Molecules to Health Records
Lead Research Organisation:
Health Data Research UK
Department Name: UNLISTED
Abstract
Bringing together different types of information about patients and their diseases can lead to new ways to predict those at risk of getting them, prevent them from happening, detect them earlier to improve outcomes, and find new ways to treat them.
This programme will develop the new tools and science needed to bring together complex information from health records across the UK and beyond, together with genetic information and other detailed understandings of what changes are causing diseases to unlock these opportunities to improve the health and wellbeing of patients and the public.
This programme will develop the new tools and science needed to bring together complex information from health records across the UK and beyond, together with genetic information and other detailed understandings of what changes are causing diseases to unlock these opportunities to improve the health and wellbeing of patients and the public.
Technical Summary
This work is funded by the UKRI Medical Research Council, UKRI Engineering and Physical Sciences Research Council, UKRI Economic and Social Research Council, Department of Health and Social Care, National Institute for Health Research (England), Chief Scientist Office (Scottish Government), Health and Care Research Wales, Public Health Agency HSC (Northern Ireland), British Heart Foundation and Cancer Research UK
The programme’s vision is to create new informatics infrastructures and data science methods that help achieve a deep integration of biology, biomedicine and population health sciences to gain major new insights into the underlying causes and biology of diseases by bringing together on a grand scale multimodal information on genomics, other molecular traits, and high-resolution electronic health records (EHRs). The ‘Molecules to Health Records’ approach will help unlock the potential of major global investments in large-scale molecular bioresources of populations and patients.
Objectives
The priority areas of focus include:
1. Molecular underpinnings of multi-disease aetiology, aligned with the strategic aims of the Medical Research Council (MRC) and National Institute for Health Research (NIHR).
2. Therapeutic target prioritisation, aligned with the MRC’s strategic aim to enhance therapeutic target validation and promote collaboration with industry across both common and rare diseases.
3. Genomic causes of rare disorders, aligned with the UK Strategy for Rare Diseases and Genome UK.
4. Risk prediction and stratified prevention, aligned with MRC and the UK Prevention Research Partnership’s and Genome UK’s strategic aim to enhance prevention and early detection of common diseases.
Impact and legacy
This programme’s distinctive contribution is, therefore, to help develop approaches and infrastructuresthat realise novel insights from EHR-enabled bioresources, working across cohorts to maximise scale, synergy and diversity. This proposal aims to seize opportunities that HDR UK is uniquely positioned to deliver, and achieve a balance of risk and reward, scale and agility, infrastructure development and tangible research outputs. This programme will contribute to HDR UK’s key cross-cutting ambitions, including addressing inequalities (e.g., through creation of genomic medicine tools in diverse non-European populations), developing synergistic approaches to disease prevention (e.g., through multi-omic studies of multi-disease aetiology), and promoting resilience against future health shocks (e.g., through mobilisation and multipurpose use of global populations cohorts for communicable and non-communicable disease epidemiology).
The programme’s vision is to create new informatics infrastructures and data science methods that help achieve a deep integration of biology, biomedicine and population health sciences to gain major new insights into the underlying causes and biology of diseases by bringing together on a grand scale multimodal information on genomics, other molecular traits, and high-resolution electronic health records (EHRs). The ‘Molecules to Health Records’ approach will help unlock the potential of major global investments in large-scale molecular bioresources of populations and patients.
Objectives
The priority areas of focus include:
1. Molecular underpinnings of multi-disease aetiology, aligned with the strategic aims of the Medical Research Council (MRC) and National Institute for Health Research (NIHR).
2. Therapeutic target prioritisation, aligned with the MRC’s strategic aim to enhance therapeutic target validation and promote collaboration with industry across both common and rare diseases.
3. Genomic causes of rare disorders, aligned with the UK Strategy for Rare Diseases and Genome UK.
4. Risk prediction and stratified prevention, aligned with MRC and the UK Prevention Research Partnership’s and Genome UK’s strategic aim to enhance prevention and early detection of common diseases.
Impact and legacy
This programme’s distinctive contribution is, therefore, to help develop approaches and infrastructuresthat realise novel insights from EHR-enabled bioresources, working across cohorts to maximise scale, synergy and diversity. This proposal aims to seize opportunities that HDR UK is uniquely positioned to deliver, and achieve a balance of risk and reward, scale and agility, infrastructure development and tangible research outputs. This programme will contribute to HDR UK’s key cross-cutting ambitions, including addressing inequalities (e.g., through creation of genomic medicine tools in diverse non-European populations), developing synergistic approaches to disease prevention (e.g., through multi-omic studies of multi-disease aetiology), and promoting resilience against future health shocks (e.g., through mobilisation and multipurpose use of global populations cohorts for communicable and non-communicable disease epidemiology).
Organisations
Publications
Marx N
(2023)
2023 ESC Guidelines for the management of cardiovascular disease in patients with diabetes.
in European heart journal
Akbari P
(2023)
A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.
in Nature communications
Patel AP
(2023)
A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease.
in Nature medicine
Pennells L
(2024)
Adapting cardiovascular risk prediction models to different populations: the need for recalibration
in European Heart Journal
Tschiderer L
(2023)
Age at Menopause and the Risk of Stroke: Observational and Mendelian Randomization Analysis in 204 244 Postmenopausal Women.
in Journal of the American Heart Association
Jiang X
(2023)
Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk.
in Nature genetics
Aung N
(2023)
Association of Longer Leukocyte Telomere Length With Cardiac Size, Function, and Heart Failure.
in JAMA cardiology
Zhu J
(2024)
Associations between genetically predicted plasma protein levels and Alzheimer's disease risk: a study using genetic prediction models.
in Alzheimer's research & therapy
Zhao S
(2023)
Associations between vitamin D and autoimmune diseases: Mendelian randomization analysis
in Seminars in Arthritis and Rheumatism