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Updated: Jul 12, 2025

A Model to Simulate Clinically Relevant Hypoxia in Humans
Published on: December 22, 2016
Changes in human sweat metabolome conditioned by severity of obstructive sleep apnea and intermittent hypoxemia
Laura S Castillo-Peinado1,2,3,4, Mónica Calderón-Santiago1,2,3,4, Bernabé Jurado-Gámez2,5
1Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Córdoba, Córdoba, Spain.
Abstract:
Obstructive sleep apnea (OSA) is a sleep disorder that has been associated with the incidence of other pathologies. Diagnosis is mainly based on the apnea-hypopnea index (AHI) obviating other repercussions such as intermittent hypoxemia, which has been found to be associated to cardiovascular complications. Blood-based samples and urine have been the most utilised biofluids in metabolomics studies related to OSA, while sweat could be an alternative due to its non-invasive and accessible sampling, its reduced complexity, and comparability with other biofluids. Therefore, this research aimed to evaluate metabolic overnight changes in sweat collected from patients with OSA classified according to the AHI and oxygen desaturation index (ODI), looking for potential cardiovascular repercussions. Pre- and post-sleeping sweat samples from all individuals (n = 61) were analysed by gas chromatography coupled to high-resolution mass spectrometry after appropriate sample preparation to detect as many metabolites as possible. Permanent significant alterations in the sweat were reported for pyruvate, serine, lactose, and hydroxybutyrate. The most relevant overnight metabolic alterations in sweat were reported for lactose, succinate, urea, and oxoproline, which presented significantly different effects on factors such as the AHI and ODI for OSA severity classification. Overall metabolic alterations mainly affected energy production-related processes, nitrogen metabolism, and oxidative stress. In conclusion, this research demonstrated the applicability of sweat for evaluation of OSA diagnosis and severity supported by the detected metabolic changes during sleep.
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