Joint Analysis of GWAS and Multi-omics QTL Summary Statistics Reveals a Large Fraction of GWAS Signals Shared with Molecular Phenotypes

Overview

Journal Cell Genom

Date 2023 Aug 21

PMID 37601976

Authors

Yang Wu

Ting Qi

Naomi R Wray

Peter M Visscher

Jian Zeng

Jian Yang

Affiliations

Soon will be listed here.

Abstract

Molecular quantitative trait loci (xQTLs) are often harnessed to prioritize genes or functional elements underpinning variant-trait associations identified from genome-wide association studies (GWASs). Here, we introduce OPERA, a method that jointly analyzes GWAS and multi-omics xQTL summary statistics to enhance the identification of molecular phenotypes associated with complex traits through shared causal variants. Applying OPERA to summary-level GWAS data for 50 complex traits (n = 20,833-766,345) and xQTL data from seven omics layers (n = 100-31,684) reveals that 50% of the GWAS signals are shared with at least one molecular phenotype. GWAS signals shared with multiple molecular phenotypes, such as those at the locus for prostate cancer, are particularly informative for understanding the genetic regulatory mechanisms underlying complex traits. Future studies with more molecular phenotypes, measured considering spatiotemporal effects in larger samples, are required to obtain a more saturated map linking molecular intermediates to GWAS signals.

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