Multimorbidity clusters, trajectories and genetic risk, in British south Asians
Lead Research Organisation:
Queen Mary University of London
Department Name: Blizard Institute of Cell and Molecular
Abstract
Our research proposal covers an important area of health called 'multimorbidity', which describes where an individual is affected by 2 or more health conditions. Studies have shown that multimorbidity is getting more common in the United Kingdom, and the National Health Service does (NHS) not currently have services designed to tackle it well. Recent research has also shown that multimorbidity exists in 'clusters', with groups of common conditions (e.g. type 2 diabetes, high blood pressure, chronic pain, and depression) often co-exist. However, there is a lot still to learn about multimorbidity, and more research is needed to find out why it occurs, who is at risk, and how to design better health and social care to manage it. Our proposal will produce new knowledge that fills some of the important gaps in our understanding of multimorbidity.
We will study multimorbidity in people living in a large east London population of 1.05million people, one-third of whom come from a south Asian ethnic group and who live in high socioeconomic deprivation; both known to be risk factors for multimorbidity. Data collected in electronic health records (e.g. the diagnoses made or treatments given to you when you visit your GP) will be used to inform us about multimorbidity in this population. We will use state-of-the-art statistical techniques that use this data to tell us which are the most common 'clusters' of multimorbidity in east London, and whether they vary in British south Asians compared to Whites. Using historical records, we will study patterns of multimorbidity clusters during a person's life, what risk factors might be associated with them, and how severely they may impact an individual.
The next focus in our research will be to investigate the genetic causes of multimorbidity using cutting edge studies of the genome in volunteers participating in the East London Genes and Health (ELGH) study. ELGH is a large study of people of British-Bangladeshi and -Pakistani origin living in east London, with 32,000 volunteers involved already. Volunteers in ELGH have given consent for us to access their electronic health records and also study their genes using a spit sample donated to the study. We will investigate whether differences in the genetic code of individuals are linked to the risk of multimorbidity. One specific genetic code change we will be looking at is called 'autozygosity', a phenomenon affecting some people in these ethnic groups where parental relatedness is common. Autozygosity increases the chance that gene copies inherited from a person's mother and father are the same, and some studies have shown that this is linked to certain disease. We will study whether the amount of autozygosity in a person's genetic make-up could affect a person's risk of developing multimorbidity. We will also investigate an area of major interest in genetic and health studies at the moment, called polygenic risk scores (PRS). These scores identify multiple, small changes to an individual's genetic code that, when added together using a mathematical formula, strongly predict whether someone is at risk of developing conditions such as heart disease. PRSs have been studied mostly in people of White ethnic groups, and we will contribute to wider efforts to investigate their impact on disease and multimorbidity in south Asians.
Our research will use potentially sensitive data for our studies and we will take very stringent and careful approaches to using this data so that there are no data security issues, and to ensure all data has been collected using appropriate consent and information governance procedures.
We expect that the impact of our research will be wide-ranging, including supporting improvements in health and social care for multimorbidity and perhaps more efficient use of limited NHS funds. We will deliver direct benefits back to our research volunteers through educational programmes and public engagement.
We will study multimorbidity in people living in a large east London population of 1.05million people, one-third of whom come from a south Asian ethnic group and who live in high socioeconomic deprivation; both known to be risk factors for multimorbidity. Data collected in electronic health records (e.g. the diagnoses made or treatments given to you when you visit your GP) will be used to inform us about multimorbidity in this population. We will use state-of-the-art statistical techniques that use this data to tell us which are the most common 'clusters' of multimorbidity in east London, and whether they vary in British south Asians compared to Whites. Using historical records, we will study patterns of multimorbidity clusters during a person's life, what risk factors might be associated with them, and how severely they may impact an individual.
The next focus in our research will be to investigate the genetic causes of multimorbidity using cutting edge studies of the genome in volunteers participating in the East London Genes and Health (ELGH) study. ELGH is a large study of people of British-Bangladeshi and -Pakistani origin living in east London, with 32,000 volunteers involved already. Volunteers in ELGH have given consent for us to access their electronic health records and also study their genes using a spit sample donated to the study. We will investigate whether differences in the genetic code of individuals are linked to the risk of multimorbidity. One specific genetic code change we will be looking at is called 'autozygosity', a phenomenon affecting some people in these ethnic groups where parental relatedness is common. Autozygosity increases the chance that gene copies inherited from a person's mother and father are the same, and some studies have shown that this is linked to certain disease. We will study whether the amount of autozygosity in a person's genetic make-up could affect a person's risk of developing multimorbidity. We will also investigate an area of major interest in genetic and health studies at the moment, called polygenic risk scores (PRS). These scores identify multiple, small changes to an individual's genetic code that, when added together using a mathematical formula, strongly predict whether someone is at risk of developing conditions such as heart disease. PRSs have been studied mostly in people of White ethnic groups, and we will contribute to wider efforts to investigate their impact on disease and multimorbidity in south Asians.
Our research will use potentially sensitive data for our studies and we will take very stringent and careful approaches to using this data so that there are no data security issues, and to ensure all data has been collected using appropriate consent and information governance procedures.
We expect that the impact of our research will be wide-ranging, including supporting improvements in health and social care for multimorbidity and perhaps more efficient use of limited NHS funds. We will deliver direct benefits back to our research volunteers through educational programmes and public engagement.
Technical Summary
Our proposal seeks to deliver new knowledge on multimorbidity, focusing on clustering, trajectories and its potential genetic risk in British South Asians, who are under-represented in research despite disproportionately high morbidity and mortality.
In an unselected, multiethnic, socioeconomically-deprived east London population of 1.05million, we will identify multimorbidity clusters, using exploratory factor analysis in electronic health record (EHR) data. We will investigate how clusters vary between British south Asians (and subgroups) and Whites. Trajectories of multimorbidity will be studied using a longitudinal data using multi-state modelling and survival analyses. We characterise the contribution from known risk factors to these trajectories as well as their ethnic variation.
East London Genes and Health (ELGH) is a community health and genomics study of British-Bangladeshis and -Pakistanis, with target (funded) recruitment of 100,000. Multi-source linked EHR data, exome-sequencing and genotype chip data will be used to study the association between multimorbidity and genetic risk. The possible genome-wide effects of autozygosity (from parental relatedness) on multimorbidity clusters and trajectories will be studied, hypothesising that they may increase the burden of rare homozygous damaging gene variants, and/or increasing additive variance and polygenic disease susceptibility. We will also investigate whether polygenic risk scores (PRSs) for individual traits can be combined to optimise prediction of multimorbid disease, and whether these PRSs for specific diseases and multimorbidity perform as well in south Asian as in White populations. Causal inference studies (e.g. Mendelian randomisation) will be applied where indicated.
