Abstract
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.
Highlights
As wearable sensors, such as smart watches, become more socially integrated, the need for novel biosources to provide real time feedback of performance is paramount
As the biomarker discovery field expands into novel biosources, sweat has become an attractive non-invasive real time media for performance monitoring
While the collection methodology to determine sweat rate outlined by Harshman et al is advantageous when smaller volumes of sweat can be utilized for analysis, sufficient normalization approaches for larger quantities, such as those obtained from patches, have yet to be determined
Summary
As wearable sensors, such as smart watches, become more socially integrated, the need for novel biosources to provide real time feedback of performance is paramount. Recent data suggest amino acid quantities in sweat have been shown to range from ∼360 to
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