medRxivGenetic & Genomic MedicinePreprint
Genome-wide association study of obstructive sleep apnea in the Million Veteran Program uncovers genetic heterogeneity by sex
Tamar SoferiD, Nuzulul KurniansyahiD, Michael T. MurrayiD, Yuk-Lam Anne HoiD, Jennifer E. HuffmaniD, Kelly ChoiD, Peter W.F. WilsoniD, Daniel J. GottliebiD
Abstract
BackgroundGenome-wide association studies (GWAS) for obstructive sleep apnea (OSA) are limited due to the underdiagnosis of OSA, leading to misclassification of OSA, which consequently reduces statistical power. We performed a GWAS of OSA in the Million Veteran Program (MVP) of the U.S. Department of Veterans Affairs (VA) healthcare system, where OSA prevalence is close to its true population prevalence. MethodsWe performed GWAS of 568,576 MVP participants, stratified by biological sex and by harmonized race/ethnicity and genetic ancestry (HARE) groups of White, Black, Hispanic, and Asian individuals. We considered both BMI adjusted (BMI-adj) and unadjusted (BMI-unadj) models. We replicated associations in independent datasets, and analyzed the heterogeneity of OSA genetic associations across HARE and sex groups. We finally performed a larger meta-analysis GWAS of MVP, FinnGen, and the MGB Biobank, totaling 916,696 individuals. FindingsMVP participants are 91% male. OSA prevalence is 21%. In MVP there were 18 and 6 genome-wide significant loci in BMI-unadj and BMI-adj analyses, respectively, corresponding to 21 association regions. Of these, 17 were not previously reported in association with OSA, and 13 replicated in FinnGen (False Discovery Rate p-value<0.05). There were widespread significant differences in genetic effects between men and women, but less so across HARE groups. Meta-analysis of MVP, FinnGen, and MGB biobank revealed 17 additional, novel, genome-wide significant regions. InterpretationSex differences in genetic associations with OSA are widespread, likely associated with multiple OSA risk factors. OSA shares genetic underpinnings with several sleep phenotypes, suggesting shared etiology and causal pathways. FundingDescribed in acknowledgements.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Genetic analysis of obstructive sleep apnoea discovers a strong association with cardiometabolic health
Satu J. Strausz, Sanni Ruotsalainen, … Samuli Ripatti·European Respiratory JournalPeer-reviewed·Nov 26, 2020
- Discovery of genomic loci associated with sleep apnoea risk through multi-trait GWAS analysis with snoring
Adrián I. Campos, Nathan Ingold, … Miguel E. Rentería·SLEEPPeer-reviewed·Dec 16, 2022
- Characterization of Genetic and Phenotypic Heterogeneity of Obstructive Sleep Apnea Using Electronic Health Records
Olivia J. Veatch, Christopher R. Bauer, … Sarah A. Pendergrass·BMC Medical GenomicsPeer-reviewed·Jul 25, 2020
- COMPREHENSIVE GENETIC INVESTIGATION REVEALS HETEROGENEOUS PATHWAYS TO OBSTRUCTIVE SLEEP APNEA
Anne E. Justice, Brendan T Keenan, … Allan I Pack·medRxiv·Jan 11, 2026
- Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank (n=408,317)
Adrián I. Campos, Luis M. García‐Marín, … Miguel E. Rentería·bioRxiv·Oct 17, 2019
- Gene-Excessive Sleepiness Interactions Suggest Treatment Targets for Obstructive Sleep Apnea Subtype
Pavithra Nagarajan, Nuzulul Kurniansyah, … Heming Wang·medRxiv·Oct 25, 2024