Metabolomic and lipidomic profile in men with obstructive sleep apnoea: implications for diagnosis and biomarkers of cardiovascular risk

• Published in: Scientific reports Vol. 8; no. 1; pp. 11270 - 12
• Main Authors: Lebkuchen, Adriana, Carvalho, Valdemir M., Venturini, Gabriela, Salgueiro, Jéssica S., Freitas, Lunara S., Dellavance, Alessandra, Martins, Franco C., Lorenzi-Filho, Geraldo, Cardozo, Karina H. M., Drager, Luciano F.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 26.07.2018; Nature Publishing Group
• Subjects: 631/553/2710; 692/308/53/2421; 692/53/2421; Apnea; Arachidonic acid; Biomarkers; Cardiovascular diseases; Chromatography; Gas chromatography; Glutamic acid; Health risks; Humanities and Social Sciences; Lipid metabolism; Lipids; Liquid chromatography; Mass spectrometry; Mass spectroscopy; Metabolites; Metabolomics; multidisciplinary; Questionnaires; Science; Science (multidisciplinary); Sleep; Sleep apnea; Sleep disorders; Sphingomyelin; Sugar
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-018-29727-6

The use of metabolomic and lipidomic strategies for selecting potential biomarkers for obstructive sleep apnoea (OSA) has been little explored. We examined adult male patients with OSA (defined by an apnoea-hypopnoea index ≥15 events/hour), as well as age-, gender-, and fat-composition-matched volunteers without OSA. All subjects were subjected to clinical evaluation, sleep questionnaires for detecting the risk of OSA (Berlin and NoSAS score), metabolomic analysis by gas chromatography coupled to mass spectrometry and lipidomic analysis with liquid chromatography followed by detection by MALDI-MS. This study included 37 patients with OSA and 16 controls. From the 6 metabolites and 22 lipids initially selected, those with the best association with OSA were glutamic acid, deoxy sugar and arachidonic acid (metabolites), and glycerophosphoethanolamines, sphingomyelin and lyso-phosphocholines (lipids). For the questionnaires, the NoSAS score performed best with screening for OSA (area under the curve [AUC] = 0.724, p  = 0.003). The combination of the NoSAS score with metabolites or lipids resulted in an AUC for detecting OSA of 0.911 and 0.951, respectively. In conclusion, metabolomic and lipidomic strategies suggested potential early biomarkers in OSA that could also be helpful in screening for this sleep disorder beyond traditional questionnaires.