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Our published paper investigates strategies for reducing the risk of cardiovascular disease, and asks whether the addition of genetic information improves the performance of established tools for calculating disease risk. The paper has a particular focus on non-European ethnicities and ancestries.
Research highlights - A new integrated risk tool combines clinical and polygenic risk scores - Prediction is significantly enhanced in multiple ethnicities and ancestries - Ethnicities include Black and White, ancestries include African and European - This is the first positive cross-ethnicity cross-ancestry validation of such a tool
A genetic investigation of pleiotropy using the UK Biobank Data.
The aim of the proposed research is to understand pleiotropy: that is the nature, extent, and effect of genetic variation on multiple phenotypes. The extent of pleiotropy in humans is an important open question. Apart from inherent interest, it is directly relevant to the use of human genetics for improving drug development pipelines (see below). By their nature, studies of pleiotropy require data on multiple phenotypes. We aim to investigate pleiotropy using genetic data together with baseline measurements and the biomarker data (as it becomes available). Our analysis ultimately aims to inform decisions about which genes and pathways are the best targets for drug development. The efficacy and safety of therapeutics depends on the consequences of perturbations, by the drug, of particular gene products. Genetic variants also perturb the nature or amount of gene products, and is informative for drug efficacy, with effects on other phenotypes informative for on-target safety effects. The proposed work, mainly on non-clinical phenotypes, will involve proof-of-principle studies and development of statistical methods. We will make a further application when more clinical phenotypes are available in UK Biobank The research will use computers to build statistical models of the correlation between the genetic variation in an individual?s genome and biological measurements collected by UK Biobank. We can use the research to ask: if the genetic difference in a gene mimics or is related to the effects of a treatment what is likely to be the (positive and negative) effects of giving it to patients? To do this effectively we will look at the relationship between genetic variation and multiple phenotypes at the same time. Full cohort.