Our proposal will deliver impact through the generation of new knowledge readily translatable to clinical care and societal benefit, and focusing on understudied populations.
In an unselected, multiethnic, socioeconomically-deprived east London population of 1.05million, we will identify multimorbidity clusters, using exploratory factor analysis in electronic health record (EHR) data. We will investigate how clusters vary between British south Asians (and subgroups) and Whites. Trajectories of multimorbidity will be studied using a longitudinal data using multi-state modelling and survival analyses. We characterise the contribution from known risk factors to these trajectories as well as their ethnic variation.
East London Genes and Health (ELGH) is a community health and genomics study of British-Bangladeshis and -Pakistanis, with target (funded) recruitment of 100,000. Multi-source linked EHR data, exome-sequencing and genotype chip data will be used to study the association between multimorbidity and genetic risk. The possible genome-wide effects of autozygosity (from parental relatedness) on multimorbidity clusters and trajectories will be studied, hypothesising that they may increase the burden of rare homozygous damaging gene variants, and/or increasing additive variance and polygenic disease susceptibility. We will also investigate whether polygenic risk scores (PRSs) for individual traits can be combined to optimise prediction of multimorbid disease, and whether these PRSs for specific diseases and multimorbidity perform as well in south Asian as in White populations. Causal inference studies (e.g. Mendelian randomisation) will be applied where indicated.
Our proposal will deliver impact through the generation of new knowledge readily translatable to clinical care and societal benefit, and focusing on understudied populations.
Planned Impact
The potential impact of this research are broad, and cover a range of domains, including academic, health policy and economic impact, as well as direct impact on the individuals contributing to the research through public engagement.
Academic impact: this will be achieved through the generation of new interdisciplinary knowledge relating to multimorbidity using electronic health record and genomic data. By studying disease clusters and trajectories using a large, population-based dataset including an under-studied British South Asian population at high risk of multimorbidity, we will generate new insights into who is at risk of multimorbidity and the different paths it follows. Through the combined study of genomic data within the East London Genes and Health subpopulation, we will be able to undertake innovative analysis that links these epidemiological patterns to potentially causal genetic phenomena, including the study of autozygosity and polygenic risk factors in populations. Our work would support large-scale, consortium-based efforts to define transethnic polygenic risk scores, and we would actively participate in these efforts through collaboration and data sharing. Our research will deliver new methodological insights related to the integration of health data science and genomics that could have direct impact to the academic community. We will actively support the training of junior academic researchers. Our findings will support research beyond the research disciplines included in this application, including translational and health services research into multimorbidity.
Economic and societal impact: we will deliver new knowledge on multimorbidity in a large ethnically-diverse and socioeconomically-deprived population at high risk. By using electronic health record data to generate this new knowledge on multimorbidity patterns, our research will support direct and feasible translation back to clinical care in the NHS, e.g. via better risk identification and stratification that could be applied to electronic health records, risk prediction tools and use of data dashboards. We have existing links to Health Data Research UK that we anticipate will help support health data science and its clinical applications within the NHS. Our research team includes clinicians embedded in local health systems (Finer, Hull, van Heel), and this will facilitate knowledge sharing and impact. We will take active steps to disseminate the results of our analyses with healthcare professionals, policymakers and commissioners to guide service improvements. Identification of autozygosity and polygenic risk scores as multimorbidity risk factors could improve clinical care through better genetic counselling to families at risk and identification of risk early in the lifecourse. As such, the research will support policy-level improvements in health care with potential economic impact, e.g. through targeting prevention strategies to those at the highest risk, reducing health inequalities, and the more efficient distribution of funds to models of care that tackle multimorbidity. By setting our research in a British south Asian population, we will be able to contribute to global research efforts on multimorbidity.
Public engagement: ELGH is a community-embedded study that keeps engagement at its core, supported by its ELGH Community Advisory Group, 'Helix Champions' (community researchers) and third sector organisations, e.g. Social Action for Health. This research would continue to support community engagement and health education activities sharing new knowledge amongst ELGH volunteers, their families and the wider east London population. We would continue our innovative engagement activities with the award-winning Centre of the Cell, to deliver educational workshops and interactive web- and app- content based on multimorbidity, polygenic risk and autozygosity.
Academic impact: this will be achieved through the generation of new interdisciplinary knowledge relating to multimorbidity using electronic health record and genomic data. By studying disease clusters and trajectories using a large, population-based dataset including an under-studied British South Asian population at high risk of multimorbidity, we will generate new insights into who is at risk of multimorbidity and the different paths it follows. Through the combined study of genomic data within the East London Genes and Health subpopulation, we will be able to undertake innovative analysis that links these epidemiological patterns to potentially causal genetic phenomena, including the study of autozygosity and polygenic risk factors in populations. Our work would support large-scale, consortium-based efforts to define transethnic polygenic risk scores, and we would actively participate in these efforts through collaboration and data sharing. Our research will deliver new methodological insights related to the integration of health data science and genomics that could have direct impact to the academic community. We will actively support the training of junior academic researchers. Our findings will support research beyond the research disciplines included in this application, including translational and health services research into multimorbidity.
Economic and societal impact: we will deliver new knowledge on multimorbidity in a large ethnically-diverse and socioeconomically-deprived population at high risk. By using electronic health record data to generate this new knowledge on multimorbidity patterns, our research will support direct and feasible translation back to clinical care in the NHS, e.g. via better risk identification and stratification that could be applied to electronic health records, risk prediction tools and use of data dashboards. We have existing links to Health Data Research UK that we anticipate will help support health data science and its clinical applications within the NHS. Our research team includes clinicians embedded in local health systems (Finer, Hull, van Heel), and this will facilitate knowledge sharing and impact. We will take active steps to disseminate the results of our analyses with healthcare professionals, policymakers and commissioners to guide service improvements. Identification of autozygosity and polygenic risk scores as multimorbidity risk factors could improve clinical care through better genetic counselling to families at risk and identification of risk early in the lifecourse. As such, the research will support policy-level improvements in health care with potential economic impact, e.g. through targeting prevention strategies to those at the highest risk, reducing health inequalities, and the more efficient distribution of funds to models of care that tackle multimorbidity. By setting our research in a British south Asian population, we will be able to contribute to global research efforts on multimorbidity.
