Public health applications of cardiovascular genomics

Heart disease and stroke (cardiovascular disease; CVD) result from arterial changes caused by interplay of genetic and environmental factors. Established (e.g. blood pressure and cholesterol) and suspected risk factors (e.g. blood levels of clotting factors, blood markers of glucose control, inflammation and others) are altered years ahead of CVD, but (with the exception of blood pressure and cholesterol) it is uncertain precisely which factors cause the disease and which are altered as a consequence of it, hampering development of new preventative therapies. Some of the genes underpinning CVD and its risk factors have been identified but it is uncertain how best to use the information to help identify those at high risk, or to develop new preventative measures and treatments. Using a technique to simultaneously type 50,000 common gene variants of 2100 genes with known or suspected links to CVD and its known or suspected risk factors, in people from the MRC-funded Whitehall II study, where detailed analyses of the changes in the blood, arteries and heart that predate CVD already exist, my research will help to disentangle the causal pathways (to help develop new preventative treatments), and critically appraise the role and limitations of predictive genetic testing for CVD.

Aims and objectives: I aim to test the hypothesis that common genetic variants associated with cardiovascular disease (CVD) and/or related traits and disorders can: (a) help to refine CVD risk stratification, to more effectively target established preventative therapies and; (b) provide new tools to understand causal pathways for CVD, to help develop new preventative interventions relevant to the population as a whole and not just those with a particular genotype. I will use the Whitehall II and collaborating studies to critically appraise the predictive utility and cost-effectiveness of genotypes for risk prediction, and their comparative and incremental utility in relation to established phenotype-based measures of risk. SNPs indexing exogenous exposures/endogenous biomarkers/risk of related disorders (e.g. pre-eclampsia and diabetes) will be applied as tools to test their causal effect on subclinical measures of CVD and, through larger collaborations, on disease risk, using mendelian randomisation.

Design and Methodology: The Whitehall II study of over 10,000 civil servants is recognised for its role in investigation of the determinants of CVD and for the range of detailed and repeated phenotypic and other measures spanning environmental exposures, biomarkers, structural and functional measures of subclinical CVD and disease end-points. Over 6000 Whitehall II participants have been genotyped for 50,000 single-nucleotide polymorphisms (SNPs) from 2100 relevant genes or regions proven or suspected of conferring susceptibility to CVD, or contributing to variance in CVD-related phenotypes using the ITMAT/BROAD/CARE gene centric Cardiochip. The 50k Cardiochip used in Whitehall II is being used by at least 7 other studies in the UK, and at least 9 collaborating studies in the USA so there is an exceptional opportunity to conduct joint analyses of these research questions on a previously unprecedented scale.

Scientific and medical opportunities. The identification of genotypes relevant to CVD from candidate gene and whole genome studies poses a challenge of how to apply the findings to improve health. The translational opportunities for predicting disease risk and treatment response (pharmacogenetics) are well recognised. The opportunities for causal analysis could be equally important because genotype is unique among naturally-occurring between-individual differences in being determined at random at conception. This could be applied to the development of new drugs for the whole population not just those with a particular genotype, using genetic studies as a natural randomised trial, to more reliably and systematically validate drug targets for CVD and to model their effects.