Health Data Science - Cardiovascular Epidemiology Unit

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Overview

Our health data science team combines expertise across numerous disciplines, including mathematics, statistics, computing and epidemiology, to answer questions in the biomedical sciences by the analysis of data. We are motivated by answering real questions of clinical interest that may beneficially impact the health and well-being of individuals.

Through our team science approach, we are committed to scientific excellence, transparency and integrity. We have a thriving intellectual environment for research and training, where we recognise our most valuable asset is the people who conceive, drive, and deliver research through their vision, imagination and intellectual energy.

Research

Areas of key contributions:

Covid-19 response Supported viral genome tracking (COG-UK, Lancet Microbe 2020); characterised CVD-Covid-19 interplay (Wood, BMJ 2021; Knight, Circulation 2022; Whiteley, PLoS Medicine 2022)

Aetiological discovery Identified many causal risk factors for coronary disease and stroke; eg, blood pressure traits (Surendran, Nat Genet 2020); kidney disfunction (Gaziano Circulation 2022)

Therapeutic target prioritisation Developed and applied causal inference methods to characterise many genomic instruments; eg, human plasma metabolites (Surendran, Nat Med 2022; Chen, Nat Commun 2022); iron markers ()

Translational epidemiology Developed new risk assessment approaches for global and European settings (Hageman, Eur Heart J 2021; Kaptoge, Lancet Global Health 2019)

Polygenic Risk Scores Developed the Polygenic Score Catalog (Lambert, Nat Genet 2021) and developed reporting standards (Wand/Lambert, Nature 2021)

Population health policies Provided evidence to underpin UK screening programme for abdominal aortic aneurysms (Sweeting, Lancet 2018); informed new alcohol guidelines (Wood, Lancet 2018; Ricci, BMJ 2018)

Key partners in health data science:

Cambridge is a research site of Health Data Research UK (https://www.hdruk.ac.uk/) , a national health data science institute. HDR UK-Cambridge (https://www.hdruk.ac.uk/about-us/locations/hdr-uk-cambridge/) is a partnership of Cambridge University, Wellcome Sanger Institute, and EMBL-EBI, providing synergy with the CEU’s activities in the areas of multi-disease aetiology and polygenic scores. Cambridge University is a founding partner of the Alan Turing Institute for Data Science and Artificial Intelligence (https://www.turing.ac.uk) and several CEU members are Turing fellows and serve on committees.  The CEU is also a strategic partner in the BHF Data Science Centre (https://www.hdruk.ac.uk/helping-with-health-data/bhf-data-science-centre/), VIAgenomics (https://viagenomics.eu) and Italy’s Human Technopole (https://humantechnopole.it/en/).