Public engagement: ELGH is a community-embedded study that keeps engagement at its core, supported by its ELGH Community Advisory Group, 'Helix Champions' (community researchers) and third sector organisations, e.g. Social Action for Health. This research would continue to support community engagement and health education activities sharing new knowledge amongst ELGH volunteers, their families and the wider east London population. We would continue our innovative engagement activities with the award-winning Centre of the Cell, to deliver educational workshops and interactive web- and app- content based on multimorbidity, polygenic risk and autozygosity.
Organisations
- Queen Mary University of London (Lead Research Organisation)
- Council of Scientific and Industrial Research (CSIR) (Collaboration)
- Centre of the Cell (Collaboration)
- Social Action for Health (Collaboration)
- Novo Nordisk (Collaboration)
- Newcastle University (Collaboration)
- Takeda Pharmaceutical Company (Collaboration)
- The Wellcome Trust Sanger Institute (Collaboration)
- National Institute for Health Research (Collaboration)
- UNIVERSITY OF CAMBRIDGE (Collaboration)
- IMPERIAL COLLEGE LONDON (Collaboration)
- UNIVERSITY OF EXETER (Collaboration)
- MERCK (Collaboration)
- UNIVERSITY OF OXFORD (Collaboration)
- AstraZeneca (Collaboration)
- Alan Turing Institute (Collaboration)
- Pfizer Ltd (Collaboration)
- Bristol-Myers Squibb (Collaboration)
- London School of Hygiene and Tropical Medicine (LSHTM) (Collaboration)
- King Edward Memorial Hospital Research Centre (Collaboration)
- GlaxoSmithKline (GSK) (Collaboration)
- Wellcome Sanger Institute (Project Partner)
Publications
Malawsky DS
(2023)
Influence of autozygosity on common disease risk across the phenotypic spectrum.
in Cell
Huang QQ
(2022)
Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistani and Bangladeshi individuals.
in Nature communications
Description | Physical and mental health multimorbidity across the lifespan (LIfespaN multimorbidity research Collaborative (LINC)). |
Amount | £3,034,322 (GBP) |
Funding ID | MR/W014416/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 12/2021 |
End | 11/2025 |
Description | Using artificial intelligence (AI) to characterize the dynamic inter-relationships between MUltiple Long-term condiTIons and PoLYpharmacy and across diverse UK populations and inform health care pathways (AI-MULTIPLY). AIM Research Collaboration |
Amount | £2,971,000 (GBP) |
Funding ID | NIHR 31672 |
Organisation | National Institute for Health Research |
Sector | Public |
Country | United Kingdom |
Start | 04/2022 |
End | 11/2025 |
Title | Genes & Health |
Description | A large resource of genomic and linked electronic health record data on Genes & Health volunteers (currently 54k). |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | Wide academic collaborations and research studies |
URL | http://www.genesandhealth.org |
Title | MULTIPLY long term conditions open access codelist resource |
Description | Most research on multimorbidity, to date, includes a maximum of 30-40 long-term conditions based heavily on the Quality Outcomes Framework in primary care, and seminal papers by, e.g. Barnett et al. We have developed MULTIPLY, a detailed clinical consensus-building exercise to define ~200 conditions for inclusion in multimorbidity studies, particularly suited to data-driven projects using real world data. We have undertaken detailed clinical curation of these codelists (across linked primary and secondary care datasets) using existing codelist resources, e.g. from CPRD, CALIBER and adding our own detailed and structured clinical review. The codelists are interoperable across different primary care software systems. Our MULTIPLY codelists are now available in an open access GitHub (https://github.com/f-eto/MULTIPLY-Initiative) with the following DOI ( https://doi.org/10.5281/zenodo.7643566) |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | Our MULITPLY codelists are already being used by several other large UKRI-funded research studies, including AI-MULTIPLY, LINC multimorbidity and Gene & Health. |
Description | East London Genes and Health (ELGH) |
Organisation | Centre of the Cell |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am deputy lead for this large community genomics study. I contribute towards the overall running of this important study (including recruitment, study design and management, recall-by-genotype, community engagement) which is a large community genomics project of British Bangladeshis and Pakistanis (n=28,000). I am also the local PI for a UK consortium studying type 2 diabetes in this cohort, including running recall-by-genotype studies, analysis of big data (using electronic health records) and the design of future metabolic phenotyping studies. |
Collaborator Contribution | ELGH works with a large international consortium (including academic and industry partners) involved in many of its activities. I am working particularly with a UK-wide consortium of diabetes researchers in recall-by-genotype studies based on rare diabetes and obesity-associated variants. |
Impact | Currently this is work in progress and we are in the recruitment phase to recall-by-genotype studies. We have a broad range of multidisciplinary partnerships involved in our community engagement and outreach activities, including close work with community-based organisations (e.g. https://www.safh.org.uk) and engagement workshops involving anthropologists and experts in public engagement (https://www.centreofthecell.org). |
Start Year | 2017 |
Description | East London Genes and Health (ELGH) |
Organisation | Imperial College London |
Department | Faculty of Medicine |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am deputy lead for this large community genomics study. I contribute towards the overall running of this important study (including recruitment, study design and management, recall-by-genotype, community engagement) which is a large community genomics project of British Bangladeshis and Pakistanis (n=28,000). I am also the local PI for a UK consortium studying type 2 diabetes in this cohort, including running recall-by-genotype studies, analysis of big data (using electronic health records) and the design of future metabolic phenotyping studies. |
Collaborator Contribution | ELGH works with a large international consortium (including academic and industry partners) involved in many of its activities. I am working particularly with a UK-wide consortium of diabetes researchers in recall-by-genotype studies based on rare diabetes and obesity-associated variants. |
Impact | Currently this is work in progress and we are in the recruitment phase to recall-by-genotype studies. We have a broad range of multidisciplinary partnerships involved in our community engagement and outreach activities, including close work with community-based organisations (e.g. https://www.safh.org.uk) and engagement workshops involving anthropologists and experts in public engagement (https://www.centreofthecell.org). |
Start Year | 2017 |
Description | East London Genes and Health (ELGH) |
Organisation | Social Action for Health |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | I am deputy lead for this large community genomics study. I contribute towards the overall running of this important study (including recruitment, study design and management, recall-by-genotype, community engagement) which is a large community genomics project of British Bangladeshis and Pakistanis (n=28,000). I am also the local PI for a UK consortium studying type 2 diabetes in this cohort, including running recall-by-genotype studies, analysis of big data (using electronic health records) and the design of future metabolic phenotyping studies. |
Collaborator Contribution | ELGH works with a large international consortium (including academic and industry partners) involved in many of its activities. I am working particularly with a UK-wide consortium of diabetes researchers in recall-by-genotype studies based on rare diabetes and obesity-associated variants. |
Impact | Currently this is work in progress and we are in the recruitment phase to recall-by-genotype studies. We have a broad range of multidisciplinary partnerships involved in our community engagement and outreach activities, including close work with community-based organisations (e.g. https://www.safh.org.uk) and engagement workshops involving anthropologists and experts in public engagement (https://www.centreofthecell.org). |
Start Year | 2017 |
Description | East London Genes and Health (ELGH) |
Organisation | The Wellcome Trust Sanger Institute |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | I am deputy lead for this large community genomics study. I contribute towards the overall running of this important study (including recruitment, study design and management, recall-by-genotype, community engagement) which is a large community genomics project of British Bangladeshis and Pakistanis (n=28,000). I am also the local PI for a UK consortium studying type 2 diabetes in this cohort, including running recall-by-genotype studies, analysis of big data (using electronic health records) and the design of future metabolic phenotyping studies. |
Collaborator Contribution | ELGH works with a large international consortium (including academic and industry partners) involved in many of its activities. I am working particularly with a UK-wide consortium of diabetes researchers in recall-by-genotype studies based on rare diabetes and obesity-associated variants. |
Impact | Currently this is work in progress and we are in the recruitment phase to recall-by-genotype studies. We have a broad range of multidisciplinary partnerships involved in our community engagement and outreach activities, including close work with community-based organisations (e.g. https://www.safh.org.uk) and engagement workshops involving anthropologists and experts in public engagement (https://www.centreofthecell.org). |
Start Year | 2017 |
Description | East London Genes and Health (ELGH) |
Organisation | University of Exeter |
Department | Medical School |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am deputy lead for this large community genomics study. I contribute towards the overall running of this important study (including recruitment, study design and management, recall-by-genotype, community engagement) which is a large community genomics project of British Bangladeshis and Pakistanis (n=28,000). I am also the local PI for a UK consortium studying type 2 diabetes in this cohort, including running recall-by-genotype studies, analysis of big data (using electronic health records) and the design of future metabolic phenotyping studies. |
Collaborator Contribution | ELGH works with a large international consortium (including academic and industry partners) involved in many of its activities. I am working particularly with a UK-wide consortium of diabetes researchers in recall-by-genotype studies based on rare diabetes and obesity-associated variants. |
Impact | Currently this is work in progress and we are in the recruitment phase to recall-by-genotype studies. We have a broad range of multidisciplinary partnerships involved in our community engagement and outreach activities, including close work with community-based organisations (e.g. https://www.safh.org.uk) and engagement workshops involving anthropologists and experts in public engagement (https://www.centreofthecell.org). |
Start Year | 2017 |
Description | East London Genes and Health (ELGH) |
Organisation | University of Oxford |
Department | Oxford Centre for Diabetes Endocrinology and Metabolism (OCDEM) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am deputy lead for this large community genomics study. I contribute towards the overall running of this important study (including recruitment, study design and management, recall-by-genotype, community engagement) which is a large community genomics project of British Bangladeshis and Pakistanis (n=28,000). I am also the local PI for a UK consortium studying type 2 diabetes in this cohort, including running recall-by-genotype studies, analysis of big data (using electronic health records) and the design of future metabolic phenotyping studies. |
Collaborator Contribution | ELGH works with a large international consortium (including academic and industry partners) involved in many of its activities. I am working particularly with a UK-wide consortium of diabetes researchers in recall-by-genotype studies based on rare diabetes and obesity-associated variants. |
Impact | Currently this is work in progress and we are in the recruitment phase to recall-by-genotype studies. We have a broad range of multidisciplinary partnerships involved in our community engagement and outreach activities, including close work with community-based organisations (e.g. https://www.safh.org.uk) and engagement workshops involving anthropologists and experts in public engagement (https://www.centreofthecell.org). |
Start Year | 2017 |
Description | Genes & Health Life Sciences partnership |
Organisation | AstraZeneca |
Country | United Kingdom |
Sector | Private |
PI Contribution | Delivery of the Genes & Health programme, including (health and genomic) data collection available to external partners. Scientific contributions to health data analysis. |
Collaborator Contribution | Financial contribution - £28million in total from all partners. Scientific contribution to the analysis of genomic and health data |
