisons between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Aug 2022

• Contributed to the meta-analyses bringing together 60 studies from 25 countries for 3 COVID-19 phenotypes.

• Between-study heterogeneity rather than differences across ancestries are a more likely explanation for the observed heterogeneity in the effect sizes across studies

• Identified that the variant rs35705950:G>T located in the promoter of MUC5B (11p15.5) is protective against hospitalization

• Identified that rs190509934:T>C, which is upstream of ACE2, is associated with decreased susceptibility risk. Recent results have shown that the rs190509934:T>C variant lowers ACE2 expression, which in turn confers protection against SARS-CoV-2 infection12.

The biological insights gained by this expansion of the COVID-19 Host Genetic Initiative showed that increasing sample size and diversity remain a fruitful activity to better understand the human genetic architecture of COVID-19.

The first genomes from severe volunteers came through in June 2020.

By June 2021, interim findings from the study were published. These findings have already helped doctors make better decisions when treating patients with COVID-19, resulting in better outcomes. In addition, two therapeutic drug trials have also commenced.

By March 2022 some 16 new genetic variants associated with severe Covid-19, including some related to blood clotting, immune response and intensity of inflammation, have been identified. These findings will act as a roadmap for future efforts, opening new fields of research focused on potential new therapies and diagnostics with pinpoint accuracy.

Determining the whole genome sequence for all participants in the study allowed the team to create a precise map and identify genetic variation linked to severity of Covid-19. The team found key differences in 16 genes in the ICU patients when compared with the DNA of the other groups. They also confirmed the involvement of seven other genetic variations already associated with severe Covid-19 discovered in earlier studies from the same team. The findings included how a single gene variant that disrupts a key messenger molecule in immune system signalling – called interferon alpha-10 – was enough to increase a patient’s risk of severe disease. This highlights the gene’s key role in the immune system and suggests that treating patients with interferon – proteins released by immune cells to defend against viruses – may help manage disease in the early stages. The study also found that variations in genes that control the levels of a central component of blood clotting – known as Factor 8 – were associated with critical illness in Covid-19. This may explain some of the clotting abnormalities that are seen in severe cases of Covid-19. Factor 8 is the gene underlying the most common type of haemophilia.

Genomics England requires access to NHS England data for the purpose of the following work programme:

The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole Genome Sequencing (WGS) of patients severely affected by COVID-19.

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS England and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people)

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England National Genomics Research Library (NGRL) to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and its outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By utilising the GenOMICC consortium’s prospective study design that leverages existing recruitment infrastructure in critical care, Genomics England will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

The following NHS England Data will be accessed:

• Hospital Episode Statistics

o Admitted Patient Care

o Accident & Emergency

o Critical Care

o Outpatients

• Emergency Care Data Set (ECDS)

These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

• Diagnostic Imaging Dataset (DID) necessary to provide invaluable, detailed information to build on participants' phenotypes, e.g., tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

• Civil Registrations of Death- Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

• Cancer Registration - necessary to see the incidence of cancer within the cohort

• Covid-19 SGSS First Positives (Second Generation Surveillance System)

• Covid-19 Vaccination Status

• Covid-19 Hospitalization in England Surveillance System

These datasets, including vaccination, SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus. These will remain only for COVID based research only.

• Mental Health Services Data Set- The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

• Covid-19 General Practise Extraction Service assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings. Genomics England understand this dataset will be used only for COVID research going forward.

The level of the Data will be

• Identifiable- many indirect identifiable Data items have been requested because they provide valuable Data that can help researchers make new scientific and medical discoveries. All directly identifiable Data items will either be removed or transformed according to best practice agreed with NHSE. De-identification is a key facet of the Genomics England resource. De-identified data are uploaded to the NGRL hosted by Genomics England on a monthly basis, where they are linked to participant genomes and primary clinical data

The Data will be minimised as follows.

• Limited to a study cohort identified by Genomics England of;

• ~100,000 patients who consented to participate. ~30,000 of which recruited by Geonomics meeting the study's COVID-19 eligibility criteria, and ~71,243 as a control cohort.

• Genomics England request full history of patient Data to provide maximum insight, and therefore maximum value to the researchers accessing the Data. Because of the wide scope of the proposal, there are no other alternative or less intrusive ways of achieving the purpose described.

Genomics England is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above. Genomics England also process the Data.

The University of Edinburgh is responsible for acquisition of primary clinical data. That relates to data acquired at patient registration. Genomics England in its provision of whole genome sequencing are applying to NHS England for secondary clinical data to link to the genomic data.

Staff and academics from the University of Edinburgh are required to join a Genomics England Clinical Interpretation Partnership (GeCIP) to access the secondary clinical data from NHS England within the NGRL. Please see the processing activities of this DSA for further detail on GeCIP.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party.

It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

The funding is provided the Department of Health and Social Care. The funding is specifically for the purposes described.

The funder will have no ability to suppress or otherwise limit the publication of findings.

Lifebit provides IT support to Genomics England.

Amazon Web Services (AWS) provides IT back up services to Genomics England and will store copies of the Data as contracted by Genomics England.

SUB-LICENCING:

Genomics Clinical Interpretation Partners (GeCIP) members (Academic research organisations), and members of the Discovery Forum (Commercial organisations) will also have access to the pseudonymised Data within the NGRL, subject to internal approval by Genomics England. NHS England Data is combined with the genomic and sample data within the NGRL, providing a more comprehensive medical history, and going forward, a more comprehensive patient journey which will be a valuable resource for medical research. All applications have to provide health and social care benefits and are reviewed by a panel (the Access Review Committee (ARC)) before access is granted.

It is anticipated that the volume of sub-licences will be 150-200 per year. The GeCIP sub licence agreement is indefinite, until it is terminated by either the GeCIP member or Genomics.

The Data Access Agreement for Discovery Forum Members has a specified term, normally 12 months, at which point the company and Genomics can choose to renew or not.

All requests for data access will be subject to the following considerations:

• Protection of data subjects (honouring commitments made to them, acting within the scope of consent and according to conditions of Research Ethics Committee approval).

• Compliance with legal and regulatory requirements General Data Protection Regulation 2018, Data Protection Bill 2017, Freedom of Information Act 2000, NHS Act 2006, Health and Social Care Act 2012, the Common Law Duty of Confidentiality, Human Tissue Act 2004 and applicable requirements from organisations affiliated with the Health Research Authority, including Research Ethics Committees and the Confidentiality Advisory Group (CAG).

• Provision of a signed Genomics England data access agreement to the Access Review Committee.

• Prioritisation of access according to resource availability.

• Facilitation of high-quality health research

Commercial partnerships are crucial to achieving the aims of the NGRL and are achieved through the Discovery Forum. As with the non-commercial academic research led by GeCIP, commercial research aims to bring benefit to the patients and, through the use of the Data, inform development of platforms and tools for future diagnostic discovery. Commercial research can be broadly categorised into four themes that answer different questions along the typical Research and Discovery Biopharmaceutical Pipeline. At a high level they are divided into:

• Diagnostic discovery

• Pre-clinical research

• Clinical Trials Referral

• Real World Evidence / Market Access

Approval process for Commercial organisations for access to the NGRL:

Discovery Forum applications from a commercial organisation would be reviewed for suitability by the Partnership Development (PD)Team. The PD Team consider the credentials of the applying organisation including consideration of adverse public perception and reputational risk from approving data access for that organisation. If the PD Team feel appropriate, they are then passed on to be scrutinised by the independent Access Review Committee (ARC). ARC is constituted of Participant Panel members and senior individuals from various scientific and medical backgrounds. ARC assess the company’s research proposal, including patient/participant involvement, potential future value to patients/the NHS and the ethics of the proposal.

The ARC will assess whether there has been any Patient and Public Involvement and Engagement (PPIE) informing the research questions and design. For many commercial applications that are exploring early-stage research and development (R&D), for example, target identification and validation, there will not have been any PPIE because the research may be tied to exploring fundamental biological mechanisms and pathways rather than particular conditions or phenotypes. If there has been PPIE, the ARC will determine whether it has adequately informed the research questions and design, and whether there is a commitment to ongoing PPIE and transparency following the outcomes of the research. Although PPIE is not a requirement of applications, ARC encourage applicants to consider at what stage in their R&D process it would be appropriate to consult with patient advocacy and participation groups.

Genomics England will only work with companies that are aligned with its strategy and mission to bring the benefits of genomic medicine to everyone. The Partnerships Development team will assess whether a company seeking access to NGRL data is working in the cancer or rare disease diagnostics and therapeutics space, or supporting UK Government strategic scientific initiatives – if not, Genomics England would not permit an application to ARC in the first place. All applications must conform to the acceptable uses set out in the REC-approved NGRL protocol. If the research proposal is for later stage research that has a clear pathway to intended patient or health system benefit, the ARC would expect to see this articulated as part of the rationale for seeking access to NGRL data. Given the early stage of much commercial genomics research, not all accepted applications will be able to demonstrate a clear explanation of the expected healthcare benefits.

Approval process for GeCIP users (academic) of the NGRL:

• Researcher visits Genomics England website to enrol as a GECIP member

• Completion of onboarding process; Verification by their institution (institution will be required to sign a Genomics participation agreement and appoint a membership secretary), verification of their self-stated qualifications and areas of research interest by the GEL Scientific Manager to join their domain of choice, take the IG and GECIP rules training course and pass test with at least 80%. They are then able to access the NGRL and the Research Portal (the area where prospective GeCIP applicants can apply and register their research project)

• Within 3 months of gaining access they need to either submit a research proposal for Genomics England approval, which currently has to fit with the Detailed Research Plan for their domain, or join another registered project. Otherwise they will lose access.

• On an annual basis, complete a survey sent out by Genomics England giving details of their research progress and any outputs, to aid reporting to ARC.

• Any data they wish to either import or export to/from the NGRL has to be approved by Airlock (Airlock policy is described below) as not being personally identifiable.

• If a researcher has not accessed the NGRL, the Research Portal, or logged into their GEL account to gain access to either of the previous for 6 months their account will be deactivated.

All research activities undertaken in the NGRL aim to enrich the existing dataset via one or multiple routes:

• Identification of diagnoses originally missed by the standardised pipeline

• Feedback of new diagnoses to patients

• Mobilising samples which can help to identify diagnoses that were missed through analyses of WGS alone

Researchers can access pseudonymised Data through NGRL under sub licence. The only Data allowed to be exported are summary results. An airlock policy has been established which enables material (data, files, tools etc) to be moved in or out of the NGRL in a controlled and supervised manner; facilitating research and discovery, while maintaining control of security and access.

Data accessed under sub licence is only granted to named individuals identified to Genomics England who agree to comply with the Airlock policy, Information Governance and IT Security Policy. Before being provided with credentials necessary to access the NGRL a Company Researcher must complete information governance training which shall be provided by Genomics England.

AIRLOCK POLICY:

The following rules are applied to all airlock requests:

1. All relevant details of the summary results to be transferred must be provided with every request.

2. All summary results transferred must be checked by Genomics England to ensure compliance with the relevant policies. Users will be notified of any summary results rejected along with the reason for the rejection.

3. All imports will be checked for viruses and malware and those failing this test will be rejected. It is the responsibility of the requestors to resolve such issues before re-submitting the file for transfer.

4. Summary results requested for transfer are assessed using the following criteria:

a. whether the request aligns with the users ARC approval in full;

b. whether the request can clearly be demonstrated to be aligned with a registered project in the NGRL;

c. any data security implications;

d. any disclosure risks;

e. the technical feasibility and associated cost of the request;

f. when importing data, its scientific value to the community of researchers within the NGRL, and when and how it will be shared;

g. when importing data, checks will be performed to ensure that the data importer owns the data and holds the correct consents and approvals.

The Airlock Manager has formal delegated approval to approve requests where there is precedent from previous Airlock Review Committees. For more complicated requests or where no precedent has been set these will go to the airlock committee for review and a decision. The airlock committee is a delegation of the Genomics England Chief Scientist who responsible for oversight of all airlock requests in accordance with the airlock policy. The committee comprises of:

• Technical Lead

• User Community Representative

• Bioinformatics Director

• Caldicott Guardian

• Chief Scientist representative

The Data will be processed worldwide.

Access is restricted to substantive employees of Genomics England, Genomics Clinical Interpretation Partners (GeCIP) members, and members of the Discovery Forum, who have authorisation from the Principal Investigator.

GeCIP membership is open to any individual, student or member of staff, who is affiliated with a host institution which include the following:

• UK academic research institutions (e.g., universities, research institutions etc.)

• NHS trusts or authorities

• UK and foreign charitable organisations directly related to the focus of the 100,000 Genomes Project

• Foreign universities and research institutions that carry out significant research activity

• UK and foreign governmental departments that carry out significant research activity (e.g., Medical Research Council (MRC), National Institute of Health (NIH), Public Health England (PHE))

• Foreign healthcare organisations (private or public) that undertake significant research activity

To be eligible for data access as a GeCIP member, applicants must meet these requirements:

• Their host institution has signed a GeCIP Participation Agreement, which outlines the key principles that members of each institution must adhere to, including the Intellectual Property and Publication Policy.

• Their host institution has verified that they are affiliated with that institution.

• The applicant’s GeCIP domain has submitted a detailed research plan and it has been approved by the Genomics England Access Review Committee (see below).

• The GeCIP domain lead has approved the application.

• Following approval, GeCIP researchers must sign a specific agreement (‘GeCIP rules’) covering their behaviour and working practice within the data infrastructure.

• Data access will not then be granted until a researcher has successfully passed mandatory information governance training.

All applications have to provide health and social care benefits in England and are reviewed by a panel (the Access Review Committee (ARC)).

The ARC provides an independent examination of requests for data access. The ARC comprises external scientific experts, patient representatives and members of Genomics England’s Participant Panel.

GeCIP users will be granted access to all data and knowledge held within the NGRL. Each GeCIP domain will have access to its own private shared area of the NGRL for data storage and collaboration. The secure virtual desktop infrastructure will provide the ‘workspace’ for clinical teams, research groups and trainees to undertake their work.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will be linked at person record level with the patient’s genetic data within the NGRL. This includes the following data:

> National Cancer Registration and Analysis Service (NCRAS)

and uncurated NCRAS data

> Secure Anonymised Information Linkage (SAIL) data; Welsh data

> Patient samples (e.g., blood, saliva, tissue, RNA, plasma and serum)

> NHS Trusts data

> Data feeds from the Intensive Care National Audit Registry (ICNARC)

> The UK Health Security Agency (UKHSA) viral genomic data and associated metadata

The Data will not be linked with any other data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised Dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised Dataset.

To protect patient confidentiality, access to the NGRL will be granted only for specific, approved purposes in accordance with informed consent. Any attempted use beyond the specified purpose may lead to exclusion and possible legal action, where appropriate.

Data accessed under sub licence will not be re-identified.

Genomics England rely on GDPR Article 6 (1)(f) for the personal data and Article 9(2)(j) for the special category data shared within the NGRL.

Data shared through the Airlock process is aggregate data only and is t herefore not personal data so does not require a legal basis under the UK GDPR.

A release register detailing any sub licences and onward sharing can be found here: https://research.genomicsengland.co.uk/research-registry/browse

Genomics will take responsibility for the actions and omissions of all sub licences and breach of a sub licence will automatically be regarded as breach of the Data Sharing Framework Contract.

In the event of termination or expiry of the Data Sharing Framework Contract between NHS England and the applicant, Data from NHS England will be removed from the NGRL, preventing access to the Data for all users.

NHS England will require the ability to audit the sub licensee.

Combining genomic sequence data from COVID participants together with their medical records has created a ground-breaking research resource. Researchers are currently studying this data to be able to deliver outputs that will have tangible benefits to healthcare and patients. Understanding the symptoms and impact of COVID on people with differing genetic make-ups is hoped to lead to successful treatment of the disease being investigated.

Specific outputs for Genomics England are to continue to release updated genomic and clinical data into the NGRL to support this ongoing research. Each research group who accesses this data will have their own defined output strategy and expectations which they will aim to deliver against. Specific examples of journal outputs are as follows:

• A first update on mapping the human genetic architecture of COVID-19 (2022) Nature 608(7921):E1-E10. doi: 10.1038/s41586-022-04826-7

• Mapping the human genetic architecture of COVID-19 (2021) Nature 600(7889):472-477. doi: 10.1038/s41586-021-03767-x

• Whole-genome sequencing reveals host factors underlying critical COVID-19 (2022) Nature 607(7917):97-103. doi: 10.1038/s41586-022-04576-6

• Genetic mechanisms of critical illness in COVID-19 (2021) Nature 591(7848):92-98. doi: 10.1038/s41586-020-03065-y

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS Digital. Understanding this significant value is why Genomics England are so keen to add NHS Digital data to its clinical data source for the GenOMICC study.

This proposal has already enabled Genomics England to discover new rare and common variants alongside new multi-omic biomarkers that underpin host response to infection, allowing investigation of the impact of viral genomic features on outcomes. The ongoing prospective component could allow nested clinical trials or case-control resources to add value to this study by detecting variants, which stratify response or predict outcomes. Benefits thus far stated below.

Summary of publications and value of study updated August 2022:

Genome wide studies (GWAS) of first 2244 GenOMICC participants admitted with severe COVID

May 2021:

• Identified 4 targets that can utilise and repurpose currently used medications for treatment and management of severe covid.

• Found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. This mechanism may also be amenable to targeted treatment with existing drugs.

These results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19.

Mapping the human genetic architecture of COVID-19

Dec 2021

• Contributed to the meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries.

• Identified 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases.

• They represent potentially actionable mechanisms in response to infection.

• There is evidence of a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes.

This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

May 2022

• Identified TMPRSS2 variant has a protective effect against severe COVID-19

• This is a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID-19

Whole genome sequencing of 7,491 GenOMICC participants admitted with severe COVID

Jul 2022

• Identified 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2)

• Found evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease.

• Found evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets.

The results show that comparisons between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Aug 2022

• Contributed to the meta-analyses bringing together 60 studies from 25 countries for 3 COVID-19 phenotypes.

• Between-study heterogeneity rather than differences across ancestries are a more likely explanation for the observed heterogeneity in the effect sizes across studies

• Identified that the variant rs35705950:G>T located in the promoter of MUC5B (11p15.5) is protective against hospitalization

• Identified that rs190509934:T>C, which is upstream of ACE2, is associated with decreased susceptibility risk. Recent results have shown that the rs190509934:T>C variant lowers ACE2 expression, which in turn confers protection against SARS-CoV-2 infection12.

The biological insights gained by this expansion of the COVID-19 Host Genetic Initiative showed that increasing sample size and diversity remain a fruitful activity to better understand the human genetic architecture of COVID-19.

The first genomes from severe volunteers came through in June 2020.

By June 2021, interim findings from the study were published. These findings have already helped doctors make better decisions when treating patients with COVID-19, resulting in better outcomes. In addition, two therapeutic drug trials have also commenced.

By March 2022 some 16 new genetic variants associated with severe Covid-19, including some related to blood clotting, immune response and intensity of inflammation, have been identified. These findings will act as a roadmap for future efforts, opening new fields of research focused on potential new therapies and diagnostics with pinpoint accuracy.

Determining the whole genome sequence for all participants in the study allowed the team to create a precise map and identify genetic variation linked to severity of Covid-19. The team found key differences in 16 genes in the ICU patients when compared with the DNA of the other groups. They also confirmed the involvement of seven other genetic variations already associated with severe Covid-19 discovered in earlier studies from the same team. The findings included how a single gene variant that disrupts a key messenger molecule in immune system signalling – called interferon alpha-10 – was enough to increase a patient’s risk of severe disease. This highlights the gene’s key role in the immune system and suggests that treating patients with interferon – proteins released by immune cells to defend against viruses – may help manage disease in the early stages. The study also found that variations in genes that control the levels of a central component of blood clotting – known as Factor 8 – were associated with critical illness in Covid-19. This may explain some of the clotting abnormalities that are seen in severe cases of Covid-19. Factor 8 is the gene underlying the most common type of haemophilia.

