The Impact of Nutritional Supplementation on Sweat Metabolomic Content: A Proof-of-Concept Study
| Autor: | Nicole M. Schaeublin, Christina N. Davidson, Andrew B. Browder, Maegan L. O'Connor, Kristyn N. Barrett, Mandy S. Phelps, Nicholas S. Mackowski, Jason J. Eckerle, Jennifer A. Martin, Rhonda L. Pitsch, Kraig E. Strayer, Adam J. Strang, Sean W. Harshman |
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| Rok vydání: | 2021 |
| Předmět: |
Nutritional Supplementation
Physiology 01 natural sciences SWEAT 03 medical and health sciences Metabolomics Metabolome Medicine Biomarker discovery QD1-999 Original Research 030304 developmental biology 0303 health sciences quantitation integumentary system Receiver operating characteristic business.industry 010401 analytical chemistry Area under the curve General Chemistry metabolomics 0104 chemical sciences Chemistry sweat normalization Biomarker (medicine) diet business |
| Zdroj: | Frontiers in Chemistry Frontiers in Chemistry, Vol 9 (2021) |
| ISSN: | 2296-2646 |
| DOI: | 10.3389/fchem.2021.659583 |
| Popis: | Sweat is emerging as a prominent biosource for real-time human performance monitoring applications. Although promising, sources of variability must be identified to truly utilize sweat for biomarker applications. In this proof-of-concept study, a targeted metabolomics method was applied to sweat collected from the forearms of participants in a 12-week exercise program who ingested either low or high nutritional supplementation twice daily. The data establish the use of dried powder mass as a method for metabolomic data normalization from sweat samples. Additionally, the results support the hypothesis that ingestion of regular nutritional supplementation semi-quantitatively impact the sweat metabolome. For example, a receiver operating characteristic (ROC) curve of relative normalized metabolite quantities show an area under the curve of 0.82 suggesting the sweat metabolome can moderately predict if an individual is taking nutritional supplementation. Finally, a significant correlation between physical performance and the sweat metabolome are established. For instance, the data illustrate that by utilizing multiple linear regression modeling approaches, sweat metabolite quantities can predict VO2 max (p = 0.0346), peak lower body Windage (p = 0.0112), and abdominal circumference (p = 0.0425). The results illustrate the need to account for dietary nutrition in biomarker discovery applications involving sweat as a biosource. |
| Databáze: | OpenAIRE |
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