Impact | Exam sequencing of 50k research volunteers Setup of google cloud trusted research environment |
Start Year | 2022 |
Description | Genes & Health Life Sciences partnership |
Organisation | Bristol-Myers Squibb |
Country | United Kingdom |
Sector | Private |
PI Contribution | Delivery of the Genes & Health programme, including (health and genomic) data collection available to external partners. Scientific contributions to health data analysis. |
Collaborator Contribution | Financial contribution - £28million in total from all partners. Scientific contribution to the analysis of genomic and health data |
Impact | Exam sequencing of 50k research volunteers Setup of google cloud trusted research environment |
Start Year | 2022 |
Description | Genes & Health Life Sciences partnership |
Organisation | GlaxoSmithKline (GSK) |
Department | GlaxoSmithKline, Stevenage |
Country | United Kingdom |
Sector | Private |
PI Contribution | Delivery of the Genes & Health programme, including (health and genomic) data collection available to external partners. Scientific contributions to health data analysis. |
Collaborator Contribution | Financial contribution - £28million in total from all partners. Scientific contribution to the analysis of genomic and health data |
Impact | Exam sequencing of 50k research volunteers Setup of google cloud trusted research environment |
Start Year | 2022 |
Description | Genes & Health Life Sciences partnership |
Organisation | Merck |
Department | Merck Sharp and Dohme Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | Delivery of the Genes & Health programme, including (health and genomic) data collection available to external partners. Scientific contributions to health data analysis. |
Collaborator Contribution | Financial contribution - £28million in total from all partners. Scientific contribution to the analysis of genomic and health data |
Impact | Exam sequencing of 50k research volunteers Setup of google cloud trusted research environment |
Start Year | 2022 |
Description | Genes & Health Life Sciences partnership |
Organisation | Novo Nordisk |
Department | Novo Nordisk Research Centre Oxford |
Country | United Kingdom |
Sector | Private |
PI Contribution | Delivery of the Genes & Health programme, including (health and genomic) data collection available to external partners. Scientific contributions to health data analysis. |
Collaborator Contribution | Financial contribution - £28million in total from all partners. Scientific contribution to the analysis of genomic and health data |
Impact | Exam sequencing of 50k research volunteers Setup of google cloud trusted research environment |
Start Year | 2022 |
Description | Genes & Health Life Sciences partnership |
Organisation | Pfizer Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | Delivery of the Genes & Health programme, including (health and genomic) data collection available to external partners. Scientific contributions to health data analysis. |
Collaborator Contribution | Financial contribution - £28million in total from all partners. Scientific contribution to the analysis of genomic and health data |
Impact | Exam sequencing of 50k research volunteers Setup of google cloud trusted research environment |
Start Year | 2022 |
Description | Genes & Health Life Sciences partnership |
Organisation | Takeda Pharmaceutical Company |
Department | Takeda Pharmaceutical Company Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | Delivery of the Genes & Health programme, including (health and genomic) data collection available to external partners. Scientific contributions to health data analysis. |
Collaborator Contribution | Financial contribution - £28million in total from all partners. Scientific contribution to the analysis of genomic and health data |
Impact | Exam sequencing of 50k research volunteers Setup of google cloud trusted research environment |
Start Year | 2022 |
Description | Genes & Health metabolic research consortium |
Organisation | Council of Scientific and Industrial Research (CSIR) |
Department | Centre for Cellular and Molecular Biology (CCMB) |
Country | India |
Sector | Academic/University |
PI Contribution | I lead a large interdisciplinary research programme, embedded in Genes & Health, that is using interdisciplinary methods to better understand the role of genetics on metabolic health in British south Asians. This work spans rare variant gene discovery (collaborating with Prof Sir Steve O'Rahilly's team in Cambridge) and the generation of ancestry-specific polygenic risk scores for for clinical application. |
Collaborator Contribution | University of Cambridge (Prof Sir Steve O'Rahilly) - rare gene variant discovery, functional characterisation and validation in population based cohorts University of Exeter (Richard Oram, Mike Weedon) - construction and testing of type 1 diabetes polygenic risk scores and its application to studies of diabetes misclassification London School of Hygiene and Tropical Medicine (Rohini Mathur) - advanced epidemiological analysis of real world data in British south Asians Wellcome Trust Sanger Institute (Hilary Martin) - construction and testing of polygenic risks scores KEM Hospital Pune (Ranjan Yajnik) - reference/validation south Asian populations and understanding of phenotype-genotype correlation CSIR (Giriraj Chandak) - GWAS and polygenic risk score generation in south Asian populations |
Impact | 1. Lam BYH*, Williamson A*, Finer S*(*joint first authors), Day F, Tadross JA,Gonçalves Soares A, Wade K, Sweeney P, Bedenbaugh MN, Porter DT, Melvin A, Ellacott KLJ, Lippert RN, Buller S, Rosmaninho-Salgado J, Dowsett GKC, Ridley KE, Xu Z, Cimino I, Rimmington D, Rainbow K, Duckett K, Holmqvist S, Khan A, Dai X, Bochukova EG, Genes & Health Research Team, Trembath RC, Martin HC, Coll AP, Rowitch DH, Wareham NJ, van Heel DA, Timpson N, Simerly RB, Ong KK, Cone, RD, Langenberg C*, Perry JRB*, Yeo GS*, O'Rahilly S*. (2021). MC3R links nutritional state to childhood growth and the timing of puberty. Nature, in press (2020-12-22599D) 2. Mathur R, Hull SA, Hodgson S, Finer S (2021). Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database. British Journal of General Practice. 2022 Feb. https://doi.org/10.3399/BJGP.2021.0508 3. Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022 Feb 26: Epub ahead of print. PMID: 35220425. 4. Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade BW, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, Krishna M, Di Gravio C, Mali ID, Sankareswaran A, Hussain A, Bhowmik BW, Khan AKA, Knight BA, Frayling TM, Finer S, Fall CH, Yajnik CS, Freathy RM, Hitman GA, Chandak GR. Babies of South Asian and European Ancestry Show Similar Associations with Genetic Risk Score for Birth Weight Despite the Smaller Size of South Asian Newborns. Diabetes. 2022 Jan. Epub ahead of print. PMID: 35061033. 5. Hodgson S, Huang Q, Sallah N, Genes & Health Research Team, Griffiths CG, Newman WG, Trembath RC, Lumbers T, Kuchenbaecker K, van Heel DA, Mathur R, Martin H, Finer S (2021) Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting. MedRxiv Preprint (under review with PLoS Medicine) https://www.medrxiv.org/content/10.1101/2021.07.12.21259837v1.full.pdf. |
Start Year | 2020 |
Description | Genes & Health metabolic research consortium |
Organisation | KEM Hospital, Pune |
Country | India |
Sector | Hospitals |
PI Contribution | I lead a large interdisciplinary research programme, embedded in Genes & Health, that is using interdisciplinary methods to better understand the role of genetics on metabolic health in British south Asians. This work spans rare variant gene discovery (collaborating with Prof Sir Steve O'Rahilly's team in Cambridge) and the generation of ancestry-specific polygenic risk scores for for clinical application. |
Collaborator Contribution | University of Cambridge (Prof Sir Steve O'Rahilly) - rare gene variant discovery, functional characterisation and validation in population based cohorts University of Exeter (Richard Oram, Mike Weedon) - construction and testing of type 1 diabetes polygenic risk scores and its application to studies of diabetes misclassification London School of Hygiene and Tropical Medicine (Rohini Mathur) - advanced epidemiological analysis of real world data in British south Asians Wellcome Trust Sanger Institute (Hilary Martin) - construction and testing of polygenic risks scores KEM Hospital Pune (Ranjan Yajnik) - reference/validation south Asian populations and understanding of phenotype-genotype correlation CSIR (Giriraj Chandak) - GWAS and polygenic risk score generation in south Asian populations |
Impact | 1. Lam BYH*, Williamson A*, Finer S*(*joint first authors), Day F, Tadross JA,Gonçalves Soares A, Wade K, Sweeney P, Bedenbaugh MN, Porter DT, Melvin A, Ellacott KLJ, Lippert RN, Buller S, Rosmaninho-Salgado J, Dowsett GKC, Ridley KE, Xu Z, Cimino I, Rimmington D, Rainbow K, Duckett K, Holmqvist S, Khan A, Dai X, Bochukova EG, Genes & Health Research Team, Trembath RC, Martin HC, Coll AP, Rowitch DH, Wareham NJ, van Heel DA, Timpson N, Simerly RB, Ong KK, Cone, RD, Langenberg C*, Perry JRB*, Yeo GS*, O'Rahilly S*. (2021). MC3R links nutritional state to childhood growth and the timing of puberty. Nature, in press (2020-12-22599D) 2. Mathur R, Hull SA, Hodgson S, Finer S (2021). Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database. British Journal of General Practice. 2022 Feb. https://doi.org/10.3399/BJGP.2021.0508 3. Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022 Feb 26: Epub ahead of print. PMID: 35220425. 4. Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade BW, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, Krishna M, Di Gravio C, Mali ID, Sankareswaran A, Hussain A, Bhowmik BW, Khan AKA, Knight BA, Frayling TM, Finer S, Fall CH, Yajnik CS, Freathy RM, Hitman GA, Chandak GR. Babies of South Asian and European Ancestry Show Similar Associations with Genetic Risk Score for Birth Weight Despite the Smaller Size of South Asian Newborns. Diabetes. 2022 Jan. Epub ahead of print. PMID: 35061033. 5. Hodgson S, Huang Q, Sallah N, Genes & Health Research Team, Griffiths CG, Newman WG, Trembath RC, Lumbers T, Kuchenbaecker K, van Heel DA, Mathur R, Martin H, Finer S (2021) Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting. MedRxiv Preprint (under review with PLoS Medicine) https://www.medrxiv.org/content/10.1101/2021.07.12.21259837v1.full.pdf. |
Start Year | 2020 |
Description | Genes & Health metabolic research consortium |
Organisation | London School of Hygiene and Tropical Medicine (LSHTM) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I lead a large interdisciplinary research programme, embedded in Genes & Health, that is using interdisciplinary methods to better understand the role of genetics on metabolic health in British south Asians. This work spans rare variant gene discovery (collaborating with Prof Sir Steve O'Rahilly's team in Cambridge) and the generation of ancestry-specific polygenic risk scores for for clinical application. |
Collaborator Contribution | University of Cambridge (Prof Sir Steve O'Rahilly) - rare gene variant discovery, functional characterisation and validation in population based cohorts University of Exeter (Richard Oram, Mike Weedon) - construction and testing of type 1 diabetes polygenic risk scores and its application to studies of diabetes misclassification London School of Hygiene and Tropical Medicine (Rohini Mathur) - advanced epidemiological analysis of real world data in British south Asians Wellcome Trust Sanger Institute (Hilary Martin) - construction and testing of polygenic risks scores KEM Hospital Pune (Ranjan Yajnik) - reference/validation south Asian populations and understanding of phenotype-genotype correlation CSIR (Giriraj Chandak) - GWAS and polygenic risk score generation in south Asian populations |
Impact | 1. Lam BYH*, Williamson A*, Finer S*(*joint first authors), Day F, Tadross JA,Gonçalves Soares A, Wade K, Sweeney P, Bedenbaugh MN, Porter DT, Melvin A, Ellacott KLJ, Lippert RN, Buller S, Rosmaninho-Salgado J, Dowsett GKC, Ridley KE, Xu Z, Cimino I, Rimmington D, Rainbow K, Duckett K, Holmqvist S, Khan A, Dai X, Bochukova EG, Genes & Health Research Team, Trembath RC, Martin HC, Coll AP, Rowitch DH, Wareham NJ, van Heel DA, Timpson N, Simerly RB, Ong KK, Cone, RD, Langenberg C*, Perry JRB*, Yeo GS*, O'Rahilly S*. (2021). MC3R links nutritional state to childhood growth and the timing of puberty. Nature, in press (2020-12-22599D) 2. Mathur R, Hull SA, Hodgson S, Finer S (2021). Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database. British Journal of General Practice. 2022 Feb. https://doi.org/10.3399/BJGP.2021.0508 3. Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022 Feb 26: Epub ahead of print. PMID: 35220425. 4. Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade BW, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, Krishna M, Di Gravio C, Mali ID, Sankareswaran A, Hussain A, Bhowmik BW, Khan AKA, Knight BA, Frayling TM, Finer S, Fall CH, Yajnik CS, Freathy RM, Hitman GA, Chandak GR. Babies of South Asian and European Ancestry Show Similar Associations with Genetic Risk Score for Birth Weight Despite the Smaller Size of South Asian Newborns. Diabetes. 2022 Jan. Epub ahead of print. PMID: 35061033. 5. Hodgson S, Huang Q, Sallah N, Genes & Health Research Team, Griffiths CG, Newman WG, Trembath RC, Lumbers T, Kuchenbaecker K, van Heel DA, Mathur R, Martin H, Finer S (2021) Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting. MedRxiv Preprint (under review with PLoS Medicine) https://www.medrxiv.org/content/10.1101/2021.07.12.21259837v1.full.pdf. |
