Urinary metabolite signatures reflect the altered host metabolism in severe obstructive sleep apnea

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder. The onset and progression of OSA are often linked with severe cardiovascular and metabolic comorbidities. At the same time, given the increasing prevalence of OSA, novel methods to screen OSA and its follow-up are needed. Untargeted metabolic profiling of OSA patients and healthy controls was planned to capture a snapshot of urinary metabolites and potential biomarkers using the gas chromatography-mass spectrometry (GC–MS) method. Polysomnography (PSG) confirmed severe OSA patients with AHI index ≥ 30 were considered for urine sample collection. The sample size was constituted of OSA (n = 36) and healthy controls (n = 36). Metabolite extraction and derivatization were performed and metabolomic analysis was performed by using GC–MS. The obtained data set was statistically analyzed using univariate and multivariate analysis. The Orthogonal partial least-squares discriminant analysis (OPLS-DA) was performed to screen differential metabolites between OSA patients and healthy controls. The metabolomic analysis revealed a total of 142 significantly altered metabolites of interest. Biomarker analysis allows for the creation of a list of putative urinary biomarkers including GABA, malic acid, glutamic acid, epichoric acid etc., with an accuracy of 99.8 % to 100 % for OSA screening. Subsequently, pathway analysis revealed that related biochemical pathways like the tricarboxylic acid cycle (TCA), glutamate/glutamine, amino acid and fatty acid metabolism, that are significantly interlinked with these metabolic biomarkers can play a crucial role in the pathogenesis of OSA. This study paves the way to undertake mass screening in a larger population to identify specific and reliable biomarkers.