0577 Principal Component Analysis Identifies Distinct Sleep-Burden Phenotypes in a Clinical Cohort of Over 4000 Patients

Abstract Introduction Obstructive sleep apnea (OSA) is one of the most common sleep disorder and can be characterized with multiple physiological burdens: hypoxic burden (HB), ventilatory burden (VB), and arousal burden (AB). To better capture patterns across these dimensions, we applied principal component analysis (PCA) to derive axes integrating multiple burdens and examine their relation to demographic and cardiometabolic phenotypes in sleep clinic patients. Methods We analyzed 4,329 adults (mean age 49.7 ± 15.4 y, 50.8% female, 20.4% non-White, 41.6% overweight) who underwent diagnostic in-laboratory polysomnography at Massachusetts General Hospital (2010–2020) through the Human Sleep Project. PCA was applied to 31 features, including HB (cumulative oxygen desaturation), VB (low-amplitude breathing), AB (total arousal duration), Apnea-Hypopnea Index (AHI), and Respiratory Disturbance Index (RDI), measured across the whole night (WN), NREM, and REM, along with sleep-architecture features. Associations with demographic or cardiometabolic variables were assessed using t-tests with Cohen’s d. For each principal component, we calculated the associations of the component score with variables including age (>50y vs ≤50y), sex, BMI, race, hypertension, and diabetes. Results PCA revealed two primary components (PC1: 29.7%; PC2: 12.9% variance explained), subsequent components contributed < 10% each. PC1 represented a global respiratory-burden phenotype, primarily driven by WN and NREM HB (apnea-related HB loadings: 0.28, 0.27; overall HB loadings: 0.25, 0.25), AHI and RDI (loadings: 0.30, 0.30), with additional contributions from AB and VB, and minimal influence from sleep-architecture features. Higher PC1 scores occurred in older, male, White, overweight individuals (p < 0.001, d = 0.83). PC2 defined a sleep-continuity phenotype, with higher sleep efficiency (loading: 0.42), total sleep time (loading: 0.36), lower wake after sleep onset (loading: –0.39) and sleep fragmentation (loading: –0.31), minimally influenced by respiratory burden. Higher PC2 scores occurred in younger, non-White women without hypertension or diabetes (p < 0.001, d = 0.34). Conclusion In 4,329 adults, PCA identified two interpretable sleep-burden phenotypes: a high respiratory-burden phenotype in older White males with elevated BMI, and a protective sleep-continuity phenotype in younger, non-White women without hypertension or diabetes. These findings demonstrated that demographic and cardiometabolic factors aligned with distinct physiologic burdens. Support (if any) NIA (R21AG085495) NIA (R01AG083836)

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SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.0576
Primary Topic
Obstructive Sleep Apnea Research
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article
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article

0577 Principal Component Analysis Identifies Distinct Sleep-Burden Phenotypes in a Clinical Cohort of Over 4000 Patients

Sasha Milton, Haoqi Sun, Y. Fang, Alice Albrecht et al.
SLEEP
Obstructive Sleep Apnea Research
article

0577 Principal Component Analysis Identifies Distinct Sleep-Burden Phenotypes in a Clinical Cohort of Over 4000 Patients

Sasha Milton, Haoqi Sun, Y. Fang, Alice Albrecht, Robert Thomas, M Brandon Westover, Ankit Parekh, Yue Leng
article en

Abstract

Abstract Introduction Obstructive sleep apnea (OSA) is one of the most common sleep disorder and can be characterized with multiple physiological burdens: hypoxic burden (HB), ventilatory burden (VB), and arousal burden (AB). To better capture patterns across these dimensions, we applied principal component analysis (PCA) to derive axes integrating multiple burdens and examine their relation to demographic and cardiometabolic phenotypes in sleep clinic patients. Methods We analyzed 4,329 adults (mean age 49.7 ± 15.4 y, 50.8% female, 20.4% non-White, 41.6% overweight) who underwent diagnostic in-laboratory polysomnography at Massachusetts General Hospital (2010–2020) through the Human Sleep Project. PCA was applied to 31 features, including HB (cumulative oxygen desaturation), VB (low-amplitude breathing), AB (total arousal duration), Apnea-Hypopnea Index (AHI), and Respiratory Disturbance Index (RDI), measured across the whole night (WN), NREM, and REM, along with sleep-architecture features. Associations with demographic or cardiometabolic variables were assessed using t-tests with Cohen’s d. For each principal component, we calculated the associations of the component score with variables including age (>50y vs ≤50y), sex, BMI, race, hypertension, and diabetes. Results PCA revealed two primary components (PC1: 29.7%; PC2: 12.9% variance explained), subsequent components contributed < 10% each. PC1 represented a global respiratory-burden phenotype, primarily driven by WN and NREM HB (apnea-related HB loadings: 0.28, 0.27; overall HB loadings: 0.25, 0.25), AHI and RDI (loadings: 0.30, 0.30), with additional contributions from AB and VB, and minimal influence from sleep-architecture features. Higher PC1 scores occurred in older, male, White, overweight individuals (p < 0.001, d = 0.83). PC2 defined a sleep-continuity phenotype, with higher sleep efficiency (loading: 0.42), total sleep time (loading: 0.36), lower wake after sleep onset (loading: –0.39) and sleep fragmentation (loading: –0.31), minimally influenced by respiratory burden. Higher PC2 scores occurred in younger, non-White women without hypertension or diabetes (p < 0.001, d = 0.34). Conclusion In 4,329 adults, PCA identified two interpretable sleep-burden phenotypes: a high respiratory-burden phenotype in older White males with elevated BMI, and a protective sleep-continuity phenotype in younger, non-White women without hypertension or diabetes. These findings demonstrated that demographic and cardiometabolic factors aligned with distinct physiologic burdens. Support (if any) NIA (R21AG085495) NIA (R01AG083836)

SLEEPVol. 49(Supplement_1)
University of California, San Francisco (US), Hadassah Medical Center (IL), Icahn School of Medicine at Mount Sinai (US)
Openalex Percentile: Top 7%
Obstructive Sleep Apnea Research
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