Start Year | 2020 |
Description | Genes & Health metabolic research consortium |
Organisation | The Wellcome Trust Sanger Institute |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | I lead a large interdisciplinary research programme, embedded in Genes & Health, that is using interdisciplinary methods to better understand the role of genetics on metabolic health in British south Asians. This work spans rare variant gene discovery (collaborating with Prof Sir Steve O'Rahilly's team in Cambridge) and the generation of ancestry-specific polygenic risk scores for for clinical application. |
Collaborator Contribution | University of Cambridge (Prof Sir Steve O'Rahilly) - rare gene variant discovery, functional characterisation and validation in population based cohorts University of Exeter (Richard Oram, Mike Weedon) - construction and testing of type 1 diabetes polygenic risk scores and its application to studies of diabetes misclassification London School of Hygiene and Tropical Medicine (Rohini Mathur) - advanced epidemiological analysis of real world data in British south Asians Wellcome Trust Sanger Institute (Hilary Martin) - construction and testing of polygenic risks scores KEM Hospital Pune (Ranjan Yajnik) - reference/validation south Asian populations and understanding of phenotype-genotype correlation CSIR (Giriraj Chandak) - GWAS and polygenic risk score generation in south Asian populations |
Impact | 1. Lam BYH*, Williamson A*, Finer S*(*joint first authors), Day F, Tadross JA,Gonçalves Soares A, Wade K, Sweeney P, Bedenbaugh MN, Porter DT, Melvin A, Ellacott KLJ, Lippert RN, Buller S, Rosmaninho-Salgado J, Dowsett GKC, Ridley KE, Xu Z, Cimino I, Rimmington D, Rainbow K, Duckett K, Holmqvist S, Khan A, Dai X, Bochukova EG, Genes & Health Research Team, Trembath RC, Martin HC, Coll AP, Rowitch DH, Wareham NJ, van Heel DA, Timpson N, Simerly RB, Ong KK, Cone, RD, Langenberg C*, Perry JRB*, Yeo GS*, O'Rahilly S*. (2021). MC3R links nutritional state to childhood growth and the timing of puberty. Nature, in press (2020-12-22599D) 2. Mathur R, Hull SA, Hodgson S, Finer S (2021). Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database. British Journal of General Practice. 2022 Feb. https://doi.org/10.3399/BJGP.2021.0508 3. Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022 Feb 26: Epub ahead of print. PMID: 35220425. 4. Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade BW, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, Krishna M, Di Gravio C, Mali ID, Sankareswaran A, Hussain A, Bhowmik BW, Khan AKA, Knight BA, Frayling TM, Finer S, Fall CH, Yajnik CS, Freathy RM, Hitman GA, Chandak GR. Babies of South Asian and European Ancestry Show Similar Associations with Genetic Risk Score for Birth Weight Despite the Smaller Size of South Asian Newborns. Diabetes. 2022 Jan. Epub ahead of print. PMID: 35061033. 5. Hodgson S, Huang Q, Sallah N, Genes & Health Research Team, Griffiths CG, Newman WG, Trembath RC, Lumbers T, Kuchenbaecker K, van Heel DA, Mathur R, Martin H, Finer S (2021) Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting. MedRxiv Preprint (under review with PLoS Medicine) https://www.medrxiv.org/content/10.1101/2021.07.12.21259837v1.full.pdf. |
Start Year | 2020 |
Description | Genes & Health metabolic research consortium |
Organisation | University of Cambridge |
Department | Metabolic Research Laboratories |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I lead a large interdisciplinary research programme, embedded in Genes & Health, that is using interdisciplinary methods to better understand the role of genetics on metabolic health in British south Asians. This work spans rare variant gene discovery (collaborating with Prof Sir Steve O'Rahilly's team in Cambridge) and the generation of ancestry-specific polygenic risk scores for for clinical application. |
Collaborator Contribution | University of Cambridge (Prof Sir Steve O'Rahilly) - rare gene variant discovery, functional characterisation and validation in population based cohorts University of Exeter (Richard Oram, Mike Weedon) - construction and testing of type 1 diabetes polygenic risk scores and its application to studies of diabetes misclassification London School of Hygiene and Tropical Medicine (Rohini Mathur) - advanced epidemiological analysis of real world data in British south Asians Wellcome Trust Sanger Institute (Hilary Martin) - construction and testing of polygenic risks scores KEM Hospital Pune (Ranjan Yajnik) - reference/validation south Asian populations and understanding of phenotype-genotype correlation CSIR (Giriraj Chandak) - GWAS and polygenic risk score generation in south Asian populations |
Impact | 1. Lam BYH*, Williamson A*, Finer S*(*joint first authors), Day F, Tadross JA,Gonçalves Soares A, Wade K, Sweeney P, Bedenbaugh MN, Porter DT, Melvin A, Ellacott KLJ, Lippert RN, Buller S, Rosmaninho-Salgado J, Dowsett GKC, Ridley KE, Xu Z, Cimino I, Rimmington D, Rainbow K, Duckett K, Holmqvist S, Khan A, Dai X, Bochukova EG, Genes & Health Research Team, Trembath RC, Martin HC, Coll AP, Rowitch DH, Wareham NJ, van Heel DA, Timpson N, Simerly RB, Ong KK, Cone, RD, Langenberg C*, Perry JRB*, Yeo GS*, O'Rahilly S*. (2021). MC3R links nutritional state to childhood growth and the timing of puberty. Nature, in press (2020-12-22599D) 2. Mathur R, Hull SA, Hodgson S, Finer S (2021). Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database. British Journal of General Practice. 2022 Feb. https://doi.org/10.3399/BJGP.2021.0508 3. Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022 Feb 26: Epub ahead of print. PMID: 35220425. 4. Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade BW, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, Krishna M, Di Gravio C, Mali ID, Sankareswaran A, Hussain A, Bhowmik BW, Khan AKA, Knight BA, Frayling TM, Finer S, Fall CH, Yajnik CS, Freathy RM, Hitman GA, Chandak GR. Babies of South Asian and European Ancestry Show Similar Associations with Genetic Risk Score for Birth Weight Despite the Smaller Size of South Asian Newborns. Diabetes. 2022 Jan. Epub ahead of print. PMID: 35061033. 5. Hodgson S, Huang Q, Sallah N, Genes & Health Research Team, Griffiths CG, Newman WG, Trembath RC, Lumbers T, Kuchenbaecker K, van Heel DA, Mathur R, Martin H, Finer S (2021) Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting. MedRxiv Preprint (under review with PLoS Medicine) https://www.medrxiv.org/content/10.1101/2021.07.12.21259837v1.full.pdf. |
Start Year | 2020 |
Description | Genes & Health metabolic research consortium |
