Literature DB >> 29108583

Metabolomics analysis of human sweat collected after moderate exercise.

M M Delgado-Povedano1, M Calderón-Santiago1, M D Luque de Castro2, F Priego-Capote3.   

Abstract

Sweat is a promising biofluid scarcely used in clinical analysis despite its non-invasive sampling. A more frequent clinical use of sweat requires to know its whole composition, especially concerning to non-polar compounds, and the development of analytical strategies for its characterization. The aim of the present study was to compare different sample preparation strategies to maximize the detection of metabolites in sweat from humans collected after practicing moderate exercise. Special emphasis was put on non-polar compounds as they have received scant attention in previous studies dealing with this biofluid. Sample preparation by liquid-liquid extraction (LLE) using extractants with different polarity index was compared to deproteination. Then, derivatization by methoxymation with subsequent silylation was compared to direct analysis of sweat extracts to check the influence of derivatization on the subsequent determination of volatile organic compounds (VOCs). 135 compounds were tentatively identified by combining spectral and retention time information after analysis by gas chromatography coupled to mass spectrometry in high resolution mode (GC-TOF/MS). Lipids, VOCs, benzenoids and other interesting metabolites such as alkaloids and ethanolamines were identified. Among the tested protocols, methyoxiamination plus silylation after LLE with dichloromethane was the best option to obtain a representative snapshot of sweat metabolome collected from different body parts after moderate exercise. Passive and active sweat pools from a cohort of volunteers (n = 6) were compared to detect compositional differences which can be explained by the sampling process and sweating induction. As most of the identified compounds are metabolites involved in key biochemical pathways, this study opens new opportunities to extend the applicability of human sweat as a source of metabolite biomarkers of pathologies or specific processes such as dehydration or nutritional unbalance.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Active sweat; Exercise; Gas chromatography–mass spectrometry; Metabolomics; Passive sweat; Sample preparation

Mesh:

Substances:

Year:  2017        PMID: 29108583     DOI: 10.1016/j.talanta.2017.09.028

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  12 in total

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Authors:  Noé Brasier; Jens Eckstein
Journal:  Digit Biomark       Date:  2019-12-05

2.  Surface Wettability for Skin-Interfaced Sensors and Devices.

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4.  Comparative Study of the Composition of Sweat from Eccrine and Apocrine Sweat Glands during Exercise and in Heat.

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Review 5.  Physiology of sweat gland function: The roles of sweating and sweat composition in human health.

Authors:  Lindsay B Baker
Journal:  Temperature (Austin)       Date:  2019-07-17

Review 6.  Physiological mechanisms determining eccrine sweat composition.

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Review 7.  Metabolomics and Lipidomics: Expanding the Molecular Landscape of Exercise Biology.

Authors:  Mehdi R Belhaj; Nathan G Lawler; Nolan J Hoffman
Journal:  Metabolites       Date:  2021-03-07

Review 8.  The Potential of Metabolomics in Biomedical Applications.

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Journal:  Metabolites       Date:  2022-02-19

9.  Axillary Microbiota Is Associated with Cognitive Impairment in Parkinson's Disease Patients.

Authors:  Muzaffer Arikan; Zeynep Yildiz; Tugce Kahraman Demir; Nesrin H Yilmaz; Aysu Sen; Lutfu Hanoglu; Suleyman Yildirim
Journal:  Microbiol Spectr       Date:  2022-02-09

10.  The proteomic and metabolomic characterization of exercise-induced sweat for human performance monitoring: A pilot investigation.

Authors:  Sean W Harshman; Rhonda L Pitsch; Zachary K Smith; Maegan L O'Connor; Brian A Geier; Anthony V Qualley; Nicole M Schaeublin; Molly V Fischer; Jason J Eckerle; Adam J Strang; Jennifer A Martin
Journal:  PLoS One       Date:  2018-11-01       Impact factor: 3.240

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