Professor Jemma C. Hopewell
+44 (0)1865 743661
Senior Scientist in Genetic Epidemiology and Clinical Trials
Big Data Institute
British Heart Foundation
Basic Science Research Fellow
BHF Centre of Research Excellence
- HPS2 -THRIVE: Treatment of HDL to Reduce the Incidence of Vascular Events
- HPS3 / TIMI 55 - REVEAL : Randomised EValuation of the Effects of Anacetrapib through Lipid-modification
- MRC/BHF Heart Protection Study
Steering Committee; WG co-chair
International Stroke Genetics Consortium
Steering Committee, Chair of METASTROKE
Scientific Advisory Board
BSc (Hons) MSc PhD (Cantab) FESC
Professor of Precision Medicine & Epidemiology
- MSc in Global Health Science Module Lead: Genetic Epidemiology
- EPSRC Centre for Doctoral Training in Health Data Science Module Lead: Genetics
- Visiting Professor, Department of Human Genetics, McGill University
Interests: Cardiovascular Disease, Arrhythmias, Risk Factors, Clinical Trials, Epidemiology, Genetic Epidemiology, Pharmacogenetics
Professor Jemma Hopewell leads a team of genetic epidemiologists, clinical fellows, medical statisticians and bioinformaticians in a programme of research focusing on the use of genetic and clinical trial-based studies to investigate the causes and treatments for cardiovascular disease and arrhythmias. She has particular interests in using epidemiological, genetic and other large-scale 'omic approaches to improve our understanding of drug targets and disease mechanisms, perform genomic characterisation of vascular disease and its risk factors, particularly Lp(a), and in determining predictors of patient response to therapy.
Jemma leads and collaborates on numerous trial-based, epidemiological, and genetic epidemiological projects involving CTSU's vascular mega-trials (e.g. HPS, SEARCH, THRIVE, REVEAL), large-scale studies and biobanks (e.g. PROCARDIS, UK Biobank), and international consortia (e.g.CARDIoGRAMplusC4D, ISGC GoLEAD, CATCH-ME), and working with colleagues from across academia and other industries.
She has Steering Committee, DMC and invited expert roles in numerous large-scale studies and clinical trials, as well as for national agencies and funders, ranging from the Lp(a) Scientific Advisory Board, to MHRA, to Chairing the American Heart Association Fellowship Committee (Human Studies 22-23).
- Research Staff & Affiliates
Dr Parag Gajendragadkar, Senior Clinical Fellow in Electrophysiology
Federico Murgia, Bioinformatician
Dr Alison Offer, Senior Statistical Programmer
Dr Elsa Valdes-Marquez, Senior Medical Statistician
Adam Von Ende, Medical Statistician
- DPhil Students
Dr Christian Camm, British Heart Foundation Clinical Research Training Fellow
Sam Smith, Personal Assistant
- Past Staff and Students
Dr Maddalena Ardissino, MSc Student
Cori Campbell, Oxford British Heart Foundation Centre for Research Excellence Student
Lorna Cowan, Oxford British Heart Foundation Centre for Research Excellence Student
Tanya Domun, UNIQ+/Oxford British Heart Foundation Centre for Research Excellence Student
Dr Parag Gajendragadkar, DPhil Student & British Heart Foundation Clinical Research Training Fellow
Dr Issaac Ghinai, MSc Student
Mengyu Gu, Statistical training Fellow
Dr Maysson Ibrahim, Senior Bioinformatician
Kingwai Lau, Bioinformatician
Dr Lerato Magosi, DPhil Student
Dr Evangelos Oikonomou, DPhil Student
Jonathan Tan, RSCI Student
Larissa Ange Tchuisseu-Kwangoua, Genetic Epidemiology Clinical Intern
Hanning Zhu, Medical Statistician
Proteomic profiling identifies novel independent relationships between inflammatory proteins and myocardial infarction.
Valdes-Marquez E. et al, (2023), Eur J Prev Cardiol
Apolipoprotein Proteomics for Residual Lipid-Related Risk in Coronary Heart Disease.
Clarke R. et al, (2023), Circulation research
Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.
Aragam KG. et al, (2022), Nature genetics, 54, 1803 - 1815
Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries.
Mishra A. et al, (2022), Nature
Stroke genetics informs drug discovery and risk prediction across ancestries.
Mishra A. et al, (2022), Nature, 611, 115 - 123