Metabolomic fingerprinting approach to sleep apnea disorder in human plasma

Introduction Obstructive sleep apnea/hypopnea syndrome (OSAHS) is becoming a major cause of morbidity and it is the most common medical cause of daytime sleepiness. Metabolomics fingerprinting is able to achieve through the identification of novel biomarkers the comprehensive characterization of the entire metabolome of a disease, with the final aim to predict response to different therapies and outcomes and increase the knowledge regarding the pathological bases underlying sleep disorders. Materials and methods A non-targeted metabolomic study of plasma from 42 OSAHS patients and 16 healthy subjects was performed. The individual analytical fingerprints obtained by gas chromatography coupled to mass spectrometry (GC-Q-MS) were deconvoluted using AMDIS software and identified by the information compiled in Fiehn’s and NIST libraries. The same set of samples were analysed by liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (LC-QTOF-MS). Profiles were aligned and filtered using Mass Profiler Professional. Univariate and multivariate statistical analysis were applied for screening potential biomarkers. Results OPLS-DA plots obtained using SIMCA-P+, based on GC-MS and LC-MS data, show clear separation between control and severe patient. Changes in the metabolic profiles of amino acids were found between both groups, showing an increase trend, including some branched-chain amino acid (BCAAs). Different metabolic pathways could be altered under conditions related to insulin resistance, such as metabolic syndrome and obesity causing alterations in branched-chain keto acid dehydrogenase that could be reflected in the increased level of BCAAs. Phosphocholine and compounds related to the glycine and glutamate metabolism were putatively assigned. Glutamate receptors have recently being found present in the lung (NMDA receptors) causing a wide range of damage (lipid peroxidation, DNA bridges broken, activation of the system caspases, loss of energy and cell death). Conclusion These findings reflect considerable differences in individual metabolite fingerprints of OSAHS patients and open the possibility of identifying novel biomarkers associated to sleep disorders, that can help to uncover the complexity underlyingthe metabolic alterations occurring in OSAHS. Acknowledgements The research leading to these results has received funding from the [European Union] Seventh Framework Programme [FP7/2007- 2013] under grant agreement n o 264864”.