Possible cross‑talk between sarcopenia and obstructive sleep apnea revealed by WGCNA analysis and machine learning

Kunze Lu; Haiyan Lei; Caixing Wu; Danxia Lin; Yi Li; Yan Deng

doi:10.1080/13685538.2026.2640269

March 5, 2026The Aging MaleOpen Access

Possible cross‑talk between sarcopenia and obstructive sleep apnea revealed by WGCNA analysis and machine learning

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Key Points

The research aims to identify biomarkers linking sarcopenia with obstructive sleep apnea (OSA).
Utilized weighted gene co-expression network analysis (WGCNA) to identify gene interactions.
Applied machine learning to create a diagnostic model based on selected biomarkers.
Assessed the predictive ability of the model for sarcopenia in OSA patients.
Identified LGR6 and ARRDC2 as potential biomarkers for OSA and sarcopenia.
Developed a diagnostic model that accurately predicts sarcopenia risk in patients with OSA.

Implication

Findings show biomarkers for diagnosing sarcopenia in obstructive sleep apnea, suggesting a connection between both conditions.

Abstract

Our findings identify LGR6 and ARRDC2 as potential biomarkers for diagnosing comorbid OSA and sarcopenia. Moreover, a diagnostic model based on these two hub genes can predict the risk of sarcopenia in patients with OSA.

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Cite This Study

Lu et al. (2026) studied this question.

synapsesocial.com/papers/69abc2075af8044f7a4eb442 https://doi.org/10.1080/13685538.2026.2640269

View Full Paper

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Possible cross‑talk between sarcopenia and obstructive sleep apnea revealed by WGCNA analysis and machine learning

Key Points

Implication

Abstract

Discussion

Cite This Study

Possible cross‑talk between sarcopenia and obstructive sleep apnea revealed by WGCNA analysis and machine learning

Key Points

Implication

Abstract

Discussion

Cite This Study

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