Following training in Genetics at the University of Cambridge and Genetic Epidemiology at the University of Sheffield, Adam completed a PhD in meta-analysis of genetic association studies of coronary heart disease at the University of Cambridge. This research was carried out jointly with the PHG Foundation, the MRC Biostatistics Unit, and the Cardiovascular Epidemiology Unit.
Since his PhD, Adam has worked in the Cardiovascular Epidemiology Unit, initially as a post-doctoral Research Associate; as a University Lecturer in Cardiovascular Epidemiology from 2012; and as a Reader in Molecular Epidemiology from 2018. As well as leading a Genetic Epidemiology team, Adam also oversees the Unit’s PhD students.
Research areas include:
- Genetic discovery: Adam’s main interests revolve around the identification of genetic variation linked with coronary disease, related phenotypes (eg, vascular risk factors such as lipids) and molecular ‘omics (eg, plasma proteomics and metabolomics) using SNP arrays. Current efforts in this area include the CARDIoGRAMplusC4D 1M+ Hearts project, the 100,000 participant CHD Exome+ consortium and imputed GWAS studies in INTERVAL and UK Biobank.
- Human genetics to inform therapeutics: By relating informative genetic variants (eg, variants of known function) to disease outcomes and phenotypes, inference about the likely efficacy and safety profile of therapeutic agents (or potential therapeutic agents) can be made. For example, the work of Adam and colleagues at CEU has highlighted the relationship of IL6R variants to risk of heart disease, raising the possibility of monoclonal antibodies being repurposed from inflammatory conditions to cardiovascular pathways. Adam works closely with large pharmaceutical companies to help discover and evaluate pathways of potential therapeutic interest.
- EPIC-CVD: Adam is the Scientific Coordinator of the EPIC-Heart/EPIC-CVD study, which is a pan-European study of incident coronary disease and stroke including participants from 23 centres across 10 European countries. This project has a wealth of genetic, biochemical and risk factor data, which are predominantly utilised for the study of gene-environment interaction, cardiovascular risk prediction, and genetic discovery.