Genomics England requires access to NHS England data for the purpose of the following work programme:

The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole Genome Sequencing (WGS) of patients severely affected by COVID-19.

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS England and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people)

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England National Genomics Research Library (NGRL) to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and its outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By utilising the GenOMICC consortium’s prospective study design that leverages existing recruitment infrastructure in critical care, Genomics England will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

The following NHS England Data will be accessed:

• Hospital Episode Statistics

o Admitted Patient Care

o Accident & Emergency

o Critical Care

o Outpatients

• Emergency Care Data Set (ECDS)

These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

• Diagnostic Imaging Dataset (DID) necessary to provide invaluable, detailed information to build on participants' phenotypes, e.g., tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

• Civil Registrations of Death- Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

• Cancer Registration - necessary to see the incidence of cancer within the cohort

• Covid-19 SGSS First Positives (Second Generation Surveillance System)

• Covid-19 Vaccination Status

• Covid-19 Hospitalization in England Surveillance System

These datasets, including vaccination, SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus. These will remain only for COVID based research only.

• Mental Health Services Data Set- The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

• Covid-19 General Practise Extraction Service assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings. Genomics England understand this dataset will be used only for COVID research going forward.

The level of the Data will be

• Identifiable- many indirect identifiable Data items have been requested because they provide valuable Data that can help researchers make new scientific and medical discoveries. All directly identifiable Data items will either be removed or transformed according to best practice agreed with NHSE. De-identification is a key facet of the Genomics England resource. De-identified data are uploaded to the NGRL hosted by Genomics England on a monthly basis, where they are linked to participant genomes and primary clinical data

The Data will be minimised as follows.

• Limited to a study cohort identified by Genomics England of;

• ~100,000 patients who consented to participate. ~30,000 of which recruited by Geonomics meeting the study's COVID-19 eligibility criteria, and ~71,243 as a control cohort.

• Genomics England request full history of patient Data to provide maximum insight, and therefore maximum value to the researchers accessing the Data. Because of the wide scope of the proposal, there are no other alternative or less intrusive ways of achieving the purpose described.

Genomics England is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above. Genomics England also process the Data.

The University of Edinburgh is responsible for acquisition of primary clinical data. That relates to data acquired at patient registration. Genomics England in its provision of whole genome sequencing are applying to NHS England for secondary clinical data to link to the genomic data.

Staff and academics from the University of Edinburgh are required to join a Genomics England Clinical Interpretation Partnership (GeCIP) to access the secondary clinical data from NHS England within the NGRL. Please see the processing activities of this DSA for further detail on GeCIP.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party.

It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

The funding is provided the Department of Health and Social Care. The funding is specifically for the purposes described.

The funder will have no ability to suppress or otherwise limit the publication of findings.

Lifebit provides IT support to Genomics England.

Amazon Web Services (AWS) provides IT back up services to Genomics England and will store copies of the Data as contracted by Genomics England.

SUB-LICENCING:

Genomics Clinical Interpretation Partners (GeCIP) members (Academic research organisations), and members of the Discovery Forum (Commercial organisations) will also have access to the pseudonymised Data within the NGRL, subject to internal approval by Genomics England. NHS England Data is combined with the genomic and sample data within the NGRL, providing a more comprehensive medical history, and going forward, a more comprehensive patient journey which will be a valuable resource for medical research. All applications have to provide health and social care benefits and are reviewed by a panel (the Access Review Committee (ARC)) before access is granted.

It is anticipated that the volume of sub-licences will be 150-200 per year. The GeCIP sub licence agreement is indefinite, until it is terminated by either the GeCIP member or Genomics.

The Data Access Agreement for Discovery Forum Members has a specified term, normally 12 months, at which point the company and Genomics can choose to renew or not.

All requests for data access will be subject to the following considerations:

• Protection of data subjects (honouring commitments made to them, acting within the scope of consent and according to conditions of Research Ethics Committee approval).

• Compliance with legal and regulatory requirements General Data Protection Regulation 2018, Data Protection Bill 2017, Freedom of Information Act 2000, NHS Act 2006, Health and Social Care Act 2012, the Common Law Duty of Confidentiality, Human Tissue Act 2004 and applicable requirements from organisations affiliated with the Health Research Authority, including Research Ethics Committees and the Confidentiality Advisory Group (CAG).

• Provision of a signed Genomics England data access agreement to the Access Review Committee.

• Prioritisation of access according to resource availability.

• Facilitation of high-quality health research

Commercial partnerships are crucial to achieving the aims of the NGRL and are achieved through the Discovery Forum. As with the non-commercial academic research led by GeCIP, commercial research aims to bring benefit to the patients and, through the use of the Data, inform development of platforms and tools for future diagnostic discovery. Commercial research can be broadly categorised into four themes that answer different questions along the typical Research and Discovery Biopharmaceutical Pipeline. At a high level they are divided into:

• Diagnostic discovery

• Pre-clinical research

• Clinical Trials Referral

• Real World Evidence / Market Access

Approval process for Commercial organisations for access to the NGRL:

Discovery Forum applications from a commercial organisation would be reviewed for suitability by the Partnership Development (PD)Team. The PD Team consider the credentials of the applying organisation including consideration of adverse public perception and reputational risk from approving data access for that organisation. If the PD Team feel appropriate, they are then passed on to be scrutinised by the independent Access Review Committee (ARC). ARC is constituted of Participant Panel members and senior individuals from various scientific and medical backgrounds. ARC assess the company’s research proposal, including patient/participant involvement, potential future value to patients/the NHS and the ethics of the proposal.

The ARC will assess whether there has been any Patient and Public Involvement and Engagement (PPIE) informing the research questions and design. For many commercial applications that are exploring early-stage research and development (R&D), for example, target identification and validation, there will not have been any PPIE because the research may be tied to exploring fundamental biological mechanisms and pathways rather than particular conditions or phenotypes. If there has been PPIE, the ARC will determine whether it has adequately informed the research questions and design, and whether there is a commitment to ongoing PPIE and transparency following the outcomes of the research. Although PPIE is not a requirement of applications, ARC encourage applicants to consider at what stage in their R&D process it would be appropriate to consult with patient advocacy and participation groups.

Genomics England will only work with companies that are aligned with its strategy and mission to bring the benefits of genomic medicine to everyone. The Partnerships Development team will assess whether a company seeking access to NGRL data is working in the cancer or rare disease diagnostics and therapeutics space, or supporting UK Government strategic scientific initiatives – if not, Genomics England would not permit an application to ARC in the first place. All applications must conform to the acceptable uses set out in the REC-approved NGRL protocol. If the research proposal is for later stage research that has a clear pathway to intended patient or health system benefit, the ARC would expect to see this articulated as part of the rationale for seeking access to NGRL data. Given the early stage of much commercial genomics research, not all accepted applications will be able to demonstrate a clear explanation of the expected healthcare benefits.

Approval process for GeCIP users (academic) of the NGRL:

• Researcher visits Genomics England website to enrol as a GECIP member

• Completion of onboarding process; Verification by their institution (institution will be required to sign a Genomics participation agreement and appoint a membership secretary), verification of their self-stated qualifications and areas of research interest by the GEL Scientific Manager to join their domain of choice, take the IG and GECIP rules training course and pass test with at least 80%. They are then able to access the NGRL and the Research Portal (the area where prospective GeCIP applicants can apply and register their research project)

• Within 3 months of gaining access they need to either submit a research proposal for Genomics England approval, which currently has to fit with the Detailed Research Plan for their domain, or join another registered project. Otherwise they will lose access.

• On an annual basis, complete a survey sent out by Genomics England giving details of their research progress and any outputs, to aid reporting to ARC.

• Any data they wish to either import or export to/from the NGRL has to be approved by Airlock (Airlock policy is described below) as not being personally identifiable.

• If a researcher has not accessed the NGRL, the Research Portal, or logged into their GEL account to gain access to either of the previous for 6 months their account will be deactivated.

All research activities undertaken in the NGRL aim to enrich the existing dataset via one or multiple routes:

• Identification of diagnoses originally missed by the standardised pipeline

• Feedback of new diagnoses to patients

• Mobilising samples which can help to identify diagnoses that were missed through analyses of WGS alone

Researchers can access pseudonymised Data through NGRL under sub licence. The only Data allowed to be exported are summary results. An airlock policy has been established which enables material (data, files, tools etc) to be moved in or out of the NGRL in a controlled and supervised manner; facilitating research and discovery, while maintaining control of security and access.

Data accessed under sub licence is only granted to named individuals identified to Genomics England who agree to comply with the Airlock policy, Information Governance and IT Security Policy. Before being provided with credentials necessary to access the NGRL a Company Researcher must complete information governance training which shall be provided by Genomics England.

AIRLOCK POLICY:

The following rules are applied to all airlock requests:

1. All relevant details of the summary results to be transferred must be provided with every request.

2. All summary results transferred must be checked by Genomics England to ensure compliance with the relevant policies. Users will be notified of any summary results rejected along with the reason for the rejection.

3. All imports will be checked for viruses and malware and those failing this test will be rejected. It is the responsibility of the requestors to resolve such issues before re-submitting the file for transfer.

4. Summary results requested for transfer are assessed using the following criteria:

a. whether the request aligns with the users ARC approval in full;

b. whether the request can clearly be demonstrated to be aligned with a registered project in the NGRL;

c. any data security implications;

d. any disclosure risks;

e. the technical feasibility and associated cost of the request;

f. when importing data, its scientific value to the community of researchers within the NGRL, and when and how it will be shared;

g. when importing data, checks will be performed to ensure that the data importer owns the data and holds the correct consents and approvals.

The Airlock Manager has formal delegated approval to approve requests where there is precedent from previous Airlock Review Committees. For more complicated requests or where no precedent has been set these will go to the airlock committee for review and a decision. The airlock committee is a delegation of the Genomics England Chief Scientist who responsible for oversight of all airlock requests in accordance with the airlock policy. The committee comprises of:

• Technical Lead

• User Community Representative

• Bioinformatics Director

• Caldicott Guardian

• Chief Scientist representative

The Data will be processed worldwide.

Access is restricted to substantive employees of Genomics England, Genomics Clinical Interpretation Partners (GeCIP) members, and members of the Discovery Forum, who have authorisation from the Principal Investigator.

GeCIP membership is open to any individual, student or member of staff, who is affiliated with a host institution which include the following:

• UK academic research institutions (e.g., universities, research institutions etc.)

• NHS trusts or authorities

• UK and foreign charitable organisations directly related to the focus of the 100,000 Genomes Project

• Foreign universities and research institutions that carry out significant research activity

• UK and foreign governmental departments that carry out significant research activity (e.g., Medical Research Council (MRC), National Institute of Health (NIH), Public Health England (PHE))

• Foreign healthcare organisations (private or public) that undertake significant research activity

To be eligible for data access as a GeCIP member, applicants must meet these requirements:

• Their host institution has signed a GeCIP Participation Agreement, which outlines the key principles that members of each institution must adhere to, including the Intellectual Property and Publication Policy.

• Their host institution has verified that they are affiliated with that institution.

• The applicant’s GeCIP domain has submitted a detailed research plan and it has been approved by the Genomics England Access Review Committee (see below).

• The GeCIP domain lead has approved the application.

• Following approval, GeCIP researchers must sign a specific agreement (‘GeCIP rules’) covering their behaviour and working practice within the data infrastructure.

• Data access will not then be granted until a researcher has successfully passed mandatory information governance training.

All applications have to provide health and social care benefits in England and are reviewed by a panel (the Access Review Committee (ARC)).

The ARC provides an independent examination of requests for data access. The ARC comprises external scientific experts, patient representatives and members of Genomics England’s Participant Panel.

GeCIP users will be granted access to all data and knowledge held within the NGRL. Each GeCIP domain will have access to its own private shared area of the NGRL for data storage and collaboration. The secure virtual desktop infrastructure will provide the ‘workspace’ for clinical teams, research groups and trainees to undertake their work.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will be linked at person record level with the patient’s genetic data within the NGRL. This includes the following data:

> National Cancer Registration and Analysis Service (NCRAS)

and uncurated NCRAS data

> Secure Anonymised Information Linkage (SAIL) data; Welsh data

> Patient samples (e.g., blood, saliva, tissue, RNA, plasma and serum)

> NHS Trusts data

> Data feeds from the Intensive Care National Audit Registry (ICNARC)

> The UK Health Security Agency (UKHSA) viral genomic data and associated metadata

The Data will not be linked with any other data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised Dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised Dataset.

To protect patient confidentiality, access to the NGRL will be granted only for specific, approved purposes in accordance with informed consent. Any attempted use beyond the specified purpose may lead to exclusion and possible legal action, where appropriate.

Data accessed under sub licence will not be re-identified.

Genomics England rely on GDPR Article 6 (1)(f) for the personal data and Article 9(2)(j) for the special category data shared within the NGRL.

Data shared through the Airlock process is aggregate data only and is t herefore not personal data so does not require a legal basis under the UK GDPR.

A release register detailing any sub licences and onward sharing can be found here: https://research.genomicsengland.co.uk/research-registry/browse

Genomics will take responsibility for the actions and omissions of all sub licences and breach of a sub licence will automatically be regarded as breach of the Data Sharing Framework Contract.

In the event of termination or expiry of the Data Sharing Framework Contract between NHS England and the applicant, Data from NHS England will be removed from the NGRL, preventing access to the Data for all users.

NHS England will require the ability to audit the sub licensee.

Combining genomic sequence data from COVID participants together with their medical records has created a ground-breaking research resource. Researchers are currently studying this data to be able to deliver outputs that will have tangible benefits to healthcare and patients. Understanding the symptoms and impact of COVID on people with differing genetic make-ups is hoped to lead to successful treatment of the disease being investigated.

Specific outputs for Genomics England are to continue to release updated genomic and clinical data into the NGRL to support this ongoing research. Each research group who accesses this data will have their own defined output strategy and expectations which they will aim to deliver against. Specific examples of journal outputs are as follows:

• A first update on mapping the human genetic architecture of COVID-19 (2022) Nature 608(7921):E1-E10. doi: 10.1038/s41586-022-04826-7

• Mapping the human genetic architecture of COVID-19 (2021) Nature 600(7889):472-477. doi: 10.1038/s41586-021-03767-x

• Whole-genome sequencing reveals host factors underlying critical COVID-19 (2022) Nature 607(7917):97-103. doi: 10.1038/s41586-022-04576-6

• Genetic mechanisms of critical illness in COVID-19 (2021) Nature 591(7848):92-98. doi: 10.1038/s41586-020-03065-y

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS Digital. Understanding this significant value is why Genomics England are so keen to add NHS Digital data to its clinical data source for the GenOMICC study.

This proposal has already enabled Genomics England to discover new rare and common variants alongside new multi-omic biomarkers that underpin host response to infection, allowing investigation of the impact of viral genomic features on outcomes. The ongoing prospective component could allow nested clinical trials or case-control resources to add value to this study by detecting variants, which stratify response or predict outcomes. Benefits thus far stated below.

Summary of publications and value of study updated August 2022:

Genome wide studies (GWAS) of first 2244 GenOMICC participants admitted with severe COVID

May 2021:

• Identified 4 targets that can utilise and repurpose currently used medications for treatment and management of severe covid.

• Found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. This mechanism may also be amenable to targeted treatment with existing drugs.

These results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19.

Mapping the human genetic architecture of COVID-19

Dec 2021

• Contributed to the meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries.

• Identified 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases.

• They represent potentially actionable mechanisms in response to infection.

• There is evidence of a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes.

This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

May 2022

• Identified TMPRSS2 variant has a protective effect against severe COVID-19

• This is a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID-19

Whole genome sequencing of 7,491 GenOMICC participants admitted with severe COVID

Jul 2022

• Identified 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2)

• Found evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease.

• Found evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets.

The results show that comparisons between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Aug 2022

• Contributed to the meta-analyses bringing together 60 studies from 25 countries for 3 COVID-19 phenotypes.

• Between-study heterogeneity rather than differences across ancestries are a more likely explanation for the observed heterogeneity in the effect sizes across studies

• Identified that the variant rs35705950:G>T located in the promoter of MUC5B (11p15.5) is protective against hospitalization

• Identified that rs190509934:T>C, which is upstream of ACE2, is associated with decreased susceptibility risk. Recent results have shown that the rs190509934:T>C variant lowers ACE2 expression, which in turn confers protection against SARS-CoV-2 infection12.

The biological insights gained by this expansion of the COVID-19 Host Genetic Initiative showed that increasing sample size and diversity remain a fruitful activity to better understand the human genetic architecture of COVID-19.

The first genomes from severe volunteers came through in June 2020.

By June 2021, interim findings from the study were published. These findings have already helped doctors make better decisions when treating patients with COVID-19, resulting in better outcomes. In addition, two therapeutic drug trials have also commenced.

By March 2022 some 16 new genetic variants associated with severe Covid-19, including some related to blood clotting, immune response and intensity of inflammation, have been identified. These findings will act as a roadmap for future efforts, opening new fields of research focused on potential new therapies and diagnostics with pinpoint accuracy.

Determining the whole genome sequence for all participants in the study allowed the team to create a precise map and identify genetic variation linked to severity of Covid-19. The team found key differences in 16 genes in the ICU patients when compared with the DNA of the other groups. They also confirmed the involvement of seven other genetic variations already associated with severe Covid-19 discovered in earlier studies from the same team. The findings included how a single gene variant that disrupts a key messenger molecule in immune system signalling – called interferon alpha-10 – was enough to increase a patient’s risk of severe disease. This highlights the gene’s key role in the immune system and suggests that treating patients with interferon – proteins released by immune cells to defend against viruses – may help manage disease in the early stages. The study also found that variations in genes that control the levels of a central component of blood clotting – known as Factor 8 – were associated with critical illness in Covid-19. This may explain some of the clotting abnormalities that are seen in severe cases of Covid-19. Factor 8 is the gene underlying the most common type of haemophilia.

This Agreement is seeking approval to request continued supply of data to support The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole Genome Sequencing (WGS) of patients severely affected by COVID-19. The work programme has sign off and prioritisation from the Chief Medical Officer for England (CMO)

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS Digital and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people)

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England Trusted Research Environment (TRE) to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and its outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel.

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By utilising the GenOMICC consortium’s prospective study design that leverages existing recruitment infrastructure in critical care, Genomics England will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

Genomics England Background: (For Context)

Genomics England was established by the Department of Health to deliver the 100,000 Genomes Project. This followed the announcement in December 2012 by the Prime Minister of a programme of whole genome sequencing (WGS) as part of the UK Government’s Life Sciences Strategy. The principal objective of the 100,000 Genomes Project was to sequence 100,000 genomes from participants with cancer and rare disorders, and to link the sequence data to a standardised, extensible account of diagnosis, treatment, and outcomes gathered at recruitment, but primarily through the ongoing collection of medical records.

Data will be released into the Genomics England TRE where it will be linked with associated clinical data as well as additional data sources, which will include NHS Digital data requested through this agreement, COVID-19 testing feeds and viral genomics from Public Health England and data feeds from the Intensive Care National Audit Registry (ICNARC).

The Department of Health and Social Care have granted approval for Genomics England to procure a new, rapidly deployable TRE for the COVID-19 programme from existing core funding, which will provide a secure and collaborative workspace that enables researchers to perform COVID-19 genomic data analysis. The new TRE (COVID-RE) will provide an intuitive, integrated and collaborative user experience that enables effective COVID-19 research outcomes across a wide range of academic and Biotech/Pharma researchers with varying levels of technical competency. This offers a major upgrade to Genomics England’s current environment and will comprise user-centric, contemporary bioinformatic workflows, support opensource tooling, and enable shared workspaces between Genomics England and Partners. COVID-RE must serve the immediate COVID-19 research effort and may also advance the transformation of Genomics England’s platform infrastructure, which is a key enabler to the research community.

