Discovery of genomic loci associated with sleep apnoea risk through multi-trait GWAS analysis with snoring

Abstract

BackgroundSleep apnoea is characterised by periods of halted breathing during sleep. Despite its association with severe health conditions, the aetiology of sleep apnoea remains understudied, and previous genetic analyses have not identified many robustly associated genetic risk variants. MethodsWe performed a genome-wide association study (GWAS) meta-analysis of sleep apnoea across five cohorts (NTotal=523,366), followed by a multi-trait analysis of GWAS (MTAG) to boost power, leveraging the high genetic correlation between sleep apnoea and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional & joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal=1,477,352; Ncases=175,522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method. ResultsOur MTAG analysis uncovered 49 significant independent loci associated with sleep apnoea risk. Twenty-nine variants were replicated in the 23andMe cohort. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions. ConclusionsOur study uncovered multiple genetic loci associated with sleep apnoea risk, thus increasing our understanding of the aetiology of this condition and its relationship with other complex traits.