Identification of metabolic fingerprints in severe obstructive sleep apnea using gas chromatography-Mass spectrometry

• Published in: Frontiers in molecular biosciences Vol. 9; p. 1026848
• Main Authors: Mohit, Tomar, Manendra Singh, Araniti, Fabrizio, Pateriya, Ankit, Singh Kushwaha, Ram Awadh, Singh, Bhanu Pratap, Jurel, Sunit Kumar, Singh, Raghuwar Dayal, Shrivastava, Ashutosh, Chand, Pooran
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 21.11.2022
• Subjects: biomarkers; gas chromatography–mass spectrometry; metabolomics; Molecular Biosciences; obstructive sleep apnea; polysomnography; obstructive sleep apnea; polysomnography; metabolomics; biomarkers; gas chromatography–mass spectrometry
• ISSN: 2296-889X; 2296-889X
• DOI: 10.3389/fmolb.2022.1026848

Obstructive sleep apnea (OSA) is considered a major sleep-related breathing problem with an increasing prevalence rate. Retrospective studies have revealed the risk of various comorbidities associated with increased severity of OSA. This study aims to identify novel metabolic biomarkers associated with severe OSA. In total, 50 cases of OSA patients (49.74 ± 11.87 years) and 30 controls (39.20 ± 3.29 years) were included in the study. According to the polysomnography reports and questionnaire-based assessment, only patients with an apnea-hypopnea index (AHI >30 events/hour) exceeding the threshold representing severe OSA patients were considered for metabolite analysis. Plasma metabolites were analyzed using gas chromatography-mass spectrometry (GC-MS). A total of 92 metabolites were identified in the OSA group compared with the control group after metabolic profiling. Metabolites and their correlated metabolic pathways were significantly altered in OSA patients with respect to controls. The fold-change analysis revealed markers of chronic kidney disease, cardiovascular risk, and oxidative stress-like indoxyl sulfate, 5-hydroxytryptamine, and 5-aminolevulenic acid, respectively, which were significantly upregulated in OSA patients. Identifying these metabolic signatures paves the way to monitor comorbid disease progression due to OSA. Results of this study suggest that blood plasma-based biomarkers may have the potential for disease management.