There are two key value streams provided by the COVID-RE. Firstly ‘raw data to analytics ready data’ stream which must permit the collection of data from multiple locations from unstructured, through semi and fully structured forms and transforms them the appropriate data model, data store based on their ongoing use and availability. Secondly the ‘discovery to insight’ stream that supports researchers by providing the capability and the framework to support their User Journey from understanding the data available to them through to providing the necessary analytics and publishing tools.

The newly established COVID-RE will provide the following:

• Seamless interface with cloud storage and compute capabilities.

• A unified data platform containing datastores appropriate for all the required clinical and genomic data types.

• Data integration capability to deliver analytics-ready datasets into domain-specific data stores across batch and streaming integration patterns.

• Standards-based access services providing secure, fast, flexible, robust and auditable access to TRE data assets.

• Applications to support the research user journey from an exploration of data sets, through cohort building, analysis and publication - providing tools appropriate to a variety of user requirements (ways of working) and programming competency.

• Applications and workflows can be delivered natively within the platform, however COVID-RE must enable access to container-based applications and, via a set of hardened APIs, to a relevant external service (as long as security is maintained).

Details of the sublicense model via the Genomics England TRE are supplied within the processing activities section of this agreement.

Regarding genome data sharing with sublicensees - As an example, if an individual’s whole-exome or whole-genome sequence forms part of a database but all other records and identifiers have been fully deleted so that all that remains is sequence data, this data could easily be ‘individuated’ or singled out. However, it can be argued that it cannot be connected to a natural person without something further which can relate it to them.

In this perspective, the Global Alliance for Genomics and Health (GA4GH) has grouped together to provide unified strategies for addressing the major challenges of this data revolution. Genomics England are key members in this alliance and a recent publication (https://www.cell.com/cell-genomics/fulltext/S2666-979X(21)00036-7) presents the GA4GH suite of secure, interoperable technical standards and policy frameworks

• GA4GH and the PHG foundation both suggest that genetic, and particularly genomic information should not be viewed as inherently or directly identifying without some further link to or impact on an individual

• To that end, Genomics' TRE is a leading light in security and standards as per HDR UK (https://zenodo.org/record/5767586#.YcPE9hPP27M) and an author is an employee of Genomics England.

• Furthermore, Genomics' Airlock policy is clear and explicit about the level of data that can be extracted and does not permit row level/ individual data extraction

The additional clinical data is key for researchers to be able to understand and infer clinically relevant and actionable findings. The aim is to provide a high quality, diverse clinical dataset, detailing each participant’s journey and to understand pre-existing conditions and also the early behaviours in the disease course. Genomics England currently have an agreement to receive NHS Digital data for the extant 100,000 Genomes Project participants (DARS-NIC-12784) and have seen first-hand the depth and quality of the data and how it has aided researchers.

To that aim, the significant gap in the current data collection for the COVID-19 project can be addressed by the non-standard NHS Digital data feed.

The Secondary Use Services Admitted Patient Care Feed (SUS APC) would provide as close to real-time data for researchers and in the current climate is vital to ensure no delays.

The associated COVID-19 datasets (including NHS111 and CV19 Testing Data in particular which will be requested under a future version of this agreement) will add to the detail in patient journey course, flagging for instance how participants were monitoring their symptoms and was there an associated poor prognosis.

The group of survivors eligible for recruitment for this study are generally healthy individuals who have suffered critical illness. It is anticipated this cohort will grow to approx. 36,000 participants.

The data would be available for analysis alongside the extant Genomics England data set of 100,000 Genomes Project participants and would be made available to approved researchers worldwide as per existing governance procedures. This 100,000 Genomes Project data set will act as an appropriate matched control group. Data on the 100,000 Genomes Cohort will be provided to NHS Digital for linkage - (as they will act as a control cohort), as well as new additions for the GenOMICC Study.

The below detail pertains to the background of the study and susceptibility to infection sets out why Genomics are investigating. The origin of the GenOMICC study was focused on smaller cohorts of participants. However, in collaboration with the COG-UK group, this is now expanded to whole genome sequence of approx. 36,000 affected individuals as set out above.

GenOMICC Study Background:

Susceptibility to infection is profoundly heritable (Sorensen et al. 1988). Patients who develop life-threatening illness following infection with usually innocuous pathogens, such as influenza (Miller et al. 2010), are genetically different from the rest of the population (Albright et al. 2008). Understanding the genetic mechanisms of susceptibility may yield new therapeutic targets (Baillie 2014) that can be used to make susceptible patients more similar to individuals who are resistant to, or tolerant of, specific pathogens.

The genetic mechanisms of susceptibility to infection are likely to be highly pathogen-specific and may even have opposing roles in different infections (as for CCR5 variants in HIV [Human Immunodeficiency Virus] (Huang et al. 1996) and WNV (Glass et al. 2006) infection). Pathogen-specific interventions (e.g., small molecules to inhibit an enzyme or receptor that is dysfunctional in resistant individuals) would therefore be protective to the host in a similar way to antibiotics, with the advantage that it is conceptually more difficult for any one pathogen to evolve resistance to such a therapy.

A second, more challenging problem arises in patients who become critically ill following infection. The patterns of immune-mediated organ dysfunction, immunoparesis, and death are very similar in severe infections and sterile systemic injuries (such as burns, haemorrhage, pancreatitis and trauma). Ultimately, death is a consequence of the host response to injury (Angus and Poll 2013), through final common pathways of organ failure that are clinically and biochemically evident, and unrelated to the original precipitant.

Broadly, the severity of critical illness follows directly from the severity and duration of the initial insult. In bacterial sepsis, early antibiotics are the mainstay of therapy; in influenza, early antivirals; in haemorrhage, early resuscitation; in trauma, urgent action to prevent secondary injury. There are no therapies with which to modulate the host response to systemic injury.

There is a lack of direct evidence of heritability for outcomes of critical illness, due in part to difficulties in defining and quantifying the heterogeneous multi-organ dysfunction syndrome (MODS), and in part due to the rapid pace of change in critical care medicine, making it impossible to tackle this question in long term outcome studies. However, clinical and biological evidence support the hypothesis that the pathogenesis of MODS is immune in origin (Angus and Poll 2013). Hence, predictions can be made from the extensive knowledge of other immune conditions. Whether or not MODS is considered to be an autoimmune or infectious condition is moot: these conditions share a great deal of similarity in genetic predispositions, cell types and mechanisms of pathogenesis. It is therefore very likely that propensity to survive MODS has a heritable component, and there is some direct evidence in support of this hypothesis (Rautanen et al. 2015). If this is the case, then the identity of the specific variants that contribute to outcome could potentially be utilised to design therapies to promote survival after the onset of MODS.

This study aims to identify genetic predisposition to specific syndromes of critical illness. Specifically, susceptibility to life-threatening infections caused by an identified pathogen, and susceptibility to death following the onset of organ failure due to sepsis or sterile injury. In order to maximise the probability of identifying host genetic loci associated with susceptibility, Genomics England will restrict some analyses to younger individuals in good general health and lacking in known predisposing factors.

The same principle was used to determine an upper age limit for inclusion for some analyses. With advancing age, there is an increase in undiagnosed co-morbidity, frailty, and susceptibility to serious complications of infection or critical injury. There is therefore an increase in the probability of susceptibility to, and mortality from, critical illness that is consequent upon non-genetic factors.

Participation Group:

Patients will be identified and recruited in hospital during acute illness. Potential participants will be identified through hospital workers upon presentation at recruiting sites. The disease processes under study have a high mortality, so it is desirable to recruit patients as early as possible in the disease process.

Participants or an appropriate parent/guardian/consultee will be approached by staff trained in consent procedures that protect the rights of the patient and adhere to the ethical principles within the Declaration of Helsinki. Staff will explain the details of the study to the participant or parent/guardian/consultee and allow them time to discuss and ask questions. The staff will review the informed consent form with the person giving consent (or assent) and endeavour to ensure understanding of the contents, including study procedures, risks, benefits, and the right to withdraw. Participants who agree to participate (or their parent/guardian or consultee who declares their wishes to do so) will be asked to sign and date an informed consent form.

In view of the importance of early sampling, participants or their parent/guardian/consultee will be permitted to consent and begin to participate in the study immediately if they wish to do so. Those who prefer more time to consider participation will be approached again after an agreed time, normally one day, to discuss further.

Patients who meet the inclusion/exclusion criteria and who have given informed consent to participate directly, or have been consented by a parent/guardian or whose wishes have been declared by a consultee, will be enrolled to the study.

Samples and data will be collected according to available resources and the weight of the patient will be measured for children under 12 in order to prevent excessive volume sampling. Samples required for medical management will at all times have priority over samples taken for research tests. Aliquots or samples for research purposes should never compromise the quality or quantity of samples required for medical management. Wherever practical, taking research samples should be timed to coincide with clinical sampling. The research team will be responsible for sharing the sampling protocol with health care workers supporting patient management in order to minimise disruption to routine care and avoid unnecessary procedures.

Consent will be sought from patients who survive critical illness and regain capacity to give consent. At each of the follow-up sessions, the investigator gathering data will determine whether the patient has regained capacity. In the event that a patient continues to be incapacitated beyond the follow-up period, the local investigator will plan a subsequent capacity check at a specific date, after an interval to be determined by the nature of the incapacity. The planned dates of capacity checks on incapacitated survivors will be stored locally in the site file, together with a record of the outcome of each check.

Patients who decline to participate at this stage will be removed from the study. Where the patient cannot be recontacted despite best endeavours, they will remain in the study.

Withdrawal:

Participants are freely able to decline participation in this study or to withdraw from participation at any point without suffering any implied or explicit disadvantage. All patients will be treated according to standard practice regardless of whether they participate.

The following options of withdrawal will be made available to participants:

1. Partial withdrawal. Data WILL continue to be updated and used for research, but no further contact will be made with the participant

2. Full withdrawal.

• no further contact will be made with the participant;

• data will not be updated from health records;

• data will not be removed from research that is underway or has already been done, and an audit record will be maintained to confirm participation.

Consent version and life course follow-up

There are a series of consent versions as documented below:

• V1.08 (March 2020) - there are circa 1500 participants on this consent, allows for COVID research but not for longitudinal follow-up. Genomics are exploring reconsenting and the Confidentiality Advisory Group (CAG) as options for this cohort. Currently, these individuals will NOT be submitted to NHS Digital

• V2.1 (April 2020) - Included retention of NHS number and linkage to longitudinal follow -up, NHS Digital are named on the Participant Information Sheet (PIS). These individuals will be submitted to NHS Digital for data linkage

• V2.4 (July 2020) - In addition to already stated in v2.1, this covers community recruitment of participants and movement of identifiers. Sharing data with NHS Digital is again stated. These individuals will be submitted to NHS Digital for data linkage

PIS and Consent Version 2.1 and 2.4 are identical in their reference to accessing data from secondary data suppliers and include retention and collection of identifiable information and both name NHS Digital as a source of linkage. All individuals consented are collected with information including version of consent recruited under, thus genomics England can distinguish individuals based on consent. The most up to date protocol is listed on the website (https://genomicc.org/protocol/)

Datasets requested from NHS Digital:

This agreement permits access to the data sets requested, in line with COVID-19 related purpose. For participants recruited under the consultee process, the restrictions set out in Reg 3( 1) COPI will also apply.

Primary Care dataset: Genomics England anticipate GPES (General Practice Extraction Service) Data for Pandemic Planning and Research (GDPPR) extracts to assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings. Genomics England understand this dataset will be used only for COVID research going forward.

Hospital Episode Statistics (HES): Outpatients (OP), Admitted Patient Care (APC), Critical Care (CC) and Accident & Emergency (AE)/ Emergency Care Data Set (ECDS). These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

Diagnostic Imaging Dataset (DIDS). This provides invaluable, detailed information to build on participants' phenotypes, e.g., tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

Secondary Uses Service datasets. The minimal latency in availability of these datasets is highly desirable for the research objectives set out in this project.

Mental Health Data sets: The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

Cancer Registration Data sets: To see the incidence of cancer within the cohort

Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

COVID datasets: These datasets, including vaccination, SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus. These will remain only for COVID based research only.

Assessment of the datasets has been undertaken and NHS Digital are satisfied that they are necessary for the COVID-19 work being undertaken. Genomics have confirmed that all research which is approved from the GenoMICC study using the data for the COVID-19 specific purposes will be published here https://www.genomicsengland.co.uk/about-gecip/research-2/

Genomics England Industry access:

Genomics England works with industry through its Discovery Forum. The Forum provides a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Industry partners comprise pharmaceutical, biotech and diagnostic companies, and those specialising in laboratory and data analysis. These companies have joined the Forum to work in a pre-competitive environment with access to a selection of genomic and associated clinical data. Ultimately, the Discovery Forum aims to help turn research findings into treatments, diagnostics and benefits for patients as soon as possible.

As the Discovery Forum is a collaborative venture, no fees are levied on participating organisations to access the COVID data, however they are charged based on storage and compute, such as running their own bioinformatics pipeline. All members of the Forum are obliged to publish all findings and research at the point at which intellectual property for any product is protected.

The Forum was created in July 2017 and allows industrial partners to report back to Genomics England on what aspects of the data are proving to be most useful to their research studies, what data is missing and how the data should be collected and developed further so it is captures what industry needs, in a format that is compatible with their research and data systems. These partners act as a 'critical friend' and have made many helpful suggestions to increase the likelihood of successful research in the future for all those using Genomics England's landmark data set.

The lawful basis for processing Participant Data under the General Data Protection Regulation (GDPR) used by Genomics England is legitimate interests as set out under Article 6(1)(f) of the GDPR. It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

Additionally, as Genomics England will be processing health data - a special category of personal data, they will also be processing data under Article 9 (2)(j) as processing is necessary for archiving purposes in the public interest. Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

Combining genomic sequence data from COVID participants together with their medical records has created a ground-breaking research resource. Researchers are currently studying this data to be able to deliver outputs that will have tangible benefits to healthcare and patients. Understanding the symptoms and impact of COVID on people with differing genetic make-ups is hoped to lead to successful treatment of the disease being investigated.

Specific outputs for Genomics England are to continue to release updated genomic and clinical data into the TRE to support this ongoing research. Each research group who accesses this data will have their own defined output strategy and expectations which they will aim to deliver against. Specific examples of journal outputs are as follows:

• A first update on mapping the human genetic architecture of COVID-19 (2022) Nature 608(7921):E1-E10. doi: 10.1038/s41586-022-04826-7

• Mapping the human genetic architecture of COVID-19 (2021) Nature 600(7889):472-477. doi: 10.1038/s41586-021-03767-x

• Whole-genome sequencing reveals host factors underlying critical COVID-19 (2022) Nature 607(7917):97-103. doi: 10.1038/s41586-022-04576-6

• Genetic mechanisms of critical illness in COVID-19 (2021) Nature 591(7848):92-98. doi: 10.1038/s41586-020-03065-y

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS Digital. Understanding this significant value is why Genomics England are so keen to add NHS Digital data to its clinical data source for the GenOMICC study.

This proposal has already enabled Genomics England to discover new rare and common variants alongside new multi-omic biomarkers that underpin host response to infection, allowing investigation of the impact of viral genomic features on outcomes. The ongoing prospective component could allow nested clinical trials or case-control resources to add value to this study by detecting variants, which stratify response or predict outcomes. Benefits thus far stated below.

Summary of publications and value of study updated August 2022:

Genome wide studies (GWAS) of first 2244 GenOMICC participants admitted with severe COVID

May 2021:

• Identified 4 targets that can utilise and repurpose currently used medications for treatment and management of severe covid.

• Found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. This mechanism may also be amenable to targeted treatment with existing drugs.

These results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19.

Mapping the human genetic architecture of COVID-19

Dec 2021

• Contributed to the meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries.

• Identified 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases.

• They represent potentially actionable mechanisms in response to infection.

• There is evidence of a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes.

This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

May 2022

• Identified TMPRSS2 variant has a protective effect against severe COVID-19

• This is a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID-19

Whole genome sequencing of 7,491 GenOMICC participants admitted with severe COVID

Jul 2022

• Identified 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2)

• Found evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease.

• Found evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets.

The results show that comparisons between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Aug 2022

• Contributed to the meta-analyses bringing together 60 studies from 25 countries for 3 COVID-19 phenotypes.

• Between-study heterogeneity rather than differences across ancestries are a more likely explanation for the observed heterogeneity in the effect sizes across studies

• Identified that the variant rs35705950:G>T located in the promoter of MUC5B (11p15.5) is protective against hospitalization

• Identified that rs190509934:T>C, which is upstream of ACE2, is associated with decreased susceptibility risk. Recent results have shown that the rs190509934:T>C variant lowers ACE2 expression, which in turn confers protection against SARS-CoV-2 infection12.

The biological insights gained by this expansion of the COVID-19 Host Genetic Initiative showed that increasing sample size and diversity remain a fruitful activity to better understand the human genetic architecture of COVID-19.

The first genomes from severe volunteers came through in June 2020.

By June 2021, interim findings from the study were published. These findings have already helped doctors make better decisions when treating patients with COVID-19, resulting in better outcomes. In addition, two therapeutic drug trials have also commenced.

By March 2022 some 16 new genetic variants associated with severe Covid-19, including some related to blood clotting, immune response and intensity of inflammation, have been identified. These findings will act as a roadmap for future efforts, opening new fields of research focused on potential new therapies and diagnostics with pinpoint accuracy.

Determining the whole genome sequence for all participants in the study allowed the team to create a precise map and identify genetic variation linked to severity of Covid-19. The team found key differences in 16 genes in the ICU patients when compared with the DNA of the other groups. They also confirmed the involvement of seven other genetic variations already associated with severe Covid-19 discovered in earlier studies from the same team. The findings included how a single gene variant that disrupts a key messenger molecule in immune system signalling – called interferon alpha-10 – was enough to increase a patient’s risk of severe disease. This highlights the gene’s key role in the immune system and suggests that treating patients with interferon – proteins released by immune cells to defend against viruses – may help manage disease in the early stages. The study also found that variations in genes that control the levels of a central component of blood clotting – known as Factor 8 – were associated with critical illness in Covid-19. This may explain some of the clotting abnormalities that are seen in severe cases of Covid-19. Factor 8 is the gene underlying the most common type of haemophilia.

December 2021 Amendment- Version 4.1 of the agreement seeks to change the way in which the common law duty of confidentiality for the cohort is being addressed moving from COPI to consent and in addition requests access to vaccination data.

This agreement is seeking approval to request continued supply of data to support The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole Genome Sequencing (WGS) of patients severely affected by COVID-19. The work programme has sign off and prioritisation from the Chief Medical Officer for England (CMO)

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS Digital and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people)

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England Research Environment to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and it’s outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel.

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By undertaking a prospective study design that leverages existing recruitment infrastructure in critical care, together with Genomics England, NHS England, Devolved Nations and Public Health England (PHE) infrastructure this research will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

Genomics England Background: (For Context)

Genomics England was established by the Department of Health to deliver the 100,000 Genomes Project. This followed the announcement in December 2012 by the Prime Minister of a programme of whole genome sequencing (WGS) as part of the UK Government’s Life Sciences Strategy. The principal objective of the 100,000 Genomes Project was to sequence 100,000 genomes from participants with cancer and rare disorders, and to link the sequence data to a standardised, extensible account of diagnosis, treatment, and outcomes gathered at recruitment, but primarily through the ongoing collection of medical records.

Data will be released into the Genomics England Research Environment where it will be linked with associated clinical data as well as additional data sources, which will include NHS Digital data requested through this agreement, COVID-19 testing feeds and viral genomics from Public Health England and data feeds from the Intensive Care National Audit Registry (ICNARC).

