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Approved research

Development and validation of polygenic risk scores for complex traits and diseases

Principal Investigator: Dr Joseph Pickrell
Approved Research ID: 49662
Approval date: July 12th 2019

Lay summary

As genomic studies of disease have become larger and more powerful, their results have become increasingly useful for prediction of disease risk. Specifically, polygenic risk scores computed by summing the effects of tens to thousands of genetic variants associated with a disease can be used to stratify individuals according to their risk of the disease, and there is increasing evidence that targeting interventions to those individuals with the highest risk scores may lead to clinical improvements in outcomes.This is perhaps best exemplified by the example of heart disease -- polygenic risk scores identify eight percent of the population with a three-fold increase in risk for heart disease (a risk analogous to that conferred by mutations that cause familial hypercholesterolemia), and individuals with higher polygenic risk obtain more clinical benefit from the use of lipid-lowering statins. This project therefore seeks to build upon and extend the current literature regarding polygenic scoring for complex diseases and to further elucidate the underlying genetic landscape of such traits. By improving the discriminatory power of these risk scores through the application of both established and novel methods for constructing polygenic predictors on traits with moderate to high heritability (such as height and BMI) and releasing the resulting code and predictors, we will enable investigators in the clinical sphere to better predict and identify high-risk groups based on genotype alone. We also note that novel statistical methodology will contribute to the iterative improvement in polygenic risk scoring that has been increasingly of interest in both the public and academic eye. The duration for the proposed project is 36 months.