An atlas of associations between polygenic risk scores from across the human phenome and circulating metabolic biomarkers

Polygenic risk scores (PRS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease. In this study, we have constructed an atlas of associations between 129 different PRS and 249 circulating metabolites in up to 83,004 participants from the UK Biobank study. As an exemplar to demonstrate the value of this atlas we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bi-directional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as body mass index (Beta=0.16 per standard deviation change in GlycA, 95% CI=0.11 to 0.21, P=9.9x10-10) or liability towards smoking cigarettes (Beta=0.28, 95% CI=0.20 to 0.35, P=2.4x10-14), on systemic inflammation as opposed to the converse direction of effect. Furthermore, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PRS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. All results can be visualised at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas.