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Polygenic scores for obstructive sleep apnoea reveal pathways contributing to cardiovascular disease

  • FinnGen
  • , The Trans-Omics in Precision Medicine Consortium
  • , The VA Million Veteran Program
  • Department of Veterans Affairs
  • Brigham and Women’s Hospital
  • Boston University
  • University of Helsinki
  • Stanford University
  • Helsinki University Hospital
  • Geisinger Medical Center
  • Harvard University
  • Beth Israel Deaconess Medical Center
  • University of Pennsylvania
  • VA Medical Center
  • Palo Alto Veterans Institute for Research
  • Albert Einstein College of Medicine
  • Saarland University
  • University of California at Los Angeles
  • University of North Carolina at Chapel Hill
  • Fred Hutchinson Cancer Research Center
  • The Lundquist Institute
  • University of Virginia
  • University of Washington
  • University of Texas Health Science Center at Houston
  • Northwestern University
  • National Institutes of Health
  • Framingham Heart Study
  • Atlanta VA Health Care System
  • Emory University
  • Massachusetts General Hospital
  • The Broad Institute of MIT and Harvard

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background: Obstructive sleep apnoea (OSA) is a common chronic condition, with obesity its strongest risk factor. Polygenic scores (PGSs) summarise the genetic liability to phenotype and can provide insights into relationships between phenotypes. Recently, large datasets that include genetic data and OSA status became available, providing an opportunity to utilise PGS approaches to study the genetic relationship between OSA and other phenotypes, while differentiating OSA-specific from obesity-specific genetic factors. Methods: Using race/ethnic diverse samples from over 1.2 million individuals from the Million Veteran Program, FinnGen, TOPMed, All of Us (AoU), Geisinger's MyCode, MGB Biobank, and the Human Phenotype Project, we developed and assessed PGSs for OSA, both without (BMIunadjOSA-PGS) and with adjustment for the genetic contributions of BMI (BMIadjOSA-PGS). Findings: Adjusted odds ratios (ORs) for OSA per 1 standard deviation of the PGSs ranged from 1.38 to 2.75. The associations of BMIadjOSA- and BMIunadjOSA-PGSs with CVD outcomes in AoU shared both common and distinct patterns. Only BMIunadjOSA-PGS was associated with type 2 diabetes, heart failure, and coronary artery disease, while both BMIadjOSA- and BMIunadjOSA-PGSs were associated with hypertension and stroke. Sex stratified analyses revealed that BMIadjOSA-PGS association with hypertension was driven by females (OR = 1.1, p-value = 0.002, OR = 1.01 p-value = 0.2 in males). OSA PGSs were also associated with body fat measures with some sex-specific associations. Interpretation: Distinct components of OSA genetic risk are related and independent of obesity. Sex-specific associations with body fat distribution measures may explain differing OSA risks and associations with cardiometabolic morbidities between sexes. Funding: R01AG080598.

Original languageEnglish
Article number105790
JournaleBioMedicine
Volume117
DOIs
StatePublished - Jul 2025

Keywords

  • Body fat distribution
  • Diverse populations
  • Genetically determined OSA
  • Sex differences

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