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Associations between obstructive sleep apnea and comorbidities in a large clinical biobank

Cade, B. E.; Li, L.; Duff, M.; Yang, C.; Hassan, S. M.; Yu, X.; Goodman, M. O.; Alex, R. M.; Azarbarzin, A.; Batool-Anwar, S.; Nezami, F. R.; Ramezani, A.; Sands, S. A.; Wang, H.; Kirchner, H. L.; Shah, N. A.; Epstein, L. J.; Pavlova, M. K.; Redline, S.

2025-08-01 respiratory medicine
10.1101/2025.07.30.25332466 medRxiv
Show abstract

BackgroundObstructive sleep apnea (OSA) is associated with a wide range of comorbidities, but large-scale phenome-wide analyses in clinical biobanks remain under-reported. In this study, we identified common comorbidities enriched in patients with OSA, tested the temporality of these associations, and analyzed relevant associations with summary sleep recording data. Methods48,251 participants with OSA in the Mass General Brigham healthcare system were identified using a natural language processing phenotyping algorithm and/or evidence of an elevated apnea-hypopnea index (AHI). Controls were matched (2:1) on demographics, body mass index (BMI), and healthcare utilization. Associations with 358 incident and 563 cross-sectional diseases were tested using Modified Poisson regression, adjusting for covariates. Sensitivity analyses examined timing by binning data in years relative to the first OSA diagnosis. Selected laboratory results were obtained based on associated diseases. Associated diseases were tested with sleep recording statistics (n [≤]18,348). Findings179 incident and 421 cross-sectional diseases were associated with OSA at Bonferroni significance. 37 diseases had Bonferroni-significant sex interactions. Several associations were significant years before the first recorded OSA diagnosis. Four red blood cell laboratory measures were significant ten years prior to the first diagnosis. One incident and 47 cross-sectional diseases were associated with the AHI and/or chronic hypoxemia. InterpretationObstructive sleep apnea is associated with enrichment of hundreds of diseases, several of which are supported by orthogonal polysomnographic evidence. Leveraging early signs of OSA in clinical data may help to identify at-risk patients. FundingNational Institutes of Health and the American Academy of Sleep Medicine Foundation.

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