Principal Investigator: Dr Louise Wain
Department: Department of Health Sciences
Institution: University of LeicesterTags: 4372, blood pressure, cardiovascular, genetics, Hypertension, pharmacogenetics
Small increases in blood pressure within the normal range impact on the risk of stroke and cardiovascular disease. Understanding genetic determinants of blood pressure may help to develop improved therapies. Genome-wide association studies of the genetic determinants underlying blood pressure have identified 29 loci associated with systolic and/or diastolic blood pressure and 6 additional loci associated with mean arterial pressure or pulse pressure. To achieve large sample sizes (~70,000), these studies were meta-analyses; each study followed a simple common association analysis plan and the results were meta-analysed. A single approach, based on adding a constant to measured blood pressure in
Treated individuals, was used in each study to adjust for the effects of blood pressure-lowering medication. This is appropriate in many situations, but it cannot identify potential interactions between genetic variants and medication and, in the presence of such interactions, false positive or false negative findings can result. To improve upon these studies, a single large study with individual-level data is needed to facilitate a wider range of analyses. We request genome-wide SNP and phenotype data only for the ~50,000 samples which have genome-wide genotype information available through the UK BiLEVE project. We aim to comprehensively study genome-wide association of
Blood pressure, testing for and taking appropriate account of potential pharmacogenetic interactions. The study will generate a short-list of genetic variants potentially subject to pharmacogenetic interactions which we can follow up in other studies. In the short-term, the methods and findings from this study should inform the approach to study of the genetics of blood pressure in the whole of UK Biobank when these data become available. The study may also identify novel genetic associations for blood pressure or identify genetic variants that predict response to antihypertensive treatment and thus inform stratified medicine for this common condition.