PQG Working Group

Wenhan Lu

Analytic and Translational Genetics Unit
HMS, MGH, Broad Institute

Quantifying the extent of pleiotropy using rare variant association data in 394,841 human exomes

Genome-wide association studies (GWAS) and rare-variant association studies (RVAS) have identified thousands of genes and variants that affect multiple phenotypes, implicating potential pleiotropic effects. However, it still needs to be determined through what biological avenue such genetic components engender these cross-phenotype associations. Characterizing the underlying genetic architecture of complex phenotypes sharing associations with the same genetic component is crucial in interpreting the functions of genes and promoting our understanding of human biology. Previous studies on existing GWAS results have provided evidence of the pervasive existence of pleiotropy across the human genome, which is well-characterized for common variants but not systematically explored for rare variants yet.

We use the rare variant association data across 4,529 phenotypes from the exome sequence data of 394,841 individuals in the UK Biobank to assess the extent of pleiotropy among rare variants. Utilizing both the variant-level and the aggregated gene-based test results, we observe a widespread pleiotropic structure across human exomes through a comprehensive survey of cross-phenotype associations at the individual phenotype level as well as phenotypic domain level. We also investigate pleiotropy as an allelic series, where variants from the same gene with different functional impacts may exhibit diverse phenotypic effects; more specifically, variants of the pLoF group and the missense group are observed to be associated with completely different phenotypic consequences. To better interpret the underlying genetic mechanisms of pleiotropy, we develop new statistical methods and frameworks to detect the allelic heterogeneity underneath the pleiotropic effects and distinguish between pleiotropy resulting from mediating factors and those implicating genuine diverse genetic pathways. Finally, we apply our novel methods to genes harboring a high potential of being pleiotropic and highlight the heterogeneous effects of variants within the genes impacting diseases from distinct domains. In this way, we demonstrate potential shared and diverse biological pathways among disease groups, providing insight into the genetic basis of pleiotropy in complex human traits.