Key result
Polygenic scores for obstructive sleep apnea were associated with increased OSA risk (OR 1.38 to 2.75 per 1 SD increase) and demonstrated distinct BMI-dependent and independent association patterns with cardiovascular diseases.
Why the study?
Obstructive sleep apnea is a heterogeneous disease, with obesity representing a significant risk factor through mechanisms including airway collapsibility, reduced lung volumes, and potentially body fat distribution.
Do BMI-adjusted and unadjusted polygenic scores for obstructive sleep apnea predict cardiovascular disease outcomes in diverse populations?
Observational
Yes
Do BMI-adjusted and unadjusted polygenic scores for obstructive sleep apnea predict cardiovascular disease outcomes in diverse populations?
Effect estimate: OR 1.38 to 2.75
Distinct genetic components of OSA risk, separated by BMI adjustment, reveal different association patterns with cardiovascular morbidities like heart failure and coronary artery disease.
Should not yet change OSA screening or CVD care; leaves open obesity-independent genetic pathways and sex differences in risk.
Background Obstructive sleep apnea (OSA) is a heterogeneous disease, with obesity a significant risk factor via increased airway collapsibility, reduced lung volumes, and possibly body fat distribution. Methods Using race/ethnic diverse samples from the Million Veteran Program, FinnGen, TOPMed, All of Us (AoU), Geisinger’s MyCode, MGB Biobank, and the Human Phenotype Project (HPP), we developed, selected, and assessed polygenic scores (PGSs) for OSA, relying on genome-wide association studies both adjusted and unadjusted for BMI: BMIadjOSA- and BMIunadjOSA-PGS. We tested their associations with CVD in AoU. Results 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. For example, BMIunadjOSA-PGS was associated with type 2 diabetes, heart failure, and coronary artery disease, but the associations of BMIadjOSA-PGS with these outcomes were statistically insignificant with estimated OR close to 1. In contrast, both BMIadjOSA- and BMIunadjOSA-PGSs were associated with hypertension and stroke. Sex stratified analyses revealed that BMIadjOSA-PGS association with hypertension was driven by data from OR=1.1, p-value=0.002, OR=1.01 p-value=0.2 in males). OSA PGSs were also associated with dual-energy X-ray absorptiometry (DXA) body fat measures with some sex-specific associations. Conclusions Distinct components of OSA genetic risk are related to obesity and body fat distribution, and may influence clinical outcomes. These may explain differing OSA risks and associations with cardiometabolic morbidities between sex groups.
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Kurniansyah et al. (2024) conducted an observational in Obstructive sleep apnea and cardiovascular disease. Polygenic scores for obstructive sleep apnea (BMI-adjusted and BMI-unadjusted) vs. Per 1 standard deviation increase in polygenic score was evaluated on Obstructive sleep apnea (OSA) risk (OR 1.38 to 2.75). Polygenic scores for obstructive sleep apnea were associated with increased OSA risk (OR 1.38 to 2.75 per 1 SD increase) and demonstrated distinct BMI-dependent and independent association patterns with cardiovascular diseases.
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