Organisation | University of Exeter |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I lead a large interdisciplinary research programme, embedded in Genes & Health, that is using interdisciplinary methods to better understand the role of genetics on metabolic health in British south Asians. This work spans rare variant gene discovery (collaborating with Prof Sir Steve O'Rahilly's team in Cambridge) and the generation of ancestry-specific polygenic risk scores for for clinical application. |
Collaborator Contribution | University of Cambridge (Prof Sir Steve O'Rahilly) - rare gene variant discovery, functional characterisation and validation in population based cohorts University of Exeter (Richard Oram, Mike Weedon) - construction and testing of type 1 diabetes polygenic risk scores and its application to studies of diabetes misclassification London School of Hygiene and Tropical Medicine (Rohini Mathur) - advanced epidemiological analysis of real world data in British south Asians Wellcome Trust Sanger Institute (Hilary Martin) - construction and testing of polygenic risks scores KEM Hospital Pune (Ranjan Yajnik) - reference/validation south Asian populations and understanding of phenotype-genotype correlation CSIR (Giriraj Chandak) - GWAS and polygenic risk score generation in south Asian populations |
Impact | 1. Lam BYH*, Williamson A*, Finer S*(*joint first authors), Day F, Tadross JA,Gonçalves Soares A, Wade K, Sweeney P, Bedenbaugh MN, Porter DT, Melvin A, Ellacott KLJ, Lippert RN, Buller S, Rosmaninho-Salgado J, Dowsett GKC, Ridley KE, Xu Z, Cimino I, Rimmington D, Rainbow K, Duckett K, Holmqvist S, Khan A, Dai X, Bochukova EG, Genes & Health Research Team, Trembath RC, Martin HC, Coll AP, Rowitch DH, Wareham NJ, van Heel DA, Timpson N, Simerly RB, Ong KK, Cone, RD, Langenberg C*, Perry JRB*, Yeo GS*, O'Rahilly S*. (2021). MC3R links nutritional state to childhood growth and the timing of puberty. Nature, in press (2020-12-22599D) 2. Mathur R, Hull SA, Hodgson S, Finer S (2021). Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database. British Journal of General Practice. 2022 Feb. https://doi.org/10.3399/BJGP.2021.0508 3. Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, Beaumont RN, Canouil M, Hatem G, Heiskala A, Joensuu A, Karhunen V, Kwak SH, Lin FTJ, Liu J, Rifas-Shiman S, Tam CH, Tam WH, Thorleifsson G, Andrew T, Auvinen J, Bhowmik B, Bonnefond A, Delahaye F, Demirkan A, Froguel P, Haller-Kikkatalo K, Hardardottir H, Hummel S, Hussain A, Kajantie E, Keikkala E, Khamis A, Lahti J, Lekva T, Mustaniemi S, Sommer C, Tagoma A, Tzala E, Uibo R, Vääräsmäki M, Villa PM, Birkeland KI, Bouchard L, Duijn CM, Finer S, Groop L, Hämäläinen E, Hayes GM, Hitman GA, Jang HC, Järvelin MR, Jenum AK, Laivuori H, Ma RC, Melander O, Oken E, Park KS, Perron P, Prasad RB, Qvigstad E, Sebert S, Stefansson K, Steinthorsdottir V, Tuomi T, Hivert MF, Franks PW, McCarthy MI, Lindgren CM, Freathy RM, Lawlor DA, Morris AP, Mägi R. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022 Feb 26: Epub ahead of print. PMID: 35220425. 4. Nongmaithem SS, Beaumont RN, Dedaniya A, Wood AR, Ogunkolade BW, Hassan Z, Krishnaveni GV, Kumaran K, Potdar RD, Sahariah SA, Krishna M, Di Gravio C, Mali ID, Sankareswaran A, Hussain A, Bhowmik BW, Khan AKA, Knight BA, Frayling TM, Finer S, Fall CH, Yajnik CS, Freathy RM, Hitman GA, Chandak GR. Babies of South Asian and European Ancestry Show Similar Associations with Genetic Risk Score for Birth Weight Despite the Smaller Size of South Asian Newborns. Diabetes. 2022 Jan. Epub ahead of print. PMID: 35061033. 5. Hodgson S, Huang Q, Sallah N, Genes & Health Research Team, Griffiths CG, Newman WG, Trembath RC, Lumbers T, Kuchenbaecker K, van Heel DA, Mathur R, Martin H, Finer S (2021) Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting. MedRxiv Preprint (under review with PLoS Medicine) https://www.medrxiv.org/content/10.1101/2021.07.12.21259837v1.full.pdf. |
Start Year | 2020 |
Description | NIHR AiM Development Award (NIHR202635) |
Organisation | Newcastle University |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Characterising the dynamic inter-relationships between polypharmacy and multiple long-term conditions. Using artificial intelligence (AI) to map patient journeys into multimorbidity clusters across the UK This is a recently awarded development grant awarded by NIHR, on which I am Co-Investigator. This NIHR grant is integrating with my Multimorbidity clusters, trajectories and genetic risk, in British south Asians award, using common methodology to define conditions for inclusion in a data-driven multimorbidity cluster analysis. The two grants are complementary, and synergistic - the MRC award generating outputs primarily on ethnicity-associated variation and genetic aetiology of multimorbidity, and the NIHR award developing an AI infrastructure to expand the scope of analyses and investigate the complex and dynamic relationship between multimorbidity and polypharmacy. |
Collaborator Contribution | The partnership has led to the successful NIHR award, and is contributing additional datasets (UK Biobank) and methodology (AI). |
Impact | Further grant funding: NIHR. "Using artificial intelligence (AI) to characterize the dynamic inter-relationships between MUltiple Long-term condiTIons and PoLYpharmacy and across diverse UK populations and inform health care pathways (AI-MULTIPLY)". AIM Research Collaboration. NIHR 31672. April 2022-November 2025, £2,971,000. I am Co-Investigator and Work Package Lead |
Start Year | 2021 |
Description | NIHR North Thames Applied Research Collaborative |
Organisation | National Institute for Health Research |
Department | NIHR CLAHRC North Thames |
Country | United Kingdom |
Sector | Private |
PI Contribution | Input into the multimorbidity theme at the NIHR ARC, contributing ideas and suggestions to other researchers studying multimorbidity, and building strategic direction and expertise collaboratively. |
Collaborator Contribution | Providing strategic direction and collaborative expertise on multimorbidity. PPI support |
Impact | None yet |
Start Year | 2020 |
Description | Turing AIM (AI for Multiple long-term conditions) Research Support Facility |
Organisation | Alan Turing Institute |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Scientific and clinical subject knowledge and methodological expertise |
Collaborator Contribution | Methodological expertise |
Impact | Nil yet |
Start Year | 2022 |
Description | QMUL Festival of Communities |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Public/other audiences |
Results and Impact | Participation in a large community festival based in Tower Hamlets, attended by over 7,000 people |
Year(s) Of Engagement Activity | 2022 |
URL | https://www.qmul.ac.uk/festival/about/2022/ |