The Department of Health and Social Care have granted approval for Genomics England to procure a new, rapidly deployable Research Environment for the COVID-19 programme from existing core funding, which will provide a secure and collaborative workspace that enables researchers to perform COVID-19 genomic data analysis. The new Research Environment (COVID-RE) will provide an intuitive, integrated and collaborative user experience that enables effective COVID-19 research outcomes across a wide range of academic and Biotech/Pharma researchers with varying levels of technical competency. This offers a major upgrade to our current environment and will comprise user-centric, contemporary bioinformatic workflows, support opensource tooling, and enable shared workspaces between Genomics England and Partners. COVID-RE must serve the immediate COVID-19 research effort and may also advance the transformation of Genomics England’s platform infrastructure, which is a key enabler to the research community.

There are two key value streams provided by the COVID-RE. Firstly ‘raw data to analytics ready data’ stream which must permit the collection of data from multiple locations from unstructured, through semi and fully structured forms and transforms them the appropriate data model, data store based on their ongoing use and availability. Secondly the ‘discovery to insight’ stream that supports researchers by providing the capability and the framework to support their User Journey from understanding the data available to them through to providing the necessary analytics and publishing tools.

The newly established COVID-RE will provide the following:

• Seamless interface with cloud storage and compute capabilities.

• A unified data platform containing datastores appropriate for all the required clinical and genomic data types.

• Data integration capability to deliver analytics-ready datasets into domain-specific data stores across batch and streaming integration patterns.

• Standards-based access services providing secure, fast, flexible, robust and auditable access to TRE data assets.

• Applications to support the research user journey from an exploration of data sets, through cohort building, analysis and publication - providing tools appropriate to a variety of user requirements (ways of working) and programming competency.

• Applications and workflows can be delivered natively within the platform, however COVID-RE must enable access to container-based applications and, via a set of hardened APIs, to a relevant external service (as long as security is maintained).

Details of the sublicense model via the Genomics England Research Environment are supplied within the processing activities section of this agreement.

Regarding genome data sharing with sublicensees - As an example, if an individual’s whole-exome or whole-genome sequence forms part of a database but all other records and identifiers have been fully deleted so that all that remains is sequence data, this data could easily be ‘individuated’ or singled out. However, it can be argued that it cannot be connected to a natural person without something further which can relate it to them.

In this perspective, the Global Alliance for Genomics and Health (GA4GH) has grouped together to provide unified strategies for addressing the major challenges of this data revolution. Genomics England are key members in this alliance and a recent publication (https://www.cell.com/cell-genomics/fulltext/S2666-979X(21)00036-7) presents the GA4GH suite of secure, interoperable technical standards and policy frameworks

• GA4GH and the PHG foundation both suggest that genetic, and particularly genomic information should not be viewed as inherently or directly identifying without some further link to or impact on an individual

• To that end, our research environment is a leading light in security and standards as per HDR UK (https://zenodo.org/record/5767586#.YcPE9hPP27M) and an author is an employee of Genomics England.

• Furthermore, our Airlock policy is clear and explicit about the level of data that can be extracted and does not permit row level/ individual data extraction

The additional clinical data is key for researchers to be able to understand and infer clinically relevant and actionable findings. The aim is to provide a high quality, diverse clinical dataset, detailing each participant’s journey and to understand pre-existing conditions and also the early behaviours in the disease course. Genomics England currently have an agreement to receive NHS Digital data for the extant 100,000 Genomes Project participants (DARS-NIC-12784) and have seen first-hand the depth and quality of the data and how it has aided researchers.

To that aim, the significant gap in the current data collection for the COVID-19 project can be addressed by the non-standard NHS Digital data feed.

The Secondary Use Services Admitted Patient Care Feed (SUS APC) would provide as close to real-time data for researchers and in the current climate is vital to ensure no delays.

The associated COVID-19 data-sets (including NHS111 and CV19 Testing Data in particular which will be requested under a future version of this agreement) will add to the detail in patient journey course, flagging for instance how participants were monitoring their symptoms and was there an associated poor prognosis.

The group of survivors eligible for recruitment for this study are generally healthy individuals who have suffered critical illness. It is anticipated this cohort will grow to approx. 36,000 participants.

The data would be available for analysis alongside the extant Genomics England data set of 100,000 Genomes Project participants and would be made available to approved researchers worldwide as per existing governance procedures. This 100,000 Genomes Project data set will act as an appropriate matched control group. Data on the 100,000 Genomes Cohort will be provided to NHS Digital for linkage - (as they will act as a control cohort), as well as new additions for the GenOMICC Study.

The below detail pertains to the background of the study and susceptibility to infection sets out why Genomics are investigating. The origin of the GenOMICC study was focused on smaller cohorts of participants. However, in collaboration with the COG-UK group, this is now expanded to whole genome sequence of approx. 36,000 affected individuals as set out above.

GenOMICC Study Background:

Susceptibility to infection is profoundly heritable (Sorensen et al. 1988). Patients who develop life-threatening illness following infection with usually innocuous pathogens, such as influenza (Miller et al. 2010), are genetically different from the rest of the population (Albright et al. 2008). Understanding the genetic mechanisms of susceptibility may yield new therapeutic targets (Baillie 2014) that can be used to make susceptible patients more similar to individuals who are resistant to, or tolerant of, specific pathogens.

The genetic mechanisms of susceptibility to infection are likely to be highly pathogen-specific and may even have opposing roles in different infections (as for CCR5 variants in HIV [Human Immunodeficiency Virus] (Huang et al. 1996) and WNV (Glass et al. 2006) infection). Pathogen-specific interventions (e.g. small molecules to inhibit an enzyme or receptor that is dysfunctional in resistant individuals) would therefore be protective to the host in a similar way to antibiotics, with the advantage that it is conceptually more difficult for any one pathogen to evolve resistance to such a therapy.

A second, more challenging problem arises in patients who become critically ill following infection. The patterns of immune-mediated organ dysfunction, immunoparesis, and death are very similar in severe infections and sterile systemic injuries (such as burns, haemorrhage, pancreatitis and trauma). Ultimately, death is a consequence of the host response to injury (Angus and Poll 2013), through final common pathways of organ failure that are clinically and biochemically evident, and unrelated to the original precipitant.

Broadly, the severity of critical illness follows directly from the severity and duration of the initial insult. In bacterial sepsis, early antibiotics are the mainstay of therapy; in influenza, early antivirals; in haemorrhage, early resuscitation; in trauma, urgent action to prevent secondary injury. There are no therapies with which to modulate the host response to systemic injury.

There is a lack of direct evidence of heritability for outcomes of critical illness, due in part to difficulties in defining and quantifying the heterogeneous multi-organ dysfunction syndrome (MODS), and in part due to the rapid pace of change in critical care medicine, making it impossible to tackle this question in long term outcome studies. However, clinical and biological evidence support the hypothesis that the pathogenesis of MODS is immune in origin (Angus and Poll 2013). Hence, predictions can be made from the extensive knowledge of other immune conditions. Whether or not MODS is considered to be an autoimmune or infectious condition is moot: these conditions share a great deal of similarity in genetic predispositions, cell types and mechanisms of pathogenesis. It is therefore very likely that propensity to survive MODS has a heritable component, and there is some direct evidence in support of this hypothesis (Rautanen et al. 2015). If this is the case, then the identity of the specific variants that contribute to outcome could potentially be utilised to design therapies to promote survival after the onset of MODS.

This study aims to identify genetic predisposition to specific syndromes of critical illness. Specifically, susceptibility to life-threatening infections caused by an identified pathogen, and susceptibility to death following the onset of organ failure due to sepsis or sterile injury. In order to maximise the probability of identifying host genetic loci associated with susceptibility, Genomics England will restrict some analyses to younger individuals in good general health and lacking in known predisposing factors.

The same principle was used to determine an upper age limit for inclusion for some analyses. With advancing age, there is an increase in undiagnosed co-morbidity, frailty, and susceptibility to serious complications of infection or critical injury. There is therefore an increase in the probability of susceptibility to, and mortality from, critical illness that is consequent upon non-genetic factors.

Participation Group:

Patients will be identified and recruited in hospital during acute illness. Potential participants will be identified through hospital workers upon presentation at recruiting sites. The disease processes under study have a high mortality, so it is desirable to recruit patients as early as possible in the disease process.

Participants or an appropriate parent/guardian/consultee will be approached by staff trained in consent procedures that protect the rights of the patient and adhere to the ethical principles within the Declaration of Helsinki. Staff will explain the details of the study to the participant or parent/guardian/consultee and allow them time to discuss and ask questions. The staff will review the informed consent form with the person giving consent (or assent) and endeavour to ensure understanding of the contents, including study procedures, risks, benefits, and the right to withdraw. Participants who agree to participate (or their parent/guardian or consultee who declares their wishes to do so) will be asked to sign and date an informed consent form.

In view of the importance of early sampling, participants or their parent/guardian/consultee will be permitted to consent and begin to participate in the study immediately if they wish to do so. Those who prefer more time to consider participation will be approached again after an agreed time, normally one day, to discuss further.

Patients who meet the inclusion/exclusion criteria and who have given informed consent to participate directly, or have been consented by a parent/guardian or whose wishes have been declared by a consultee, will be enrolled to the study.

Samples and data will be collected according to available resources and the weight of the patient will be measured for children under 12 in order to prevent excessive volume sampling. Samples required for medical management will at all times have priority over samples taken for research tests. Aliquots or samples for research purposes should never compromise the quality or quantity of samples required for medical management. Wherever practical, taking research samples should be timed to coincide with clinical sampling. The research team will be responsible for sharing the sampling protocol with health care workers supporting patient management in order to minimise disruption to routine care and avoid unnecessary procedures.

Consent will be sought from patients who survive critical illness and regain capacity to give consent. At each of the follow-up sessions, the investigator gathering data will determine whether the patient has regained capacity. In the event that a patient continues to be incapacitated beyond the follow-up period, the local investigator will plan a subsequent capacity check at a specific date, after an interval to be determined by the nature of the incapacity. The planned dates of capacity checks on incapacitated survivors will be stored locally in the site file, together with a record of the outcome of each check.

Patients who decline to participate at this stage will be removed from the study. Where the patient cannot be recontacted despite best endeavours, they will remain in the study.

Withdrawal:

Participants are freely able to decline participation in this study or to withdraw from participation at any point without suffering any implied or explicit disadvantage. All patients will be treated according to standard practice regardless of whether they participate.

The following options of withdrawal will be made available to participants:

1. Partial withdrawal. Data WILL continue to be updated and used for research, but no further contact will be made with the participant

2. Full withdrawal.

• no further contact will be made with the participant;

• data will not be updated from health records;

• data will not be removed from research that is underway or has already been done, and an audit record will be maintained to confirm participation.

Consent version and life course follow-up

There are a series of consent versions as documented below:

• V1.08 (March 2020) - there are circa 1500 participants on this consent , allows for COVID research but not for longitudinal follow-up. Genomics are exploring reconsenting and CAG as options for this cohort. Currently, these individuals will NOT be submitted to NHS Digital

• V2.1 (April 2020) - Included retention of NHS number and linkage to longitudinal follow -up, NHS Digital are named on the PIS. These individuals will be submitted to NHS Digital for data linkage

• V2.4 (July 2020) - In addition to already stated in v2.1, this covers community recruitment of participants and movement of identifiers. Sharing data with NHS Digital is again stated. These individuals will be submitted to NHS Digital for data linkage

PIS and Consent Version 2.1 and 2.4 are identical in their reference to accessing data from secondary data suppliers and include retention and collection of identifiable information and both name NHS Digital as a source of linkage. All individuals consented are collected with information including version of consent recruited under, thus genomics England can distinguish individuals based on consent. The most up to date protocol is listed on the website (https://genomicc.org/protocol/)

Datasets requested from NHS Digital:

The current application to access to the data sets requested are in line with COVID-19 related purpose, in terms of the restrictions set out in Reg 3(1) COPI. However, based on the now REC approved protocol, we are looking to move this application to Consent basis.

Primary Care dataset: Genomics England anticipate GPES (General Practice Extraction Service) Data for Pandemic Planning and Research (GDPPR) extracts to assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings. We understand this dataset remains under COVID regulations and will remain only for COVID research going forward.

Hospital Episode Statistics (HES): Outpatients (OP), Admitted Patient Care (APC), Critical Care (CC) and Accident & Emergency (AE)/ Emergency Care Data Set (ECDS). These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

Diagnostic Imaging Dataset (DIDS). This provides invaluable, detailed information to build on participants' phenotypes, e.g. tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

Secondary Uses Service datasets. The minimal latency in availability of these datasets is highly desirable for the research objectives set out in this project.

Mental Health Data sets: The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

Cancer Registration Data sets: To see the incidence of cancer within the cohort

Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

COVID datasets: These datasets, including vaccination, SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus. These will remain only for COVID based research only.

Assessment of the datasets has been undertaken and NHS Digital are satisfied that they are necessary for the COVID-19 work being undertaken. Genomics have confirmed that all research which is approved from the GenoMICC study using the data for the COVID-19 specific purposes will be published here https://www.genomicsengland.co.uk/about-gecip/research-2/

Genomics England Industry access:

Genomics England works with industry through its Discovery Forum. The Forum provides a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Industry partners comprise pharmaceutical, biotech and diagnostic companies, and those specialising in laboratory and data analysis. These companies have joined the Forum to work in a pre-competitive environment with access to a selection of genomic and associated clinical data. Ultimately, the Discovery Forum aims to help turn research findings into treatments, diagnostics and benefits for patients as soon as possible.

As the Discovery Forum is a collaborative venture, no fees are levied on participating organisations to access the COVID data, however they are charged based on storage and compute, such as running their own bioinformatics pipeline. All members of the Forum are obliged to publish all findings and research at the point at which intellectual property for any product is protected.

The Forum was created in July 2017 and allows industrial partners to report back to Genomics England on what aspects of the data are proving to be most useful to their research studies, what data is missing and how the data should be collected and developed further so it is captures what industry needs, in a format that is compatible with their research and data systems. These partners act as a 'critical friend' and have made many helpful suggestions to increase the likelihood of successful research in the future for all those using Genomics England's landmark data set.

The lawful basis for processing Participant Data under the General Data Protection Regulation (GDPR) used by Genomics England is legitimate interests as set out under Article 6(1)(f) of the GDPR. It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

Additionally, as Genomics England will be processing health data - a special category of personal data, they will also be processing data under Article 9 (2)(j) as processing is necessary for archiving purposes in the public interest. Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

Access to the data will enable the research to discover new rare and common variants alongside new multi-omic biomarkers that underpin host response to infection, allow investigation of the impact of viral genomic features on outcomes and allow creation of a polygenic risk score, which may detect risk of severe response to similar viruses. The prospective component could allow nested clinical trials or case-control resources to add value to this study by detecting variants, which stratify response or predict outcomes. Although the 100,000 Genomes Project and the Genomic Medicine Service may include participants biased to specific disease ascertainment, the scale of these resources and the presence of parents helps compensate for this problem.

Specifically the short term (6 months) and medium term benefits and outcomes from this programme of research anticipated are;

• Variants enable Polygenic Risk Score to predict greatest risk and avoid ITU

• Pre-morbid clinical conditions or biomarkers of risk and rapid NHS uptake to avoid ITU

• Identify novel therapies or precision interventions for rapid national trials

• Longitudinal life course sequel of COVID-19 for pandemic planning

• Patient benefit:

o Providing improved clinical understanding of disease progression in COVID-19

o Correlation to disease progression and pre-morbid status

o Identification of susceptibility genes

o Develop a biomarker test(s) to predict an individual’s response to SARS-CoV-2 exposure, considering both COVID-19 severity and vulnerability to infection.

o Identify targets that can be used in to inform development of new treatments

• New scientific insights and discovery:

o with the consent of patients, creating a database of 35,000 whole genome sequences linked to continually updated long term patient health and personal information for analysis by researchers.

o Correlation of host and viral genomic data

o Potential to provide improved testing for future pandemics

o Aide researchers to identify novel targets for vaccines and therapy

o Identification of highly penetrant rare variants in genes and pathways relating to viral susceptibility or immunodeficiency.

o Genome wide association studies (GWAS) using common variants to identify genes and pathways associated with viral response. These analyses will be aligned with other COVID-19 research consortia.

o Rare variant burden analysis to identify genes and pathways enriched in rare variants associated with viral response

• Accelerating the uptake of genomic medicine in the NHS: working with NHSE and other partners to deliver a scale-able WGS and informatics platform to enable these services to be made widely available for NHS patients. WGS could potentially provide the most accurate diagnostic test for COVID 19.

• Stimulating and enhancing UK industry and investment: by providing access to this unique data resource by industry for the purpose of developing new knowledge, methods of analysis, medicines, diagnostics and devices.

• Increasing public knowledge and support for genomic medicine: delivering an ethical and transparent programme which has public trust and confidence and working with a range of partners to increase knowledge of genomics.

Although the 100,000 genomes project has completed recruitment, Genomics England is committed to continue gathering life-long clinical data from the participants and making these available in the Research Environment.

Genomics England will be responsible for the onward workflow, in partnership with Illumina for the delivery of 30X whole genome sequences, subject to passing appropriate sequence QC, into the Genomics England data centre. Alignment and variant calling will be performed alongside the potential application of bespoke immunodeficiency panels as part of the Genomics England bioinformatics pipeline analysis.

Genomic data will be released into the Genomics England Research Environment where it will be linked with associated clinical data.

The GenOMICC study is backed by £28 million from Genomics England, UK Research and Innovation, the Department of Health and Social Care and the National Institute for Health Research. Illumina will sequence all 35,000 genomes and share some of the cost via an in-kind contribution.

A press release on 13/05/20 included a comment from Health and Social Care Secretary Matt Hancock: “As each day passes, we are learning more about this virus, and understanding how genetic makeup may influence how people react to it is a critical piece of the jigsaw.

“This is a ground-breaking and far-reaching study which will harness the UK’s world-leading genomics science to improve treatments and ultimately save lives across the world.” To date, nearly 3000 patients have been recruited into the project.

The Research environment also contained clinical data on 89,157 participants (this is because cancer participants have two genomes submitted). The clinical data for 17,246 cancer participants includes clinical data from NHS Digital (HES OP/APC/ CC and AE) but also cancer specific data from Public Health England Cancer Registry (NCRAS). The combination of clinical data for all 100,000 participants totals about 5m records.

As the GenOMICC study prospectively recruits participants, the aim will be to use the existing 100,000 participants and age and match-ranked controls for those entered into the study. As Genomics England prospectively enrolls more participants into the study, Genomics England plans further releases of genomic and clinical data, including clinical data received from NHS Digital and viral and host genomic data, into the Research Environment monthly in order to continue support for, and to further develop, this ground-breaking resource.

