A multi-ancestry genome-wide meta-analysis, fine-mapping, and target gene prioritization to characterize the genetic architecture of adiponectin.

Abstract

Previous genome-wide association studies (GWAS) for adiponectin, a complex trait linked to type 2 diabetes and obesity, identified >20 associated loci. However, most loci were identified in populations of European ancestry, and many of the target genes underlying the associations remain unknown. We conducted a multi-ancestry adiponectin GWAS meta-analysis in [≤]46,434 individuals from the METSIM cohort and the ADIPOGen and AGEN consortiums. We combined study-specific association summary statistics using a fixed-effects, inverse variance-weighted approach. We identified 22 loci associated with adiponectin (P 0.9), which also exhibited potential pleiotropy for cardiometabolic traits. To prioritize target genes at associated loci, we propose a combinatorial likelihood scoring formalism ("GPScore") based on measures derived from 11 gene prioritization strategies and the physical distance to the transcription start site. With "GPScore", we prioritize the 30 most probable target genes underlying the adiponectin-associated variants in the multi-ancestry analysis, including well-known causal genes (e.g., ADIPOQ, CDH13) and novel genes (e.g., CSF1, RGS17). Functional association networks revealed complex interactions of prioritized genes, their functionally connected genes, and their underlying pathways centered around insulin and adiponectin signaling, indicating an essential role in regulating energy balance in the body, inflammation, coagulation, fibrinolysis, insulin resistance, and diabetes. Overall, our analyses identify and characterize adiponectin association signals and inform experimental interrogation of target genes for adiponectin.