ArticleJournal of diabetes investigation2026
Physiological phenotypes of obstructive sleep apnea identified by cluster analysis: Association with type 2 diabetes.
Article in Journal of diabetes investigation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Comment on "Physiological phenotypes of obstructive sleep apnea identified by cluster analysis: Association with type 2 diabetes".Journal of diabetes investigation · 2026Article
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5 authors.
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Abstract
AIMS/
introductionObstructive sleep apnea (OSA) is a multifaceted condition that may variably influence metabolic risk. This study aimed to identify physiological phenotypes of OSA using polysomnographic (PSG) data and examine their association with type 2 diabetes (T2DM) in a Japanese cohort. MATERIALS AND
methodsAmong 3,683 individuals who underwent attended PSG between April 2019 and March 2024, 602 adults with OSA were included. Phenotypes were identified by k-means clustering. The association between phenotype and T2DM was assessed using logistic regression adjusted for covariates.
resultsFive phenotypes were identified: Severe desaturation, REM-predominant, PLMS-dominant, Sleep-fragmented, and Mild. Severe desaturation and REM-predominant types showed higher T2DM prevalence (54.5% and 45.7%). In multivariable analysis, both were independently associated with T2DM compared with the Mild type (adjusted odds ratio [OR] 5.00, 95% CI 1.52-16.4; and OR 3.12, 95% CI 1.32-7.38). To further explore the underlying mechanisms, logistic regression including all participants showed that CT90 was independently associated with T2DM, even after adjustment for arousal threshold and AHI.
conclusionsData-driven clustering identified distinct physiological phenotypes of OSA. In addition to the Severe desaturation type, the REM-predominant type was also strongly associated with T2DM, underscoring the metabolic heterogeneity of OSA. Prospective studies are needed to determine causal relationships and evaluate phenotype-targeted interventions.
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