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


 
 
 Despite its association with severe health conditions, the aetiology of sleep apnoea remains understudied. This study sought to identify genetic variants robustly associated with sleep apnoea risk.
 
 
 
 We 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.
 
 
 
 Our sleep apnoea meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with sleep apnoea risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. 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.
 
 
 
 Our 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.
