Multimorbidity Mechanism and Therapeutics Research Collaborative
Lead Research Organisation:
University College London
Department Name: Institute of Cardiovascular Science
Abstract
As people live to a greater age there is an increased risk of suffering more than one health condition at a time. Known as multimorbidity this has a serious effect on the daily lives of patients, their families and their carers. The project will examine the sequence and patterns of multimorbidity and the evidence obtained will aid both the prediction and treatment of patients with multiple health conditions. We will also seek to address the problem of coordinating treatments so that treatment for one condition does not cause difficulties in the treatment of another condition suffered by the same patient. The frequency of this "competition" between health conditions will be established and solutions identified. In doing this we hope to identify medicines that are able to treat more than one condition and investigate the potential of new uses for existing safe medicines.
Our research will utilise anonymous patient data recorded by the NHS as well as the findings from existing genetic studies and clinical trials. We will look across the different types of evidence to check consistency to ensure our recommendations are sound. Where uncertainties remain we will recommend new clinical trials or genetic studies. In this way we hope to improve the outlook for patients, regardless of their particular combination of health conditions, by maximising the benefits from effective treatments.
Two patient participants are co-applicants on this project. A Patient and Public Advisory Group will be established which will also assist in ensuring that the findings from the project are widely disseminated. During the course of our work we will liaise with organisations such as the Coalition for Collaborative Care with a view to the establishment of a national Multimorbidity Special Interest Group.
Our research will utilise anonymous patient data recorded by the NHS as well as the findings from existing genetic studies and clinical trials. We will look across the different types of evidence to check consistency to ensure our recommendations are sound. Where uncertainties remain we will recommend new clinical trials or genetic studies. In this way we hope to improve the outlook for patients, regardless of their particular combination of health conditions, by maximising the benefits from effective treatments.
Two patient participants are co-applicants on this project. A Patient and Public Advisory Group will be established which will also assist in ensuring that the findings from the project are widely disseminated. During the course of our work we will liaise with organisations such as the Coalition for Collaborative Care with a view to the establishment of a national Multimorbidity Special Interest Group.
Technical Summary
Our research will uncover mechanisms underlying multimorbidity by triangulating relationships between medicines, drug targets and disease outcomes from electronic health records (EHRs), genetic association studies and trials. The findings will maximise treatment benefits by guiding drug indication expansion and re-purposing; reduce harm by optimising prescribing when diseases co-exist; and yield new tools for prediction and prevention of multi-morbidity.
Organisations
- University College London (Lead Research Organisation)
- Amsterdam Medical Center (Collaboration)
- UNIVERSITY OF LEICESTER (Collaboration)
- ST GEORGE'S UNIVERSITY OF LONDON (Collaboration)
- University of Bristol (Collaboration)
- UNIVERSITY OF EXETER (Collaboration)
- UNIVERSITY HOSPITALS BIRMINGHAM NHS FOUNDATION TRUST (Collaboration)
Publications
Denaxas S
(2021)
Mapping the Read2/CTV3 controlled clinical terminologies to Phecodes in UK Biobank primary care electronic health records: implementation and evaluation.
in AMIA ... Annual Symposium proceedings. AMIA Symposium
Lai AG
(2021)
An informatics consult approach for generating clinical evidence for treatment decisions.
in BMC medical informatics and decision making
Gordillo-Marañón M
(2021)
Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics.
in Nature communications
Pietzner M
(2021)
Synergistic insights into human health from aptamer- and antibody-based proteomic profiling.
in Nature communications
Pietzner M
(2021)
Mapping the proteo-genomic convergence of human diseases.
in Science (New York, N.Y.)
Schmidt AF
(2021)
Cholesteryl ester transfer protein (CETP) as a drug target for cardiovascular disease.
in Nature communications
Fraser H
(2022)
Biological mechanisms of aging predict age-related disease co-occurrence in patients
in Aging Cell
Henry A
(2022)
Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization.
in Circulation
Schmidt AF
(2022)
Human Genomics and Drug Development.
in Cold Spring Harbor perspectives in medicine
Borges MC
(2022)
The impact of fatty acids biosynthesis on the risk of cardiovascular diseases in Europeans and East Asians: a Mendelian randomization study.
in Human molecular genetics
Asiimwe IG
(2022)
Drug-Drug-Gene Interactions in Cardiovascular Medicine.
in Pharmacogenomics and personalized medicine
Cupido AJ
(2022)
Joint Genetic Inhibition of PCSK9 and CETP and the Association With Coronary Artery Disease: A Factorial Mendelian Randomization Study.
in JAMA cardiology
Patel RS
(2022)
Elevated plasma triglyceride concentration and risk of adverse clinical outcomes in 1.5 million people: a CALIBER linked electronic health record study.
in Cardiovascular diabetology
Kivimäki M
(2022)
Comment on "A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk".
in Science translational medicine
Patel RS
(2022)
Reproducible disease phenotyping at scale: Example of coronary artery disease in UK Biobank.
in PloS one
Sanghvi S
(2023)
How to assess pharmacogenomic tests for implementation in the NHS in England.
in British journal of clinical pharmacology
Schmidt AF
(2023)
Genetic evidence for serum amyloid P component as a drug target for treatment of neurodegenerative disorders.
in medRxiv : the preprint server for health sciences
Koprulu M
(2023)
Proteogenomic links to human metabolic diseases.
in Nature metabolism
Schmidt AF
(2023)
Biomedical consequences of elevated cholesterol-containing lipoproteins and apolipoproteins on cardiovascular and non-cardiovascular outcomes.
in Communications medicine
Langenberg C
(2023)
Biological and functional multimorbidity-from mechanisms to management.
in Nature medicine
Schmidt AF
(2023)
Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity.
