Machine Learning-Based Analysis of Salivary Proteomic Signatures in Catathrenia.

ABSTRACT: Catathrenia is a rare sleep-related breathing disorder characterized by recurrent episodes of groaning during sleep, which leads to sleep fragmentation and daytime symptoms. Catathrenia could be misclassified as sleep apnea. Integrating omics data with machine learning techniques holds potential for diagnosis and advancing the understanding of its etiology. All participants included in the study underwent full-night polysomnography for evaluation. This study employed in-depth 4D-DIA proteomics to analyze salivary protein profiles in 22 catathrenia patients and 22 matched nonsnoring controls, revealing significant differences in protein characterization. Functional analysis of differentially expressed proteins indicated a predominant association with the extracellular matrix (ECM)-receptor

SUBMITTER: Yu M 

PROVIDER: S-EPMC12268424 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature