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Published on: December 6, 2016
Surface Active Salivary Metabolites Indicate Oxidative Stress and Inflammation in Obstructive Sleep Apnea
Jiyoung Kim1,2,3,4, Sangmin An5,6, Yisook Kim1,2,3
1Obstructive Upper Airway Research (OUaR) Laboratory, Department of Pharmacology, Seoul National University College of Medicine, Seoul, Korea.
Purpose:
Obstructive sleep apnea (OSA), a highly prevalent and potentially serious sleep disorder, requires effective screening tools. Saliva is a useful biological fluid with various metabolites that might also influence upper airway patency by affecting surface tension in the upper airway. However, little is known about the composition and role of salivary metabolites in OSA. Therefore, we investigated the metabolomics signature in saliva from the OSA patients and evaluated the associations between identified metabolites and salivary surface tension.
Methods:
We studied 68 subjects who visited sleep clinic due to the symptoms of OSA. All underwent full-night in-lab polysomnography. Patients with apnea-hypopnea index (AHI) < 10 were classified to the control, and those with AHI ≥ 10 were the OSA groups. Saliva samples were collected before and after sleep. The centrifuged saliva samples were analyzed by liquid chromatography with high-resolution mass spectrometry (ultra-performance liquid chromatography-tandem mass spectrometry; UPLC-MS/MS). Differentially expressed salivary metabolites were identified using open source software (XCMS) and Compound Discoverer 2.1. Metabolite set enrichment analysis (MSEA) was performed using MetaboAnalyst 5.0. The surface tension of the saliva samples was determined by the pendant drop method.
Results:
Three human-derived metabolites (1-palmitoyl-2-[5-hydroxyl-8-oxo-6-octenoyl]-sn-glycerol-3-phosphatidylcholine [PHOOA-PC], 1-palmitoyl-2-[5-keto-8-oxo-6-octenoyl]-sn-glycerol-3-phosphatidylcholine [KPOO-PC], and 9-nitrooleate) were significantly upregulated in the after-sleep salivary samples from the OSA patients compared to the control group samples. Among the candidate metabolites, only PHOOA-PC was correlated with the AHI. In OSA samples, salivary surface tension decreased after sleep. The differences in surface tension were negatively correlated with PHOOA-PC and 9-nitrooleate concentrations. Furthermore, MSEA revealed that arachidonic acid-related metabolism pathways were upregulated in the after-sleep samples from the OSA group.
Conclusions:
This study revealed that salivary PHOOA-PC was correlated positively with the AHI and negatively with salivary surface tension in the OSA group. Salivary metabolomic analysis may improve our understanding of upper airway dynamics and provide new insights into novel biomarkers and therapeutic targets in OSA.
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