Venkataraman, G. | bioRxiv Science

bioRxiv2019

Medical relevance of common protein-altering variants in GPCR genes across 337,205 individuals in the UK Biobank study

G protein-coupled receptors (GPCRs) drive an array of critical physiological functions and are an important class of drug targets, though a map of which GPCR genetic variants are associated with phenotypic variation is lacking. We performed a phenome-wide association analysis for 269 common protein-altering variants in 156 GPCRs and 275 phenotypes, including disease outcomes and diverse quantitative measurements, using 337,205 UK Biobank participants and identified 138 associations. We discovered novel associations between GPCR variants and migraine risk, hypothyroidism, and dietary consumption. We also demonstrated experimentally that variants in the {beta}2 adrenergic receptor (ADRB2) associated with immune cell counts and pulmonary function and variants in the gastric inhibitory polypeptide receptor (GIPR) associated with food intake and body size affect downstream signaling pathways. Overall, this study provides a map of genetic associations for GPCR coding variants across a wide variety of phenotypes, which can inform future drug discovery efforts targeting GPCRs.

genetics↗

bioRxiv2019

Polygenic risk modeling with latent trait-related genetic components

Polygenic risk models have led to significant advances in understanding complex diseases and their clinical presentation. While models like polygenic risk scores (PRS) can effectively predict outcomes, they do not generally account for disease subtypes or pathways which underlie within-trait diversity. Here, we introduce a latent factor model of genetic risk based on components from Decomposition of Genetic Associations (DeGAs), which we call the DeGAs polygenic risk score (dPRS). We compute DeGAs using genetic associations for 977 traits in the UK Biobank and find that dPRS performs comparably to standard PRS while offering greater interpretability. We show how to decompose an individuals genetic risk for a trait across DeGAs components, highlighting specific results for body mass index (BMI), myocardial infarction (heart attack), and gout in 337,151 white British individuals, with replication in a further set of 25,486 non-British white individuals from the Biobank. We find that BMI polygenic risk factorizes into components relating to fat-free mass, fat mass, and overall health indicators like physical activity measures. Most individuals with high dPRS for BMI have strong contributions from both a fat mass component and a fat-free mass component, whereas a few outlier individuals have strong contributions from only one of the two components. Overall, our method enables fine-scale interpretation of the drivers of genetic risk for complex traits.

genomics↗