Outputs published to date are;

Publications:

• Pairo-Castineira E., Clohisey S., Klaric L., Bretherick A.D., Rawlik K., Pasko D., Walker S., Parkinson N., Fourman M.H., Russell C.D., Furniss J., Richmond A., Gountouna E., Wrobel N., Harrison D., Wang B., Wu Y., Meynert A., Griffiths F., Oosthuyzen W., Kousathanas A., Moutsianas L., Yang Z., Zhai R., Zheng C., Grimes G., Beale R., Millar J., Shih B., Keating S., Zechner M., Haley C., Porteous D.J., Hayward C., Yang J., Knight J., Summers C., Shankar-Hari M., Klenerman P., Turtle L., Ho A., Moore S.C., Hinds C., Horby P., Nichol A., Maslove D., Ling L., McAuley D., Montgomery H., Walsh T., Pereira A.C., Renieri A., GenOMICC I., Investigators, COVID- Human Genetics I., Investigators, BRACOVID I., Gen-COVID I., Shen X., Ponting C.P., Fawkes A., Tenesa A., Caulfield M., Scott R., Rowan K., Murphy L., Openshaw P., Semple M.G., Law A., Vitart V., Wilson J.F., Baillie J.K. Genetic mechanisms of critical illness in COVID-19. Nature. 2020;591(7848):92–98

• Kosmicki JA, Horowitz JE, Banerjee N, Lanche R, Marcketta A, Maxwell E, Bai X, Sun D, Backman JD, Sharma D, Kang HM, O'Dushlaine C, Yadav A, Mansfield AJ, Li AH, Watanabe K, Gurski L, McCarthy SE, Locke AE, Khalid S, O'Keeffe S, Mbatchou J, Chazara O, Huang Y, Kvikstad E, O'Neill A, Nioi P, Parker MM, Petrovski S, Runz H, Szustakowski JD, Wang Q, Wong E, Cordova-Palomera A, Smith EN, Szalma S, Zheng X, Esmaeeli S, Davis JW, Lai YP, Chen X, Justice AE, Leader JB, Mirshahi T, Carey DJ, Verma A, Sirugo G, Ritchie MD, Rader DJ, Povysil G, Goldstein DB, Kiryluk K, Pairo-Castineira E, Rawlik K, Pasko D, Walker S, Meynert A, Kousathanas A, Moutsianas L, Tenesa A, Caulfield M, Scott R, Wilson JF, Baillie JK, Butler-Laporte G, Nakanishi T, Lathrop M, Richards JB, Jones M, Balasubramanian S, Salerno W, Shuldiner AR, Marchini J, Overton JD, Habegger L, Cantor MN, Reid JG, Baras A, Abecasis GR, Ferreira MA. A catalog of associations between rare coding variants and COVID-19 outcomes. medRxiv [Preprint]. 2021 Feb 27:2020.10.28.20221804. doi: 10.1101/2020.10.28.20221804. PMID: 33655273; PMCID: PMC7924298.

• RECOVERY Collaborative Group. Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial. Lancet. 2021 May 1;397(10285):1637-1645. doi: 10.1016/S0140-6736(21)00676-0. PMID: 33933206; PMCID: PMC8084355.

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS Digital. Understanding this significant value is why Genomics England are so keen to add NHS Digital data to its clinical data source for the GenOMICC study.

This proposal has already enabled Genomics England to discover new rare and common variants alongside new multi-omic biomarkers that underpin host response to infection, allowing investigation of the impact of viral genomic features on outcomes. The ongoing prospective component could allow nested clinical trials or case-control resources to add value to this study by detecting variants, which stratify response or predict outcomes. Benefits thus far stated below.

Summary of publications and value of study updated December 2021:

Genome wide studies (GWAS) of first 2244 GenOMICC participants admitted with severe COVID

Identified the following genes of interest:

• chromosome 12q24.13 in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3)

• chromosome 19p13.2 near the gene that encodes tyrosine kinase 2 (TYK2);

• chromosome 19p13.3 within the gene that encodes dipeptidyl peptidase 9 (DPP9);

• chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2.

• These targets can utilise and repurpose currently used medications for treatment and management of severe covid.

• evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19.

• Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19.

• Both mechanisms may be amenable to targeted treatment with existing drugs.

In addition, two therapeutic drug trials have also commenced.

By March 2022 some 16 new genetic variants associated with severe Covid-19, including some related to blood clotting, immune response and intensity of inflammation, have been identified. These findings will act as a roadmap for future efforts, opening new fields of research focused on potential new therapies and diagnostics with pinpoint accuracy. Determining the whole genome sequence for all participants in the study allowed the team to create a precise map and identify genetic variation linked to severity of Covid-19. The team found key differences in 16 genes in the ICU patients when compared with the DNA of the other groups. They also confirmed the involvement of seven other genetic variations already associated with severe Covid-19 discovered in earlier studies from the same team. The findings included how a single gene variant that disrupts a key messenger molecule in immune system signalling – called interferon alpha-10 – was enough to increase a patient’s risk of severe disease. This highlights the gene’s key role in the immune system and suggests that treating patients with interferon – proteins released by immune cells to defend against viruses – may help manage disease in the early stages. The study also found that variations in genes that control the levels of a central component of blood clotting – known as Factor 8 – were associated with critical illness in Covid-19. This may explain some of the clotting abnormalities that are seen in severe cases of Covid-19. Factor 8 is the gene underlying the most common type of haemophilia.

SEPTEMBER 2021 - v3 is a extension at no cost to keep customer in agreement ONLY. No data is to flow under this Extension.

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This agreement is seeking approval to request data to support The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole Genome Sequencing (WGS) of patients severely affected by COVID-19. The work programme has sign off and prioritisation from the Chief Medical Officer for England (CMO)

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS Digital and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people) and UK Biobank data sets (500,000 people) with WGS where more cases may be identified, including those with milder disease and unaffected people.

This mention of linkage of the NHS Digital data to UK Biobank data is purely aspirational at present. This has not been approved under previous iterations of the agreement, and is not covered under v1.2 of this agreement. Genomics England can confirm that if such linkage were to occur - then appropriate documentation (including transparency, patient, consent and ethics materials) would be provided to NHS Digital and a subsequent amended application put in place.

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England Research Environment to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and it’s outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel.

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By undertaking a prospective study design that leverages existing recruitment infrastructure in critical care, together with Genomics England, NHS England, Devolved Nations and Public Health England (PHE) infrastructure this research will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

Genomics England Background: (For Context)

Genomics England was established by the Department of Health to deliver the 100,000 Genomes Project. This followed the announcement in December 2012 by the Prime Minister of a programme of whole genome sequencing (WGS) as part of the UK Government’s Life Sciences Strategy. The principal objective of the 100,000 Genomes Project was to sequence 100,000 genomes from participants with cancer and rare disorders, and to link the sequence data to a standardised, extensible account of diagnosis, treatment, and outcomes gathered at recruitment, but primarily through the ongoing collection of medical records.

Data will be released into the Genomics England Research Environment where it will be linked with associated clinical data as well as additional data sources, which will include NHS Digital data requested through this agreement, COVID-19 testing feeds and viral genomics from Public Health England and data feeds from the Intensive Care National Audit Registry (ICNARC).

The Department of Health and Social Care have granted approval for Genomics England to procure a new, rapidly deployable Research Environment for the COVID-19 programme from existing core funding, which will provide a secure and collaborative workspace that enables researchers to perform COVID-19 genomic data analysis. The new Research Environment (COVID-RE) will provide an intuitive, integrated and collaborative user experience that enables effective COVID-19 research outcomes across a wide range of academic and Biotech/Pharma researchers with varying levels of technical competency. This offers a major upgrade to our current environment and will comprise user-centric, contemporary bioinformatic workflows, support opensource tooling, and enable shared workspaces between Genomics England and Partners. COVID-RE must serve the immediate COVID-19 research effort and may also advance the transformation of Genomics England’s platform infrastructure, which is a key enabler to the research community.

There are two key value streams provided by the COVID-RE. Firstly ‘raw data to analytics ready data’ stream which must permit the collection of data from multiple locations from unstructured, through semi and fully structured forms and transforms them the appropriate data model, data store based on their ongoing use and availability. Secondly the ‘discovery to insight’ stream that supports researchers by providing the capability and the framework to support their User Journey from understanding the data available to them through to providing the necessary analytics and publishing tools.

The newly established COVID-RE will provide the following:

• Seamless interface with cloud storage and compute capabilities.

• A unified data platform containing datastores appropriate for all the required clinical and genomic data types.

• Data integration capability to deliver analytics-ready datasets into domain-specific data stores across batch and streaming integration patterns.

• Standards-based access services providing secure, fast, flexible, robust and auditable access to TRE data assets.

• Applications to support the research user journey from an exploration of data sets, through cohort building, analysis and publication - providing tools appropriate to a variety of user requirements (ways of working) and programming competency.

• Applications and workflows can be delivered natively within the platform, however COVID-RE must enable access to container-based applications and, via a set of hardened APIs, to a relevant external service (as long as security is maintained).

Details of the sublicence model via the Genomics England Research Environment are supplied within the processing activities section of this agreement.

The additional clinical data is key for researchers to be able to understand and infer clinically relevant and actionable findings. The aim is to provide a high quality, diverse clinical dataset, detailing each participant’s journey and to understand pre-existing conditions and also the early behaviours in the disease course. Genomics England currently have an agreement to receive NHS Digital data for the extant 100,000 Genomes Project participants (DARS-NIC-12784) and have seen first-hand the depth and quality of the data and how it has aided researchers.

To that aim, the significant gap in the current data collection for the COVID-19 project can be addressed by the non-standard NHS Digital data feed.

The Secondary Use Services Admitted Patient Care Feed (SUS APC) would provide as close to real-time data for researchers and in the current climate is vital to ensure no delays.

The associated COVID-19 data-sets (including NHS111 and CV19 Testing Data in particular which will be requested under a future version of this agreement) will add to the detail in patient journey course, flagging for instance how participants were monitoring their symptoms and was there an associated poor prognosis.

The group of survivors eligible for recruitment for this study are generally healthy individuals who have suffered critical illness. It is anticipated this cohort will grow to approx 36,000 participants.

The data would be available for analysis alongside the extant Genomics England data set of 100,000 Genomes Project participants and would be made available to approved researchers worldwide as per existing governance procedures. This 100,000 Genomes Project data set will act as an appropriate matched control group. Data on the 100,000 Genomes Cohort will be provided to NHS Digital for linkage - (as they will act as a control cohort), as well as new additions for the GenOMICC Study.

The below detail pertains to the background of the study and susceptibility to infection sets out why Genomics are investigating. The origin of the GenOMICC study was focused on smaller cohorts of participants. However, in collaboration with the COG-UK group, this is now expanded to whole genome sequence of approx. 36,000 affected individuals as set out above.

GenOMICC Study Background:

Susceptibility to infection is profoundly heritable (Sorensen et al. 1988). Patients who develop life-threatening illness following infection with usually innocuous pathogens, such as influenza (Miller et al. 2010), are genetically different from the rest of the population (Albright et al. 2008). Understanding the genetic mechanisms of susceptibility may yield new therapeutic targets (Baillie 2014) that can be used to make susceptible patients more similar to individuals who are resistant to, or tolerant of, specific pathogens.

The genetic mechanisms of susceptibility to infection are likely to be highly pathogen-specific and may even have opposing roles in different infections (as for CCR5 variants in HIV [Human Immunodeficiency Virus] (Huang et al. 1996) and WNV (Glass et al. 2006) infection). Pathogen-specific interventions (e.g. small molecules to inhibit an enzyme or receptor that is dysfunctional in resistant individuals) would therefore be protective to the host in a similar way to antibiotics, with the advantage that it is conceptually more difficult for any one pathogen to evolve resistance to such a therapy.

A second, more challenging problem arises in patients who become critically ill following infection. The patterns of immune-mediated organ dysfunction, immunoparesis, and death are very similar in severe infections and sterile systemic injuries (such as burns, haemorrhage, pancreatitis and trauma). Ultimately, death is a consequence of the host response to injury (Angus and Poll 2013), through final common pathways of organ failure that are clinically and biochemically evident, and unrelated to the original precipitant.

Broadly, the severity of critical illness follows directly from the severity and duration of the initial insult. In bacterial sepsis, early antibiotics are the mainstay of therapy; in influenza, early antivirals; in haemorrhage, early resuscitation; in trauma, urgent action to prevent secondary injury. There are no therapies with which to modulate the host response to systemic injury.

There is a lack of direct evidence of heritability for outcomes of critical illness, due in part to difficulties in defining and quantifying the heterogeneous multi-organ dysfunction syndrome (MODS), and in part due to the rapid pace of change in critical care medicine, making it impossible to tackle this question in long term outcome studies. However, clinical and biological evidence support the hypothesis that the pathogenesis of MODS is immune in origin (Angus and Poll 2013). Hence, predictions can be made from the extensive knowledge of other immune conditions. Whether or not MODS is considered to be an autoimmune or infectious condition is moot: these conditions share a great deal of similarity in genetic predispositions, cell types and mechanisms of pathogenesis. It is therefore very likely that propensity to survive MODS has a heritable component, and there is some direct evidence in support of this hypothesis (Rautanen et al. 2015). If this is the case, then the identity of the specific variants that contribute to outcome could potentially be utilised to design therapies to promote survival after the onset of MODS.

This study aims to identify genetic predisposition to specific syndromes of critical illness. Specifically, susceptibility to life-threatening infections caused by an identified pathogen, and susceptibility to death following the onset of organ failure due to sepsis or sterile injury. In order to maximise the probability of identifying host genetic loci associated with susceptibility, Genomics England will restrict some analyses to younger individuals in good general health and lacking in known predisposing factors.

The same principle was used to determine an upper age limit for inclusion for some analyses. With advancing age, there is an increase in undiagnosed co-morbidity, frailty, and susceptibility to serious complications of infection or critical injury. There is therefore an increase in the probability of susceptibility to, and mortality from, critical illness that is consequent upon non-genetic factors.

Participation Group:

Patients will be identified and recruited in hospital during acute illness. Potential participants will be identified through hospital workers upon presentation at recruiting sites. The disease processes under study have a high mortality, so it is desirable to recruit patients as early as possible in the disease process.

Participants or an appropriate parent/guardian/consultee will be approached by staff trained in consent procedures that protect the rights of the patient and adhere to the ethical principles within the Declaration of Helsinki. Staff will explain the details of the study to the participant or parent/guardian/consultee and allow them time to discuss and ask questions. The staff will review the informed consent form with the person giving consent (or assent) and endeavour to ensure understanding of the contents, including study procedures, risks, benefits, and the right to withdraw. Participants who agree to participate (or their parent/guardian or consultee who declares their wishes to do so) will be asked to sign and date an informed consent form.

In view of the importance of early sampling, participants or their parent/guardian/consultee will be permitted to consent and begin to participate in the study immediately if they wish to do so. Those who prefer more time to consider participation will be approached again after an agreed time, normally one day, to discuss further.

Patients who meet the inclusion/exclusion criteria and who have given informed consent to participate directly, or have been consented by a parent/guardian or whose wishes have been declared by a consultee, will be enrolled to the study.

Samples and data will be collected according to available resources and the weight of the patient will be measured for children under 12 in order to prevent excessive volume sampling. Samples required for medical management will at all times have priority over samples taken for research tests. Aliquots or samples for research purposes should never compromise the quality or quantity of samples required for medical management. Wherever practical, taking research samples should be timed to coincide with clinical sampling. The research team will be responsible for sharing the sampling protocol with health care workers supporting patient management in order to minimise disruption to routine care and avoid unnecessary procedures.

Consent will be sought from patients who survive critical illness and regain capacity to give consent. At each of the follow-up sessions, the investigator gathering data will determine whether the patient has regained capacity. In the event that a patient continues to be incapacitated beyond the follow-up period, the local investigator will plan a subsequent capacity check at a specific date, after an interval to be determined by the nature of the incapacity. The planned dates of capacity checks on incapacitated survivors will be stored locally in the site file, together with a record of the outcome of each check.

Patients who decline to participate at this stage will be removed from the study. Where the patient cannot be recontacted despite best endeavours, they will remain in the study.

Withdrawal:

Participants are freely able to decline participation in this study or to withdraw from participation at any point without suffering any implied or explicit disadvantage. All patients will be treated according to standard practice regardless of whether they participate.

The following options of withdrawal will be made available to participants:

1. Partial withdrawal. Data WILL continue to be updated and used for research, but no further contact will be made with the participant

2. Full withdrawal.

• no further contact will be made with the participant;

• data will not be updated from health records;

• data will not be removed from research that is underway or has already been done, and an audit record will be maintained to confirm participation.

Consent version and lifecourse follow-up

The first COVID positive patient was recruited to the GenOMICC study in March 2020. All patients (c.1500) currently recruited to the GenOMICC study are on consent and Protocol version 1.08 (which allows for COVID research but not longitudinal life course follow up). This Protocol v2.1 (submitted as part of this DARS request) was Research Ethics Committe (REC) approved on 23rd March 2020, IRAS [Integrated Research Application System] IDs are: 269326 & 189676 (https://www.hra.nhs.uk/covid-19-research/approved-covid-19-research/269326/). Genomics England will attempt to reconsent all patients recruited under version 1.08 onto the newly amended materials (version 2.5 of the patient information sheet – submitted as part of this DARS application) which allows for longitudinal lifecourse follow-up. For any patients on the v1.08 Protocol for which Genomics England are not able to seek consent, Genomics England will not be requesting their data for linkage. For patients prospectively recruited onto the v2.1 Protocol and consent materials, Genomics England will be requesting their data for linkage and follow-up .

Datasets requested from NHS Digital:

Consideration has been be given to assess and ensure that access to the data sets requested are inline with COVID-19 related purpose, in terms of the restrictions set out in Reg 3(1) COPI, below are details of what each of the data sets will at a high level provide insight to.

Primary Care dataset: Genomics England anticipate GPES (General Practice Extraction Service) Data for Pandemic Planning and Research (GDPPR) extracts to assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings.

Hospital Episode Statistics (HES): Outpatients (OP), Admitted Patient Care (APC), Critical Care (CC) and Accident & Emergency (AE)/ Emergency Care Data Set (ECDS). These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

Diagnostic Imaging Dataset (DIDS). This provides invaluable, detailed information to build on participants' phenotypes, e.g. tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

Secondary Uses Service datasets. The minimal latency in availability of these datasets is highly desirable for the research objectives set out in this project.

Mental Health Data sets: The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

Cancer Registration Data sets: To see the incidence of cancer within the cohort

Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

COVID datasets: These datasets, including SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus.

Assessment of the datasets has been undertaken and NHS Digital are satisfied that they are necessary for the COVID-19 work being undertaken. Genomics have confirmed that all research which is approved from the GenoMICC study using the data for the COVID-19 specific purposes will be published here https://www.genomicsengland.co.uk/about-gecip/research-2/

Genomics England Industry access:

Genomics England works with industry through its Discovery Forum. The Forum provides a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Industry partners comprise pharmaceutical, biotech and diagnostic companies, and those specialising in laboratory and data analysis. These companies have joined the Forum to work in a pre-competitive environment with access to a selection of genomic and associated clinical data. Ultimately, the Discovery Forum aims to help turn research findings into treatments, diagnostics and benefits for patients as soon as possible.

As the Discovery Forum is a collaborative venture, no fees are levied on participating organisations to access the COVID data, however they are charged based on storage and compute, such as running their own bioinformatics pipeline. All members of the Forum are obliged to publish all findings and research at the point at which intellectual property for any product is protected.

The Forum was created in July 2017 and allows industrial partners to report back to Genomics England on what aspects of the data are proving to be most useful to their research studies, what data is missing and how the data should be collected and developed further so it is captures what industry needs, in a format that is compatible with their research and data systems. These partners act as a 'critical friend' and have made many helpful suggestions to increase the likelihood of successful research in the future for all those using Genomics England's landmark data set.

The lawful basis for the release and use of the confidential data being shared under this version of the agreement is Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations entitled to process this under COPI for COVID-19 purposes. The application of this has been based on the information provided in the Whole genome sequencing of patients severely affected by COVID-19 funding proposal from The GenOMICC - COVID Genomics UK (CoG-UK) partnership which was supported by the CMO of England and the CFO of the DHSC.

The lawful basis for processing Participant Data under the General Data Protection Regulation (GDPR) used by Genomics England is legitimate interests as set out under Article 6(1)(f) of the GDPR. It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

Additionally, as Genomics England will be processing health data - a special category of personal data, they will also be processing data under Article 9 (2)(j) as processing is necessary for archiving purposes in the public interest. Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

SEPTEMBER 2021 - v3 is a extension at no cost to keep customer in agreement ONLY. No data is to flow under this Extension.

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Genomics England completed sequencing 100,000 genomes at the end of 2018 (https://www.newscientist.com/article/2187499-uk-dna-project-hits-major-milestone-with-100000- genomes-sequenced/). During 2018, the Genomics England Research Environment was established to allow research access to de-identified genomic and clinical data received from NHS Digital. Thirty disease and cross-cutting GeCIP research domains were requested and approved, with now over 3000 GeCIP members given access to the Research Environment. Genomics England had also created the industry Discovery Forum to provide a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Although the 100,000 genomes project has completed recruitment, Genomics England is committed to continue gathering life-long clinical data from the participants and making these available in the Research Environment.

Genomics England will be responsible for the onward workflow, in partnership with Illumina for the delivery of 30X whole genome sequences, subject to passing appropriate sequence QC, into the Genomics England data centre. Alignment and variant calling will be performed alongside the potential application of bespoke immunodeficiency panels as part of the Genomics England bioinformatics pipeline analysis.

Genomic data will be released into the Genomics England Research Environment where it will be linked with associated clinical data.

The GenOMICC study is backed by £28 million from Genomics England, UK Research and Innovation, the Department of Health and Social Care and the National Institute for Health Research. Illumina will sequence all 35,000 genomes and share some of the cost via an in-kind contribution.

A press release on 13/05/20 included a comment from Health and Social Care Secretary Matt Hancock: “As each day passes, we are learning more about this virus, and understanding how genetic makeup may influence how people react to it is a critical piece of the jigsaw.

“This is a ground-breaking and far-reaching study which will harness the UK’s world-leading genomics science to improve treatments and ultimately save lives across the world.” To date, nearly 3000 patients have been recruited into the project.

As of March 2020, the Genomics England Research Environment contained 107,694 genomes, of which, 33,461 were cancer and 74,233 were rare diseases.

The Research environment also contained clinical data on 89,157 participants (this is because cancer participants have two genomes submitted). The clinical data for 17,246 cancer participants includes clinical data from NHS Digital (HES OP/APC/ CC and AE) but also cancer specific data from Public Health England Cancer Registry (NCRAS). The combination of clinical data for all 100,000 participants totals about 5m records.

As the GenOMICC study prospectively recruits participants, the aim will be to use the existing 100,000 participants and age and match-ranked controls for those entered into the study. As Genomics England prospectively enrolls more participants into the study, Genomics England plans further releases of genomic and clinical data, including clinical data received from NHS Digital and viral and host genomic data, into the Research Environment monthly in order to continue support for, and to further develop, this ground-breaking resource.

Specific outputs over the period of this agreement are therefore to release updated genomic and clinical data for the 100,000 genomes participants and GenOMICC participants into the Research Environment on the dates shown above.

SEPTEMBER 2021 - v3 is a extension at no cost to keep customer in agreement ONLY. No data is to flow under this Extension.

_____________________________________________________________________________________

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS Digital. Understanding this significant value is why Genomics England are so keen to add NHS Digital data to its clinical data source for the GenOMICC study.

The GenOMICC study is very much in its infancy and whole genome sequencing has only begun in the last month. It is thus too early to demonstrate any significant outcomes. These outcomes will only gain power and relevance with more prospectively recruited patients and a breadth and depth of clinical data. By providing this to researchers, Genomics England can provide them the necessary tools to explore the genomic data.

This agreement is seeking approval to request data to support The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole genome sequencing (WGS) of patients severely affected by COVID-19. The work programme has sign off and prioritisation from the Chief Medical Officer for England (CMO)

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS Digital and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people) and UK Biobank data sets (500,000 people) with WGS where more cases may be identified, including those with milder disease and unaffected people.

This mention of linkage of the NHS Digital data to UK Biobank data is purely aspirational at present. This has not been approved under previous iterations of the agreement, and is not covered under v1.2 of this agreement. Genomics England can confirm that if such linkage were to occur - then appropriate documentation (including transparency, patient, consent and ethics materials) would be provided to NHS Digital and a subsequent amended application put in place.

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England Trusted Research Environment to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and it’s outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel.

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By undertaking a prospective study design that leverages existing recruitment infrastructure in critical care, together with Genomics England, NHS England, Devolved Nations and Public Health England (PHE) infrastructure this research will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

Genomics England Background: (For Context)

Genomics England was established by the Department of Health to deliver the 100,000 Genomes Project. This followed the announcement in December 2012 by the Prime Minister of a programme of whole genome sequencing (WGS) as part of the UK Government’s Life Sciences Strategy. The principal objective of the 100,000 Genomes Project was to sequence 100,000 genomes from participants with cancer and rare disorders, and to link the sequence data to a standardised, extensible account of diagnosis, treatment, and outcomes gathered at recruitment, but primarily through the ongoing collection of medical records.

Data will be released into the Genomics England Trusted Research Environment where it will be linked with associated clinical data as well as additional data sources, which will include NHS Digital data requested through this agreement, COVID-19 testing feeds and viral genomics from Public Health England and data feeds from the Intensive Care National Audit Registry (ICNARC).

The Department of Health and Social Care have granted approval for Genomics England to procure a new, rapidly deployable Research Environment for the COVID-19 programme from existing core funding, which will provide a secure and collaborative workspace that enables researchers to perform COVID-19 genomic data analysis. The new Research Environment (COVID-RE) will provide an intuitive, integrated and collaborative user experience that enables effective COVID-19 research outcomes across a wide range of academic and Biotech/Pharma researchers with varying levels of technical competency. This offers a major upgrade to our current environment and will comprise user-centric, contemporary bioinformatic workflows, support opensource tooling, and enable shared workspaces between Genomics England and Partners. COVID-RE must serve the immediate COVID-19 research effort and may also advance the transformation of Genomics England’s platform infrastructure, which is a key enabler to the research community.

There are two key value streams provided by the COVID-RE. Firstly ‘raw data to analytics ready data’ stream which must permit the collection of data from multiple locations from unstructured, through semi and fully structured forms and transforms them the appropriate data model, data store based on their ongoing use and availability. Secondly the ‘discovery to insight’ stream that supports researchers by providing the capability and the framework to support their User Journey from understanding the data available to them through to providing the necessary analytics and publishing tools.

The newly established COVID-RE will provide the following:

• Seamless interface with cloud storage and compute capabilities.

• A unified data platform containing datastores appropriate for all the required clinical and genomic data types.

• Data integration capability to deliver analytics-ready datasets into domain-specific data stores across batch and streaming integration patterns.

• Standards-based access services providing secure, fast, flexible, robust and auditable access to TRE data assets.

• Applications to support the research user journey from an exploration of data sets, through cohort building, analysis and publication - providing tools appropriate to a variety of user requirements (ways of working) and programming competency.

• Applications and workflows can be delivered natively within the platform, however COVID-RE must enable access to container-based applications and, via a set of hardened APIs, to a relevant external service (as long as security is maintained).

Details of the sublicence model via the Genomics England Trusted Research Environment are supplied within the processing activities section of this agreement.

The additional clinical data is key for researchers to be able to understand and infer clinically relevant and actionable findings. The aim is to provide a high quality, diverse clinical dataset, detailing each participant’s journey and to understand pre-existing conditions and also the early behaviours in the disease course. Genomics England currently have an agreement to receive NHS Digital data for the extant 100,000 Genomes Project participants (DARS-NIC-12784) and have seen first-hand the depth and quality of the data and how it has aided researchers.

To that aim, the significant gap in the current data collection for the COVID-19 project can be addressed by the non-standard NHS Digital data feed.

The Secondary Use Services Admitted Patient Care Feed (SUS APC) would provide as close to real-time data for researchers and in the current climate is vital to ensure no delays.

The associated COVID-19 data-sets (including NHS111 and CV19 Testing Data in particular which will be requested under a future version of this agreement) will add to the detail in patient journey course, flagging for instance how participants were monitoring their symptoms and was there an associated poor prognosis.

The group of survivors eligible for recruitment for this study are generally healthy individuals who have suffered critical illness. It is anticipated this cohort will grow to approx 36,000 participants.

The data would be available for analysis alongside the extant Genomics England data set of 100,000 Genomes Project participants and would be made available to approved researchers worldwide as per existing governance procedures. This 100,000 Genomes Project data set will act as an appropriate matched control group. Data on the 100,000 Genomes Cohort will be provided to NHS Digital for linkage - (as they will act as a control cohort), as well as new additions for the GenOMICC Study.

The below detail pertains to the background of the study and susceptibility to infection sets out why Genomics are investigating. The origin of the GenOMICC study was focused on smaller cohorts of participants. However, in collaboration with the COG-UK group, this is now expanded to whole genome sequence of approx. 36,000 affected individuals as set out above.

GenOMICC Study Background:

Susceptibility to infection is profoundly heritable (Sorensen et al. 1988). Patients who develop life-threatening illness following infection with usually innocuous pathogens, such as influenza (Miller et al. 2010), are genetically different from the rest of the population (Albright et al. 2008). Understanding the genetic mechanisms of susceptibility may yield new therapeutic targets (Baillie 2014) that can be used to make susceptible patients more similar to individuals who are resistant to, or tolerant of, specific pathogens.

The genetic mechanisms of susceptibility to infection are likely to be highly pathogen-specific and may even have opposing roles in different infections (as for CCR5 variants in HIV [Human Immunodeficiency Virus] (Huang et al. 1996) and WNV (Glass et al. 2006) infection). Pathogen-specific interventions (e.g. small molecules to inhibit an enzyme or receptor that is dysfunctional in resistant individuals) would therefore be protective to the host in a similar way to antibiotics, with the advantage that it is conceptually more difficult for any one pathogen to evolve resistance to such a therapy.

A second, more challenging problem arises in patients who become critically ill following infection. The patterns of immune-mediated organ dysfunction, immunoparesis, and death are very similar in severe infections and sterile systemic injuries (such as burns, haemorrhage, pancreatitis and trauma). Ultimately, death is a consequence of the host response to injury (Angus and Poll 2013), through final common pathways of organ failure that are clinically and biochemically evident, and unrelated to the original precipitant.

Broadly, the severity of critical illness follows directly from the severity and duration of the initial insult. In bacterial sepsis, early antibiotics are the mainstay of therapy; in influenza, early antivirals; in haemorrhage, early resuscitation; in trauma, urgent action to prevent secondary injury. There are no therapies with which to modulate the host response to systemic injury.

There is a lack of direct evidence of heritability for outcomes of critical illness, due in part to difficulties in defining and quantifying the heterogeneous multi-organ dysfunction syndrome (MODS), and in part due to the rapid pace of change in critical care medicine, making it impossible to tackle this question in long term outcome studies. However, clinical and biological evidence support the hypothesis that the pathogenesis of MODS is immune in origin (Angus and Poll 2013). Hence, predictions can be made from the extensive knowledge of other immune conditions. Whether or not MODS is considered to be an autoimmune or infectious condition is moot: these conditions share a great deal of similarity in genetic predispositions, cell types and mechanisms of pathogenesis. It is therefore very likely that propensity to survive MODS has a heritable component, and there is some direct evidence in support of this hypothesis (Rautanen et al. 2015). If this is the case, then the identity of the specific variants that contribute to outcome could potentially be utilised to design therapies to promote survival after the onset of MODS.

This study aims to identify genetic predisposition to specific syndromes of critical illness. Specifically, susceptibility to life-threatening infections caused by an identified pathogen, and susceptibility to death following the onset of organ failure due to sepsis or sterile injury. In order to maximise the probability of identifying host genetic loci associated with susceptibility, Genomics England will restrict some analyses to younger individuals in good general health and lacking in known predisposing factors.

The same principle was used to determine an upper age limit for inclusion for some analyses. With advancing age, there is an increase in undiagnosed co-morbidity, frailty, and susceptibility to serious complications of infection or critical injury. There is therefore an increase in the probability of susceptibility to, and mortality from, critical illness that is consequent upon non-genetic factors.

Participation Group:

Patients will be identified and recruited in hospital during acute illness. Potential participants will be identified through hospital workers upon presentation at recruiting sites. The disease processes under study have a high mortality, so it is desirable to recruit patients as early as possible in the disease process.

Participants or an appropriate parent/guardian/consultee will be approached by staff trained in consent procedures that protect the rights of the patient and adhere to the ethical principles within the Declaration of Helsinki. Staff will explain the details of the study to the participant or parent/guardian/consultee and allow them time to discuss and ask questions. The staff will review the informed consent form with the person giving consent (or assent) and endeavour to ensure understanding of the contents, including study procedures, risks, benefits, and the right to withdraw. Participants who agree to participate (or their parent/guardian or consultee who declares their wishes to do so) will be asked to sign and date an informed consent form.

In view of the importance of early sampling, participants or their parent/guardian/consultee will be permitted to consent and begin to participate in the study immediately if they wish to do so. Those who prefer more time to consider participation will be approached again after an agreed time, normally one day, to discuss further.

Patients who meet the inclusion/exclusion criteria and who have given informed consent to participate directly, or have been consented by a parent/guardian or whose wishes have been declared by a consultee, will be enrolled to the study.

Samples and data will be collected according to available resources and the weight of the patient will be measured for children under 12 in order to prevent excessive volume sampling. Samples required for medical management will at all times have priority over samples taken for research tests. Aliquots or samples for research purposes should never compromise the quality or quantity of samples required for medical management. Wherever practical, taking research samples should be timed to coincide with clinical sampling. The research team will be responsible for sharing the sampling protocol with health care workers supporting patient management in order to minimise disruption to routine care and avoid unnecessary procedures.

Consent will be sought from patients who survive critical illness and regain capacity to give consent. At each of the follow-up sessions, the investigator gathering data will determine whether the patient has regained capacity. In the event that a patient continues to be incapacitated beyond the follow-up period, the local investigator will plan a subsequent capacity check at a specific date, after an interval to be determined by the nature of the incapacity. The planned dates of capacity checks on incapacitated survivors will be stored locally in the site file, together with a record of the outcome of each check.

Patients who decline to participate at this stage will be removed from the study. Where the patient cannot be recontacted despite best endeavours, they will remain in the study.

Withdrawal:

Participants are freely able to decline participation in this study or to withdraw from participation at any point without suffering any implied or explicit disadvantage. All patients will be treated according to standard practice regardless of whether they participate.

The following options of withdrawal will be made available to participants:

1. Partial withdrawal. Data WILL continue to be updated and used for research, but no further contact will be made with the participant

2. Full withdrawal.

• no further contact will be made with the participant;

• data will not be updated from health records;

• data will not be removed from research that is underway or has already been done, and an audit record will be maintained to confirm participation.

Consent version and lifecourse follow-up

The first COVID positive patient was recruited to the GenOMICC study in March 2020. All patients (c.1500) currently recruited to the GenOMICC study are on consent and Protocol version 1.08 (which allows for COVID research but not longitudinal life course follow up). This Protocol v2.1 (submitted as part of this DARS request) was Research Ethics Committe (REC) approved on 23rd March 2020, IRAS [Integrated Research Application System] IDs are: 269326 & 189676 (https://www.hra.nhs.uk/covid-19-research/approved-covid-19-research/269326/). Genomics England will attempt to reconsent all patients recruited under version 1.08 onto the newly amended materials (version 2.5 of the patient information sheet – submitted as part of this DARS application) which allows for longitudinal lifecourse follow-up. For any patients on the v1.08 Protocol for which Genomics England are not able to seek consent, Genomics England will not be requesting their data for linkage. For patients prospectively recruited onto the v2.1 Protocol and consent materials, Genomics England will be requesting their data for linkage and follow-up .

Datasets requested from NHS Digital:

Consideration has been be given to assess and ensure that access to the data sets requested are inline with COVID-19 related purpose, in terms of the restrictions set out in Reg 3(1) COPI, below are details of what each of the data sets will at a high level provide insight to.

Primary Care dataset: Genomics England anticipate GPES (General Practice Extraction Service) Data for Pandemic Planning and Research (GDPPR) extracts to assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings.

Hospital Episode Statistics (HES): Outpatients (OP), Admitted Patient Care (APC), Critical Care (CC) and Accident & Emergency (AE)/ Emergency Care Data Set (ECDS). These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

Diagnostic Imaging Dataset (DIDS). This provides invaluable, detailed information to build on participants' phenotypes, e.g. tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

Secondary Uses Service datasets. The minimal latency in availability of these datasets is highly desirable for the research objectives set out in this project.

Mental Health Data sets: The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

Cancer Registration Data sets: To see the incidence of cancer within the cohort

Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

COVID datasets: These datasets, including SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus.

Assessment of the datasets has been undertaken and NHS Digital are satisfied that they are necessary for the COVID-19 work being undertaken. Genomics have confirmed that all research which is approved from the GenoMICC study using the data for the COVID-19 specific purposes will be published here https://www.genomicsengland.co.uk/about-gecip/research-2/

Genomics England Industry access:

Genomics England works with industry through its Discovery Forum. The Forum provides a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Industry partners comprise pharmaceutical, biotech and diagnostic companies, and those specialising in laboratory and data analysis. These companies have joined the Forum to work in a pre-competitive environment with access to a selection of genomic and associated clinical data. Ultimately, the Discovery Forum aims to help turn research findings into treatments, diagnostics and benefits for patients as soon as possible.

As the Discovery Forum is a collaborative venture, no fees are levied on participating organisations to access the COVID data, however they are charged based on storage and compute, such as running their own bioinformatics pipeline. All members of the Forum are obliged to publish all findings and research at the point at which intellectual property for any product is protected.

The Forum was created in July 2017 and allows industrial partners to report back to Genomics England on what aspects of the data are proving to be most useful to their research studies, what data is missing and how the data should be collected and developed further so it is captures what industry needs, in a format that is compatible with their research and data systems. These partners act as a 'critical friend' and have made many helpful suggestions to increase the likelihood of successful research in the future for all those using Genomics England's landmark data set.

The lawful basis for the release and use of the confidential data being shared under this version of the agreement is Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations entitled to process this under COPI for COVID-19 purposes. The application of this has been based on the information provided in the Whole genome sequencing of patients severely affected by COVID-19 funding proposal from The GenOMICC - COVID Genomics UK (CoG-UK) partnership which was supported by the CMO of England and the CFO of the DHSC.

The lawful basis for processing Participant Data under the General Data Protection Regulation (GDPR) used by Genomics England is legitimate interests as set out under Article 6(1)(f) of the GDPR. It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

The only permitted activities under this Data Sharing Agreement (DSA) are for COVID-19 purposes and within bounds of Reg 3(2) COPI. Reg 3 (2) COPI states that: "2) For the purposes of this regulation, “processing” includes any operations, or set of operations set out in regulation 2(2) which are undertaken for the purposes set out in paragraph (1)." The research relates to the monitoring and managing of COVID-19 and would therefore be covered by Reg 3(1)(d) of COPI

Genomics England completed sequencing 100,000 genomes at the end of 2018 (https://www.newscientist.com/article/2187499-uk-dna-project-hits-major-milestone-with-100000- genomes-sequenced/). During 2018, the Genomics England Research Environment was established to allow research access to de-identified genomic and clinical data received from NHS Digital. Thirty disease and cross-cutting GeCIP research domains were requested and approved, with now over 3000 GeCIP members given access to the Research Environment. Genomics England had also created the industry Discovery Forum to provide a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Although the 100,000 genomes project has completed recruitment, Genomics England is committed to continue gathering life-long clinical data from the participants and making these available in the Research Environment.

Genomics England will be responsible for the onward workflow, in partnership with Illumina for the delivery of 30X whole genome sequences, subject to passing appropriate sequence QC, into the Genomics England data centre. Alignment and variant calling will be performed alongside the potential application of bespoke immunodeficiency panels as part of the Genomics England bioinformatics pipeline analysis.

Genomic data will be released into the Genomics England Trusted Research Environment where it will be linked with associated clinical data.

The GenOMICC study is backed by £28 million from Genomics England, UK Research and Innovation, the Department of Health and Social Care and the National Institute for Health Research. Illumina will sequence all 35,000 genomes and share some of the cost via an in-kind contribution.

A press release on 13/05/20 included a comment from Health and Social Care Secretary Matt Hancock: “As each day passes, we are learning more about this virus, and understanding how genetic makeup may influence how people react to it is a critical piece of the jigsaw.

“This is a ground-breaking and far-reaching study which will harness the UK’s world-leading genomics science to improve treatments and ultimately save lives across the world.” To date, nearly 3000 patients have been recruited into the project.

As of March 2020, the Genomics England Research Environment contained 107,694 genomes, of which, 33,461 were cancer and 74,233 were rare diseases.