in Science advances
Hartmann S
(2023)
ADRA2A and IRX1 are putative risk genes for Raynaud's phenomenon.
in Nature communications
Kuan V
(2023)
Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study.
in The Lancet. Digital health
Hamilton FW
(2023)
Therapeutic potential of IL6R blockade for the treatment of sepsis and sepsis-related death: A Mendelian randomisation study.
in PLoS medicine
Huntley C
(2023)
Utility of polygenic risk scores in UK cancer screening: a modelling analysis.
in The Lancet. Oncology
Asiimwe I
(2024)
Genetic Determinants of Thiazide-Induced Hyperuricemia, Hyperglycemia, and Urinary Electrolyte Disturbances - A Genome-Wide Evaluation of the UK Biobank
in Clinical Pharmacology & Therapeutics
Asiimwe I
(2024)
CYP3A4*22 and bleeding risk in ticagrelor users
in Basic & Clinical Pharmacology & Toxicology
Title | Should you donate your DNA to cure diseases? |
Description | TED Ed animation with Greg Foot |
Type Of Art | Film/Video/Animation |
Year Produced | 2021 |
Impact | 158,000 you tube views |
Description | University College London Biomedical Research Centre |
Amount | £90,186,915 (GBP) |
Funding ID | NIHR203328 |
Organisation | National Institute for Health Research |
Sector | Public |
Country | United Kingdom |
Start | 12/2022 |
End | 11/2027 |
Description | Welcome Trust Collaborative Award 'Prediction of complications of diabetes mellitus utilising novel retinal image analysis, genetics, and linked electronic health records data.' |
Amount | £1,126,103 (GBP) |
Funding ID | 224390/Z/21/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2022 |
End | 03/2026 |
Title | Look up tool based on analyses of disease co-occurrence from Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study published in Lancet Digital Health 2023 |
Description | An R shiny app to visualise and quantify multimorbidity and comorbidity frequencies and networks. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2023 |
Provided To Others? | Yes |
Impact | 2 citations - 1 featuring the paper in Cell Reports Medicine 6 news mentions 112 social media 3 - wikipedia references -"Electronic health record', 'Global health', '2022 in science' |
URL | https://multimorbidity.caliberresearch.org/ |
Title | Look up tool based on summary statistics from Mapping the proteo-genomic convergence of human diseases paper in Science. 2021 Nov 12; 374(6569): eabj1541. |
Description | A tool to identify protein disease associations through genome wide colocalisation analysis. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | 23,000 downloads of the paper 23 citations |
URL | https://pubmed.ncbi.nlm.nih.gov/34648354/ |
Title | Mapping the proteogenomic convergence of human disease search tool |
Description | A tool to visualise gene and protein relationships across multiple diseases. |
Type Of Material | Model of mechanisms or symptoms - human |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | Widespread interest from the science community and general audience. Altmetric score 520. |
URL | https://www.science.org/doi/10.1126/science.abj1541 |
Title | Derivation of relevant metrics to assess the performance of polygenic risk scores from reported metrics. |
Description | Secondary analysis of the PGS Catalog. |
Type Of Material | Data analysis technique |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | Awaited |
Description | Collaboration with Bristol, Birmingham, Liverpool, and Cambridge as part of the Multimorbidity Mechanism and Therapeutics Research Collaborative |
Organisation | University Hospitals Birmingham NHS Foundation Trust |
Country | United Kingdom |
Sector | Public |
PI Contribution | Led the application for funding and coordination of the award |
Collaborator Contribution | Topic specific expertise |
Impact | Detailed elsewhere |
Start Year | 2021 |
Description | Collaboration with Bristol, Birmingham, Liverpool, and Cambridge as part of the Multimorbidity Mechanism and Therapeutics Research Collaborative |
Organisation | University of Bristol |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Led the application to UKRI for the award. Co-ordinate the collaborative |
Collaborator Contribution | Contribution to specific work packages and interdisciplinary working. |
Impact | Publications listed elsewhere |
Start Year | 2021 |
Description | Collaboration with Exeter in an application to UKRI for a clinical community of practice grant |
Organisation | University of Exeter |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Support of the MMTRC |
Collaborator Contribution | Leading the application |
Impact | None yet |
Start Year | 2022 |
Description | Collaboration with Leicester in an application to UKRI for funding for a community of practice grant in statistical genetics |
Organisation | University of Leicester |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | One of the ECRs in the MMTRC collaborative is a co-applicant |
Collaborator Contribution | Leicester are leading |
Impact | None yet |
Start Year | 2022 |
Description | Collaboration with Professor Nick Wald and Joan Morris |
Organisation | St George's University of London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Developed the idea of converting reported metrics on performance of polygenic scores into metrics most relevant for prediction |
Collaborator Contribution | Developed the underlying statistical methods |
Impact | Pre print in MedRxiv Paper under review in Communications Medicine |
Start Year | 2021 |
Description | Collaboration with University Medical Centre Amsterdam |
Organisation | Amsterdam Medical Center |
Country | Netherlands |
Sector | Hospitals |
PI Contribution | Joint scientific meeting in September 2023 to plan academic collaboration. |
Collaborator Contribution | All members of the Amsterdam research group attended, gave presentations and participated in the collaboration planning workshops. |
Impact | Multidisciplinary - genomics, imaging data science, clinical science, epidemiology. |
Start Year | 2023 |
Description | Patient group workshop on polypharmacy |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Patients, carers and/or patient groups |
Results and Impact | The workshop involved presentations on prescribing and polypharmacy researchers involved in the MMTRC to the Patient Involvement in Multimorbidity Group established as part of the award. Presentations were followed by question and answer sessions and contributed to shaping plans for future research. |
Year(s) Of Engagement Activity | 2023 |