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Polygenic scores for obstructive sleep apnoea reveal pathways contributing to cardiovascular disease.
Wednesday,2025-07-16 14:45 America/Los_Angeles — ecterry
| Title | Polygenic scores for obstructive sleep apnoea reveal pathways contributing to cardiovascular disease. |
| Publication Type | Journal Article |
| Year of Publication | 2025 |
| Authors | Kurniansyah, N, Strausz, SJ, Chittoor, G, Gupta, S, Justice, AE, Hrytsenko, Y, Keenan, BT, Cade, BE, Spitzer, BW, Wang, H, Huffman, J, Moll, MR, Haring, B, Jung, SYon, Raffield, LM, Kaplan, R, Rotter, JI, Rich, SS, Gharib, SA, Bartz, TM, Liu, PY, Chen, H, Fornage, M, Hou, L, Levy, D, Morrison, AC, Ochs-Balcom, HM, Psaty, BM, Wilson, PWF, Cho, K, Pack, AI, Ollila, HM, Redline, S, Gottlieb, DJ, Sofer, T |
| Corporate/Institutional Authors | FinnGen, Trans-Omics in Precision Medicine Consortium, VA Million Veteran Program |
| Journal | EBioMedicine |
| Volume | 117 |
| Pagination | 105790 |
| Date Published | 2025 Jul |
| ISSN | 2352-3964 |
| Keywords | Aged, Body Mass Index, Cardiovascular Diseases, Female, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Multifactorial Inheritance, Obesity, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Sleep Apnea, Obstructive |
| Abstract | <p><b>BACKGROUND: </b>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.</p><p><b>METHODS: </b>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).</p><p><b>FINDINGS: </b>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.</p><p><b>INTERPRETATION: </b>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.</p><p><b>FUNDING: </b>R01AG080598.</p> |
| DOI | 10.1016/j.ebiom.2025.105790 |
| Alternate Journal | EBioMedicine |
| PubMed ID | 40472801 |
| PubMed Central ID | PMC12171572 |
ePub date:
25/06