The Research environment also contained clinical data on 89,157 participants (this is because cancer participants have two genomes submitted). The clinical data for 17,246 cancer participants includes clinical data from NHS Digital (HES OP/APC/ CC and AE) but also cancer specific data from Public HeaLth England Cancer Registry (NCRAS). The combination of clinical data for all 100,000 participants totals about 5m records.

As the GenOMICC study prospectively recruits participants, the aim will be to use the existing 100,000 participants and age and match-ranked controls for those entered into the study. As Genomics England prospectively enrolls more participants into the study, Genomics England plans further releases of genomic and clinical data, including clinical data received from NHS Digital and viral and host genomic data, into the Research Environment montly in order to continue support for, and to further develop, this ground-breaking resource.

Specific outputs over the period of this agreement are therefore to release updated genomic and clinical data for the 100,000 genomes participants and GenOMICC participants into the Research Environment on the dates shown above.

The 100,000 genomes project has been hugely successful and provided numerous academic and clinical publications and discoveries. The success of the project has been based on the strength of the clinical data provided by NHS Digital. Understanding this significant value is why Genomics England are so keen to add NHS Digital data to its clinical data source for the GenOMICC study.

The GenOMICC study is very much in its infancy and whole genome sequencing has only begun in the last month. It is thus too early to demonstrate any significant outcomes. These outcomes will only gain power and relevance with more prospectively recruited patients and a breadth and depth of clinical data. By providing this to researchers, Genomics England can provide them the necessary tools to explore the genomic data.

This agreement is seeking approval to request data to support The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole genome sequencing (WGS) of patients severely affected by COVID-19. The work programme has sign off and prioritisation from the Chief Medical Officer for England (CMO)

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS Digital and Health Data Research UK (HDRUK). Genomics England will include deep immune “omic” datasets on a subset of patients. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people) and UK Biobank data sets (500,000 people) with WGS where more cases may be identified, including those with milder disease and unaffected people.

This mention of linkage of the NHS Digital data to UK Biobank data is purely aspirational at present. This has not been approved under previous iterations of the agreement, and is not covered under v1.2 of this agreement. Genomics England can confirm that if such linkage were to occur - then appropriate documentation (including transparency, patient, consent and ethics materials) would be provided to NHS Digital and a subsequent amended application put in place.

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England Trusted Research Environment to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and it’s outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel.

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By undertaking a prospective study design that leverages existing recruitment infrastructure in critical care, together with Genomics England, NHS England, Devolved Nations and Public Health England (PHE) infrastructure this research will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 whole genome sequences (WGS) this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

Genomics England Background: (For Context)

Genomics England was established by the Department of Health to deliver the 100,000 Genomes Project. This followed the announcement in December 2012 by the Prime Minister of a programme of whole genome sequencing (WGS) as part of the UK Government’s Life Sciences Strategy. The principal objective of the 100,000 Genomes Project was to sequence 100,000 genomes from participants with cancer and rare disorders, and to link the sequence data to a standardised, extensible account of diagnosis, treatment, and outcomes gathered at recruitment, but primarily through the ongoing collection of medical records.

Data will be released into the Genomics England Trusted Research Environment where it will be linked with associated clinical data as well as additional data sources, which will include NHS Digital data requested through this agreement, COVID-19 testing feeds and viral genomics from Public Health England and data feeds from the Intensive Care National Audit Registry (ICNARC).

The Department of Health and Social Care have granted approval for Genomics England to procure a new, rapidly deployable Research Environment for the COVID-19 programme from existing core funding, which will provide a secure and collaborative workspace that enables researchers to perform COVID-19 genomic data analysis. The new Research Environment (COVID-RE) will provide an intuitive, integrated and collaborative user experience that enables effective COVID-19 research outcomes across a wide range of academic and Biotech/Pharma researchers with varying levels of technical competency. This offers a major upgrade to our current environment and will comprise user-centric, contemporary bioinformatic workflows, support opensource tooling, and enable shared workspaces between Genomics England and Partners. COVID-RE must serve the immediate COVID-19 research effort and may also advance the transformation of Genomics England’s platform infrastructure, which is a key enabler to the research community.

There are two key value streams provided by the COVID-RE. Firstly ‘raw data to analytics ready data’ stream which must permit the collection of data from multiple locations from unstructured, through semi and fully structured forms and transforms them the appropriate data model, data store based on their ongoing use and availability. Secondly the ‘discovery to insight’ stream that supports researchers by providing the capability and the framework to support their User Journey from understanding the data available to them through to providing the necessary analytics and publishing tools.

The newly established COVID-RE will provide the following:

• Seamless interface with cloud storage and compute capabilities.

• A unified data platform containing datastores appropriate for all the required clinical and genomic data types.

• Data integration capability to deliver analytics-ready datasets into domain-specific data stores across batch and streaming integration patterns.

• Standards-based access services providing secure, fast, flexible, robust and auditable access to TRE data assets.

• Applications to support the research user journey from an exploration of data sets, through cohort building, analysis and publication - providing tools appropriate to a variety of user requirements (ways of working) and programming competency.

• Applications and workflows can be delivered natively within the platform, however COVID-RE must enable access to container-based applications and, via a set of hardened APIs, to a relevant external service (as long as security is maintained).

Details of the sublicence model via the Genomics England Trusted Research Environment are supplied within the processing activities section of this agreement.

The additional clinical data is key for researchers to be able to understand and infer clinically relevant and actionable findings. The aim is to provide a high quality, diverse clinical dataset, detailing each participant’s journey and to understand pre-existing conditions and also the early behaviours in the disease course. Genomics England currently have an agreement to receive NHS Digital data for the extant 100,000 Genomes Project participants (DARS-NIC-12784) and have seen first-hand the depth and quality of the data and how it has aided researchers.

To that aim, the significant gap in the current data collection for the COVID-19 project can be addressed by the non-standard NHS Digital data feed.

The Secondary Use Services Admitted Patient Care Feed (SUS APC) would provide as close to real-time data for researchers and in the current climate is vital to ensure no delays.

The associated COVID-19 data-sets (including NHS111 and CV19 Testing Data in particular which will be requested under a future version of this agreement) will add to the detail in patient journey course, flagging for instance how participants were monitoring their symptoms and was there an associated poor prognosis.

The group of survivors eligible for recruitment for this study are generally healthy individuals who have suffered critical illness. It is anticipated this cohort will grow to approx 36,000 participants.

The data would be available for analysis alongside the extant Genomics England data set of 100,000 Genomes Project participants and would be made available to approved researchers worldwide as per existing governance procedures. This 100,000 Genomes Project data set will act as an appropriate matched control group. Data on the 100,000 Genomes Cohort will be provided to NHS Digital for linkage - (as they will act as a control cohort), as well as new additions for the GenOMICC Study.

The below detail pertains to the background of the study and susceptibility to infection sets out why Genomics are investigating. The origin of the GenOMICC study was focused on smaller cohorts of participants. However, in collaboration with the COG-UK group, this is now expanded to whole genome sequence of approx. 36,000 affected individuals as set out above.

GenOMICC Study Background:

Susceptibility to infection is profoundly heritable (Sorensen et al. 1988). Patients who develop life-threatening illness following infection with usually innocuous pathogens, such as influenza (Miller et al. 2010), are genetically different from the rest of the population (Albright et al. 2008). Understanding the genetic mechanisms of susceptibility may yield new therapeutic targets (Baillie 2014) that can be used to make susceptible patients more similar to individuals who are resistant to, or tolerant of, specific pathogens.

The genetic mechanisms of susceptibility to infection are likely to be highly pathogen-specific and may even have opposing roles in different infections (as for CCR5 variants in HIV [Human Immunodeficiency Virus] (Huang et al. 1996) and WNV (Glass et al. 2006) infection). Pathogen-specific interventions (e.g. small molecules to inhibit an enzyme or receptor that is dysfunctional in resistant individuals) would therefore be protective to the host in a similar way to antibiotics, with the advantage that it is conceptually more difficult for any one pathogen to evolve resistance to such a therapy.

A second, more challenging problem arises in patients who become critically ill following infection. The patterns of immune-mediated organ dysfunction, immunoparesis, and death are very similar in severe infections and sterile systemic injuries (such as burns, haemorrhage, pancreatitis and trauma). Ultimately, death is a consequence of the host response to injury (Angus and Poll 2013), through final common pathways of organ failure that are clinically and biochemically evident, and unrelated to the original precipitant.

Broadly, the severity of critical illness follows directly from the severity and duration of the initial insult. In bacterial sepsis, early antibiotics are the mainstay of therapy; in influenza, early antivirals; in haemorrhage, early resuscitation; in trauma, urgent action to prevent secondary injury. There are no therapies with which to modulate the host response to systemic injury.

There is a lack of direct evidence of heritability for outcomes of critical illness, due in part to difficulties in defining and quantifying the heterogeneous multi-organ dysfunction syndrome (MODS), and in part due to the rapid pace of change in critical care medicine, making it impossible to tackle this question in long term outcome studies. However, clinical and biological evidence support the hypothesis that the pathogenesis of MODS is immune in origin (Angus and Poll 2013). Hence, predictions can be made from the extensive knowledge of other immune conditions. Whether or not MODS is considered to be an autoimmune or infectious condition is moot: these conditions share a great deal of similarity in genetic predispositions, cell types and mechanisms of pathogenesis. It is therefore very likely that propensity to survive MODS has a heritable component, and there is some direct evidence in support of this hypothesis (Rautanen et al. 2015). If this is the case, then the identity of the specific variants that contribute to outcome could potentially be utilised to design therapies to promote survival after the onset of MODS.

This study aims to identify genetic predisposition to specific syndromes of critical illness. Specifically, susceptibility to life-threatening infections caused by an identified pathogen, and susceptibility to death following the onset of organ failure due to sepsis or sterile injury. In order to maximise the probability of identifying host genetic loci associated with susceptibility, Genomics England will restrict some analyses to younger individuals in good general health and lacking in known predisposing factors.

The same principle was used to determine an upper age limit for inclusion for some analyses. With advancing age, there is an increase in undiagnosed co-morbidity, frailty, and susceptibility to serious complications of infection or critical injury. There is therefore an increase in the probability of susceptibility to, and mortality from, critical illness that is consequent upon non-genetic factors.

Participation Group:

Patients will be identified and recruited in hospital during acute illness. Potential participants will be identified through hospital workers upon presentation at recruiting sites. The disease processes under study have a high mortality, so it is desirable to recruit patients as early as possible in the disease process.

Participants or an appropriate parent/guardian/consultee will be approached by staff trained in consent procedures that protect the rights of the patient and adhere to the ethical principles within the Declaration of Helsinki. Staff will explain the details of the study to the participant or parent/guardian/consultee and allow them time to discuss and ask questions. The staff will review the informed consent form with the person giving consent (or assent) and endeavour to ensure understanding of the contents, including study procedures, risks, benefits, and the right to withdraw. Participants who agree to participate (or their parent/guardian or consultee who declares their wishes to do so) will be asked to sign and date an informed consent form.

In view of the importance of early sampling, participants or their parent/guardian/consultee will be permitted to consent and begin to participate in the study immediately if they wish to do so. Those who prefer more time to consider participation will be approached again after an agreed time, normally one day, to discuss further.

Patients who meet the inclusion/exclusion criteria and who have given informed consent to participate directly, or have been consented by a parent/guardian or whose wishes have been declared by a consultee, will be enrolled to the study.

Samples and data will be collected according to available resources and the weight of the patient will be measured for children under 12 in order to prevent excessive volume sampling. Samples required for medical management will at all times have priority over samples taken for research tests. Aliquots or samples for research purposes should never compromise the quality or quantity of samples required for medical management. Wherever practical, taking research samples should be timed to coincide with clinical sampling. The research team will be responsible for sharing the sampling protocol with health care workers supporting patient management in order to minimise disruption to routine care and avoid unnecessary procedures.

Consent will be sought from patients who survive critical illness and regain capacity to give consent. At each of the follow-up sessions, the investigator gathering data will determine whether the patient has regained capacity. In the event that a patient continues to be incapacitated beyond the follow-up period, the local investigator will plan a subsequent capacity check at a specific date, after an interval to be determined by the nature of the incapacity. The planned dates of capacity checks on incapacitated survivors will be stored locally in the site file, together with a record of the outcome of each check.

Patients who decline to participate at this stage will be removed from the study. Where the patient cannot be recontacted despite best endeavours, they will remain in the study.

Withdrawal:

Participants are freely able to decline participation in this study or to withdraw from participation at any point without suffering any implied or explicit disadvantage. All patients will be treated according to standard practice regardless of whether they participate.

The following options of withdrawal will be made available to participants:

1. Partial withdrawal. Data WILL continue to be updated and used for research, but no further contact will be made with the participant

2. Full withdrawal.

• no further contact will be made with the participant;

• data will not be updated from health records;

• data will not be removed from research that is underway or has already been done, and an audit record will be maintained to confirm participation.

Consent version and lifecourse follow-up

The first COVID positive patient was recruited to the GenOMICC study in March 2020. All patients (c.1500) currently recruited to the GenOMICC study are on consent and Protocol version 1.08 (which allows for COVID research but not longitudinal life course follow up). This Protocol v2.1 (submitted as part of this DARS request) was Research Ethics Committe (REC) approved on 23rd March 2020, IRAS [Integrated Research Application System] IDs are: 269326 & 189676 (https://www.hra.nhs.uk/covid-19-research/approved-covid-19-research/269326/). Genomics England will attempt to reconsent all patients recruited under version 1.08 onto the newly amended materials (version 2.1 – submitted as part of this DARS application) which allows for longitudinal lifecourse follow-up. For any patients on the v1.08 Protocol for which Genomics England are not able to seek consent, Genomics England will not be requesting their data for linkage. For patients prospectively recruited onto the v2.1 Protocol and consent materials, Genomics England will be requesting their data for linkage and follow-up .

Datasets requested from NHS Digital:

Consideration has been be given to assess and ensure that access to the data sets requested are inline with COVID-19 related purpose, in terms of the restrictions set out in Reg 3(1) COPI, below are details of what each of the data sets will at a high level provide insight to.

Primary Care dataset: Genomics England anticipate GPES (General Practice Extraction Service) Data for Pandemic Planning and Research (GDPPR) extracts to assist in completing the clinical image of a patient particularly around the identification of comorbidities and underlying medical conditions that were not captured in acute settings.

Hospital Episode Statistics (HES): Outpatients (OP), Admitted Patient Care (APC), Critical Care (CC) and Accident & Emergency (AE)/ Emergency Care Data Set (ECDS). These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

Diagnostic Imaging Dataset (DIDS). This provides invaluable, detailed information to build on participants' phenotypes, e.g. tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

Secondary Uses Service datasets. The minimal latency in availability of these datasets is highly desirable for the research objectives set out in this project.

Mental Health Data sets: The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

Cancer Registration Data sets: To see the incidence of cancer within the cohort

Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

COVID datasets: These datasets, including SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus.

Assessment of the datasets has been undertaken and NHS Digital are satisfied that they are necessary for the COVID-19 work being undertaken. Genomics have confirmed that all research which is approved from the GenoMICC study using the data for the COVID-19 specific purposes will be published here https://www.genomicsengland.co.uk/about-gecip/research-2/

Genomics England Industry access:

Genomics England works with industry through its Discovery Forum. The Forum provides a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Industry partners comprise pharmaceutical, biotech and diagnostic companies, and those specialising in laboratory and data analysis. These companies have joined the Forum to work in a pre-competitive environment with access to a selection of genomic and associated clinical data. Ultimately, the Discovery Forum aims to help turn research findings into treatments, diagnostics and benefits for patients as soon as possible.

As the Discovery Forum is a collaborative venture, no fees are levied on participating organisations to access the COVID data, however they are charged based on storage and compute, such as running their own bioinformatics pipeline. All members of the Forum are obliged to publish all findings and research at the point at which intellectual property for any product is protected.

The Forum was created in July 2017 and allows industrial partners to report back to Genomics England on what aspects of the data are proving to be most useful to their research studies, what data is missing and how the data should be collected and developed further so it is captures what industry needs, in a format that is compatible with their research and data systems. These partners act as a 'critical friend' and have made many helpful suggestions to increase the likelihood of successful research in the future for all those using Genomics England's landmark data set.

The lawful basis for processing Participant Data under the General Data Protection Regulation (GDPR) used by Genomics England is legitimate interests as set out under Article 6(1)(f) of the GDPR. It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then others will be added who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

The lawful basis for the release and use of the confidential data being shared under this version of the agreement is Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations entitled to process this under COPI for COVID-19 purposes. The application of this has been based on the information provided in the Whole genome sequencing of patients severely affected by COVID-19 funding proposal from The GenOMICC - COVID Genomics UK (CoG-UK) partnership which was supported by the CMO of England and the CFO of the DHSC.

The only permitted activities under this Data Sharing Agreement (DSA) are for COVID-19 purposes and within bounds of Reg 3(2) COPI. Reg 3 (2) COPI states that: "2) For the purposes of this regulation, “processing” includes any operations, or set of operations set out in regulation 2(2) which are undertaken for the purposes set out in paragraph (1)." The research relates to the monitoring and managing of COVID-19 and would therefore be covered by Reg 3(1)(d) of COPI

Genomics England completed sequencing 100,000 genomes at the end of 2018 (https://www.newscientist.com/article/2187499-uk-dna-project-hits-major-milestone-with-100000- genomes-sequenced/). During 2018, the Genomics England Research Environment was established to allow research access to de-identified genomic and clinical data received from NHS Digital. Thirty disease and cross-cutting GeCIP research domains were requested and approved, with now over 3000 GeCIP members given access to the Research Environment. Genomics England had also created the industry Discovery Forum to provide a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Although the 100,000 genomes project has completed recruitment, Genomics England is committed to continue gathering life-long clinical data from the participants and making these available in the Research Environment.

Genomics England will be responsible for the onward workflow, in partnership with Illumina for the delivery of 30X whole genome sequences, subject to passing appropriate sequence QC, into the Genomics England data centre. Alignment and variant calling will be performed alongside the potential application of bespoke immunodeficiency panels as part of the Genomics England bioinformatics pipeline analysis.

Genomic data will be released into the Genomics England Trusted Research Environment where it will be linked with associated clinical data.

The GenOMICC study is backed by £28 million from Genomics England, UK Research and Innovation, the Department of Health and Social Care and the National Institute for Health Research. Illumina will sequence all 35,000 genomes and share some of the cost via an in-kind contribution.

A press release on 13/05/20 included a comment from Health and Social Care Secretary Matt Hancock: “As each day passes, we are learning more about this virus, and understanding how genetic makeup may influence how people react to it is a critical piece of the jigsaw.

“This is a ground-breaking and far-reaching study which will harness the UK’s world-leading genomics science to improve treatments and ultimately save lives across the world.” To date, nearly 3000 patients have been recruited into the project.

As of March 2020, the Genomics England Research Environment contained 107,694 genomes, of which, 33,461 were cancer and 74,233 were rare diseases.

The Research environment also contained clinical data on 89,157 participants (this is because cancer participants have two genomes submitted). The clinical data for 17,246 cancer participants includes clinical data from NHS Digital (HES OP/APC/ CC and AE) but also cancer specific data from Public HeaLth England Cancer Registry (NCRAS). The combination of clinical data for all 100,000 participants totals about 5m records.

As the GenOMICC study prospectively recruits participants, the aim will be to use the existing 100,000 participants and age and match-ranked controls for those entered into the study. As Genomics England prospectively enrolls more participants into the study, Genomics England plans further releases of genomic and clinical data, including clinical data received from NHS Digital and viral and host genomic data, into the Research Environment on the following dates, in order to continue support for, and to further develop, this ground-breaking resource:

• 3rd August 2020

• 7th September 2020

• 5th October 2020

• 2nd November 2020

Specific outputs over the period of this agreement are therefore to release updated genomic and clinical data for the 100,000 genomes participants and GenOMICC participants into the Research Environment on the dates shown above.

This agreement is seeking approval to request data to support The GenOMICC - COVID Genomics UK (CoG-UK) partnership in researching Whole genome sequencing of patients severely affected by COVID-19. The work programme has sign off and prioritisation from the Chief Medical Officer for England

The goals of this work programme are set out below:

1. To harness world-leading UK healthcare and genomic infrastructure and systems to undertake prospective host whole genome sequencing at scale. This will elucidate the genetic architecture of host response to SARS-CoV-2 and identify opportunities to improve outcomes in the current pandemic, via international collaboration.

2. To identify rare and common variants that may affect susceptibility to response, identify novel opportunities for intervention and accelerate recovery.

3. To collect longitudinal life course datasets from primary care, hospital episodes, intensive care registries and outcomes via an extant partnership with NHS Digital and Health Data Research UK. We will include deep immune “omic” datasets on a subset of patients 9. This will allow case-control studies that capitalise upon unique UK assets, such as the 100,000 Genomes Project (97,000 people) and UK Biobank data sets (500,000 people) with WGS where more cases may be identified, including those with milder disease and unaffected people.

4. To use these rich data sets to understand the premorbid, concurrent and consequent sequelae of COVID-19 infection.

5. In partnership with the CoG-UK Viral Programme to evaluate the combination of viral and host genomics on outcomes to give pre-emptive insights into subsequent outbreaks and potentially future pandemics.

6. To provide access to these data sets via the Genomics England Trusted Research Environment to international and national academia and industry and facilitate international collaboration on COVID-19.

7. To link this to national COVID-19 clinical trials infrastructure offering potential for genomics to add value with insights into precision medicine and building a global-leading knowledgebase to enable better UK-wide and international capacity for future pandemic preparedness.

8. To engage and involve public and patients in setting strategy and priorities that shape the programme and it’s outputs. This will initially be based upon the 100,000 Genomes Project Participant Panel.

The prospective GenOMICC CoG-UK study

The variable response to COVID-19 suggests that, as with susceptibility to other infections, critical illness and mortality from COVID-19 may be determined by host genetic factors. From the 100,000 Genomes Project and the NIHR BioResource for Rare Disease it is known that rare variants cause immunodeficiency. By undertaking a prospective study design that leverages existing recruitment infrastructure in critical care, together with Genomics England, NHS England, Devolved Nations and PHE infrastructure this research will be able to apply the most advanced genomic testing to those most severely affected people admitted to hospital or intensive care.

The retrospective GenOMICC CoG-UK study:

The retrospective cohorts offer control arms for the study but also new case finding potential, particularly for people who have a milder clinical case. The study propose to harness the potential of two key national data assets. Firstly, analysis of the 100,000 Genomes Project data set which provides the genome sequences of 97,000 participants where they can use their longitudinal life course datasets to identify those affected by COVID-19, as well as providing appropriate unaffected controls. This dataset includes 627 families with rare immunodeficiency syndromes, which may allow insights to be accelerated because of co-existence of rare variants. Secondly, the UK Biobank cohort will provide 120,000 WGS this year, building to 500,000 WGS over the next 18 months from people, currently aged circa 55-85 years old, which is skewed towards the at-risk age groups for COVID-19 but will provide additional cases and controls, including mildly affected individuals.

Over the next five years these datasets will be enriched further by consented individuals from the NHS Genomic Medicine Service, and the new Genomics England programmes proposed in their strategic plan under consideration by Government. Furthermore, the Accelerating Detection of Disease Cohort will enrol up to 5 million people with genome-wide variants available with longitudinal life course data sets that could particularly add value to host response-variant associations and polygenic risk scores.

Genomics England Background:

Genomics England was established by the Department of Health to deliver the 100,000 Genomes Project. This followed the announcement in December 2012 by the Prime Minister of a programme of whole genome sequencing (WGS) as part of the UK Government’s Life Sciences Strategy. The principal objective of the 100,000 Genomes Project was to sequence 100,000 genomes from participants with cancer and rare disorders, and to link the sequence data to a standardised, extensible account of diagnosis, treatment, and outcomes gathered at recruitment, but primarily through the ongoing collection of medical records.

Data will be released into the Genomics England Trusted Research Environment where it will be linked with associated clinical data as well as additional data sources, which will include NHS Digital data requested through this agreement, COVID-19 testing feeds and viral genomics from Public Health England and data feeds from the Intensive Care National Audit Registry (ICNARC).

The Department of Health and Social Care have granted approval for Genomics England to procure a new, rapidly deployable Research Environment for the COVID-19 programme from existing core funding, which will provide a secure and collaborative workspace that enables researchers to perform COVID-19 genomic data analysis. The new Research Environment (COVID-RE) will provide an intuitive, integrated and collaborative user experience that enables effective COVID-19 research outcomes across a wide range of academic and Biotech/Pharma researchers with varying levels of technical competency. This offers a major upgrade to our current environment and will comprise user-centric, contemporary bioinformatic workflows, support opensource tooling, and enable shared workspaces between Genomics England and Partners. COVID-RE must serve the immediate COVID-19 research effort and may also advance the transformation of Genomics England’s platform infrastructure, which is a key enabler to the research community.

There are two key value streams provided by the COVID-RE. Firstly ‘raw data to analytics ready data’ stream which must permit the collection of data from multiple locations from unstructured, through semi and fully structured forms and transforms them the appropriate data model, data store based on their ongoing use and availability. Secondly the ‘discovery to insight’ stream that supports researchers by providing the capability and the framework to support their User Journey from understanding the data available to them through to providing the necessary analytics and publishing tools.

The newly established COVID-RE will provide the following:

• Seamless interface with cloud storage and compute capabilities.

• A unified data platform containing datastores appropriate for all the required clinical and genomic data types.

• Data integration capability to deliver analytics-ready datasets into domain-specific data stores across batch and streaming integration patterns.

• Standards-based access services providing secure, fast, flexible, robust and auditable access to TRE data assets.

• Applications to support the research user journey from an exploration of data sets, through cohort building, analysis and publication - providing tools appropriate to a variety of user requirements (ways of working) and programming competency.

• Applications and workflows can be delivered natively within the platform, however COVID-RE must enable access to container-based applications and, via a set of hardened APIs, to a relevant external service (as long as security is maintained).

Details of the sublicence model via the Genomics England Trusted Research Environment are supplied within the processing activities section of this agreement.

The additional clinical data is key for researchers to be able to understand and infer clinically relevant and actionable findings. The aim is to provide a high quality, diverse clinical dataset, detailing each participant’s journey and to understand pre-existing conditions and also the early behaviours in the disease course. Genomics England currently have an agreement to receive NHS Digital data for the extant 100,000 Genomes Project participants (DARS-NIC-12784) and have seen first-hand the depth and quality of the data and how it has aided researchers.

To that aim, the significant gap in the current data collection for the COVID-19 project can be addressed by the non-standard NHS Digital data feed.

The SUS APC feed would provide as close to real-time data for researchers and in the current climate is vital to ensure no delays.

The associated COVID-19 data-sets (including NHS111 and CV19 Testing Data in particular which will be requested under a future version of this agreement) will add to the detail in patient journey course, flagging for instance how participants were monitoring their symptoms and was there an associated poor prognosis.

The group of survivors eligible for recruitment for this study are generally healthy individuals who have suffered critical illness. It is anticipated this cohort will grow to approx 36,000 participants.

The data would be available for analysis alongside the extant Genomics England data set of 100,000 Genomes Project participants and would be made available to approved researchers worldwide as per existing governance procedures. This 100,000 Genomes Project data set will act as an appropriate matched control group. Data on the 100,000 Genomes Cohort will be provided to NHS Digital for linkage - (as they will act as a control cohort), as well as new additions for the GenOMICC Study.

The below detail pertains to the background of the study and susceptibility to infection sets out why Genomics are investigating. The origin of the GenOMICC study was focused on smaller cohorts of participants. However, in collaboration with the COG-UK group, this is now expanded to whole genome sequence of approx. 36,000 affected individuals as set out above.

GenOMICC Study Background:

Susceptibility to infection is profoundly heritable (Sorensen et al. 1988). Patients who develop life-threatening illness following infection with usually innocuous pathogens, such as influenza (Miller et al. 2010), are genetically different from the rest of the population (Albright et al. 2008). Understanding the genetic mechanisms of susceptibility may yield new therapeutic targets (Baillie 2014) that can be used to make susceptible patients more similar to individuals who are resistant to, or tolerant of, specific pathogens.

The genetic mechanisms of susceptibility to infection are likely to be highly pathogen-specific and may even have opposing roles in different infections (as for CCR5 variants in HIV (Huang et al. 1996) and WNV (Glass et al. 2006) infection). Pathogen-specific interventions (e.g. small molecules to inhibit an enzyme or receptor that is dysfunctional in resistant individuals) would therefore be protective to the host in a similar way to antibiotics, with the advantage that it is conceptually more difficult for any one pathogen to evolve resistance to such a therapy.

A second, more challenging problem arises in patients who become critically ill following infection. The patterns of immune-mediated organ dysfunction, immunoparesis, and death are very similar in severe infections and sterile systemic injuries (such as burns, haemorrhage, pancreatitis and trauma). Ultimately, death is a consequence of the host response to injury (Angus and Poll 2013), through final common pathways of organ failure that are clinically and biochemically evident, and unrelated to the original precipitant.

Broadly, the severity of critical illness follows directly from the severity and duration of the initial insult. In bacterial sepsis, early antibiotics are the mainstay of therapy; in influenza, early antivirals; in haemorrhage, early resuscitation; in trauma, urgent action to prevent secondary injury. There are no therapies with which to modulate the host response to systemic injury.

There is a lack of direct evidence of heritability for outcomes of critical illness, due in part to difficulties in defining and quantifying the heterogeneous multi-organ dysfunction syndrome (MODS), and in part due to the rapid pace of change in critical care medicine, making it impossible to tackle this question in long term outcome studies. However, clinical and biological evidence support the hypothesis that the pathogenesis of MODS is immune in origin (Angus and Poll 2013). Hence, predictions can be made from the extensive knowledge of other immune conditions. Whether or not MODS is considered to be an autoimmune or infectious condition is moot: these conditions share a great deal of similarity in genetic predispositions, cell types and mechanisms of pathogenesis. It is therefore very likely that propensity to survive MODS has a heritable component, and there is some direct evidence in support of this hypothesis (Rautanen et al. 2015). If this is the case, then the identity of the specific variants that contribute to outcome could potentially be utilised to design therapies to promote survival after the onset of MODS.

This study aims to identify genetic predisposition to specific syndromes of critical illness. Specifically, susceptibility to life-threatening infections caused by an identified pathogen, and susceptibility to death following the onset of organ failure due to sepsis or sterile injury. In order to maximise the probability of identifying host genetic loci associated with susceptibility, Genomics England will restrict some analyses to younger individuals in good general health and lacking in known predisposing factors.

The same principle was used to determine an upper age limit for inclusion for some analyses. With advancing age, there is an increase in undiagnosed co-morbidity, frailty, and susceptibility to serious complications of infection or critical injury. There is therefore an increase in the probability of susceptibility to, and mortality from, critical illness that is consequent upon non-genetic factors.

Withdrawal:

Participants are freely able to decline participation in this study or to withdraw from participation at any point without suffering any implied or explicit disadvantage. All patients will be treated according to standard practice regardless of whether they participate.

The following options of withdrawal will be made available to participants:

1. Partial withdrawal. Data WILL continue to be updated and used for research, but no further contact will be made with the participant

2. Full withdrawal.

• no further contact will be made with the participant;

• data will not be updated from health records;

• data will not be removed from research that is underway or has already been done, and an audit record will be maintained to confirm participation.

Consent version and lifecourse follow-up

The first COVID positive patient was recruited to the GenOMICC study in March 2020. All patients (c.1500) currently recruited to the GenOMICC study are on consent and Protocol version 1.08 (which allows for COVID research but not longitudinal life course follow up). This Protocol v2.1 (submitted as part of this DARS request) was REC approved on 23rd March 2020, IRAS IDs are: 269326 & 189676 (https://www.hra.nhs.uk/covid-19-research/approved-covid-19-research/269326/). Genomics England will attempt to reconsent all patients recruited under version 1.08 onto the newly amended materials (version 2.1 – submitted as part of this DARS application) which allows for longitudinal lifecourse follow-up. For any patients on the v1.08 Protocol for which Genomics England are not able to seek consent, Genomics England will not be requesting their data for linkage. For patients prospectively recruited onto the v2.1 Protocol and consent materials, Genomics England will be requesting their data for linkage and follow-up .

Datasets requested from NHS Digital:

Consideration has been be given to assess and ensure that access to the data sets requested are inline with COVID-19 related purpose, in terms of the restrictions set out in Reg 3(1) COPI, below are details of what each of the data sets will at a high level provide insight to.

Hospital Episode Statistics: Outpatients, Admitted Patient Care, Critical Care and Accident & Emergency/ ECDS. These datasets provide the core clinical data for participants and are vital to the provision of a detailed medical history for participants.

Diagnostic Imaging Dataset. This provides invaluable, detailed information to build on participants' phenotypes, e.g. tumour size and spread in cancer, adding to the understanding of patients' histories on individual and cohort level and their relationship with genomic alterations.

Secondary Uses Service datasets. The minimal latency in availability of these datasets is highly desirable for the research objectives set out in this project.

Mental Health Data sets: The 100,000 Genomes Project includes recruitment of psychiatric diseases and others with mental health phenotypes: intellectual disability and seizures are some of the most prevalent conditions within the Project. To-date nearly 10% of project participants have a mental health record. Mental health data are therefore vital in ensuring that a complete and relevant medical history is available for all participants.

Cancer Registration Data sets: To see the incidence of cancer within the cohort

Mortality data are essential for performing survival analyses and as a metric for success of medical care: this is crucial information for research in combination with other medical history. Cause of death information is vital in order to determine if mortality is related to the primary disease of a participant or to highlight unforeseen trends. Knowledge of participant death is also vital for the correct analysis of medical timeline data and for the management of participant cohorts.

COVID datasets: These datasets, including SGSS (Second Generation Surveillance System Data Set) and CHESS (COVID-19 Hospitalization in England Surveillance System) will be crucial to identify early Prognostic features in those affected with Coronavirus.

Assessment of the datasets has been undertaken and NHS Digital are satisfied that they are necessary for the COVID-19 work being undertaken. Genomics have confirmed that all research which is approved from the GenoMICC study using the data for the COVID-19 specific purposes will be published here https://www.genomicsengland.co.uk/about-gecip/research-2/

Genomics England Industry access:

Genomics England works with industry through its Discovery Forum. The Forum provides a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Industry partners comprise pharmaceutical, biotech and diagnostic companies, and those specialising in laboratory and data analysis. These companies have joined the Forum to work in a pre-competitive environment with access to a selection of genomic and associated clinical data. Ultimately, the Discovery Forum aims to help turn research findings into treatments, diagnostics and benefits for patients as soon as possible.

As the Discovery Forum is a collaborative venture, no fees are levied on participating organisations to access the COVID data, however they are charged based on storage and compute, such as running their own bioinformatics pipeline. All members of the Forum are obliged to publish all findings and research at the point at which intellectual property for any product is protected. Participants in the 100,000 Genomes Project have been asked explicitly to give consent for commercial companies to access their de-identified genome and health data.

The Forum was created in July 2017 and allows industrial partners to report back to Genomics England on what aspects of the data are proving to be most useful to their research studies, what data is missing and how the data should be collected and developed further so it is captures what industry needs, in a format that is compatible with their research and data systems. These partners act as a 'critical friend' and have made many helpful suggestions to increase the likelihood of successful research in the future for all those using Genomics England's landmark data set.

The lawful basis for processing Participant Data under the General Data Protection:

Regulation (GDPR) used by Genomics England is legitimate interests as set out under Article 6(1)(f) of the GDPR. It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

It is necessary for Genomics England to process Participant Data for its legitimate interests in carrying out medical research and in providing reports used by clinicians in their care of Participants.

The processing is necessary to support and enable Genomics England's legitimate interests in enabling new medical research on using genomics in health care, and on the causes, diagnosis and treatment of COVID-19.

Patients and the public will be at the heart of this programme. Initially the researchers will involve the extant 35 strong Genomics England Participant Panel and then we will add others who have been affected by COVID-19 at a later point. These participants and members of the public will be represented on all committees and working groups and will also meet separately.

The beneficiaries are:

o Participants - through the work Genomics England do will ultimately influence their care;

o researchers and industry - by giving them access to a unique ground-breaking resource of genomic data combined with life-course clinical data;

o and the wider public - by accelerating the uptake of genomic medicine making it available to patients in the UK.

The lawful basis for the release and use of the confidential data being shared under this version of the agreement is Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations entitled to process this under COPI for COVID-19 purposes. The application of this has been based on the information provided in the Whole genome sequencing of patients severely affected by COVID-19 funding proposal from The GenOMICC - COVID Genomics UK (CoG-UK) partnership which was supported by the CMO of England and the CFO of the DHSC.

Genomics England completed sequencing 100,000 genomes at the end of 2018 (https://www.newscientist.com/article/2187499-uk-dna-project-hits-major-milestone-with-100000- genomes-sequenced/). During 2018, the Genomics England Research Environment was established to allow research access to de-identified genomic and clinical data received from NHS Digital. Thirty disease and cross-cutting GeCIP research domains were requested and approved, with now over 3000 GeCIP members given access to the Research Environment. Genomics England had also created the industry Discovery Forum to provide a platform for collaboration and engagement between Genomics England, industry partners, academia, the NHS and the wider UK genomics landscape.

Although the 100,000 genomes project has completed recruitment, Genomics England is committed to continue gathering life-long clinical data from the participants and making these available in the Research Environment.

Genomics England will be responsible for the onward workflow, in partnership with Illumina for the delivery of 30X whole genome sequences, subject to passing appropriate sequence QC, into the Genomics England data centre. Alignment and variant calling will be performed alongside the potential application of bespoke immunodeficiency panels as part of the Genomics England bioinformatics pipeline analysis.

Genomic data will be released into the Genomics England Trusted Research Environment where it will be linked with associated clinical data.

The GenOMICC study is backed by £28 million from Genomics England, UK Research and Innovation, the Department of Health and Social Care and the National Institute for Health Research. Illumina will sequence all 35,000 genomes and share some of the cost via an in-kind contribution.

A press release on 13/05/20 included a comment from Health and Social Care Secretary Matt Hancock: “As each day passes, we are learning more about this virus, and understanding how genetic makeup may influence how people react to it is a critical piece of the jigsaw.

“This is a ground-breaking and far-reaching study which will harness the UK’s world-leading genomics science to improve treatments and ultimately save lives across the world.” To date, nearly 3000 patients have been recruited into the project.

As of March 2020, the Genomics England Research Environment contained 107,694 genomes, of which, 33,461 were cancer and 74,233 were rare diseases.

The Research environment also contained clinical data on 89,157 participants (this is because cancer participants have two genomes submitted). The clinical data for 17,246 cancer participants includes clinical data from NHS Digital (HES OP/APC/ CC and AE) but also cancer specific data from Public HeaLth England Cancer Registry (NCRAS). The combination of clinical data for all 100,000 participants totals about 5m records.

As the GenOMICC study prospectively recruits participants, the aim will be to use the existing 100,000 participants and age and match-ranked controls for those entered into the study. As Genomics England prospectively enrolls more participants into the study, Genomics England plans further releases of genomic and clinical data, including clinical data received from NHS Digital and viral and host genomic data, into the Research Environment on the following dates, in order to continue support for, and to further develop, this ground-breaking resource:

• 3rd August 2020

• 7th September 2020

• 5th October 2020

• 2nd November 2020

Specific outputs over the period of this agreement are therefore to release updated genomic and clinical data for the 100,000 genomes participants and GenOMICC participants into the Research Environment on the dates shown above.

Yielded Benefits is not a requirement for new applications.