Dynamic Behavior of Cortisol and Cortisol Metabolites in Human Eccrine Sweat

J. Ray Runyon, Min Jia, Michael R. Goldstein, Perry Skeath, Leif Abrell, Jon Chorover, and Esther M. Sternberg
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Special Issue PHM for Human Health and Performance
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Full Paper
ijphm_19_006.pdf1.3 MBFebruary 28, 2019 - 10:54am

The simultaneous measurement of cortisol with its downstream metabolites in human eccrine sweat is a sensitive approach to capture minute-to-minute stress responses. This study investigates exercise stress induced time dependent dynamic changes in cortisol, cortisone and downstream inactive cortisol metabolites in human eccrine sweat using a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Cortisol and metabolite production (change in concentration over time) was measured in sweat at different time points during an administered exercise stress session with four healthy volunteers. Biomarker production plots were found to be highly individualized and sensitive to stress interventions such as exercise, and corresponded with stress response measures such as increases in heart rate. The LC-MS/MS method yielded baseline resolution between cortisol and cortisol metabolites with lower levels of detection and quantitation for each compound below 1 part-per-billion (ppb). Cortisol and cortisol metabolites were found at concentrations ranging from 1 – 25 ppb in human eccrine sweat. They were also found to be stable in sweat with respect to temperature (37 C for up to 5 hours), pH (3-9) and freeze/thaw cycles (up to 4) This indicates that changes in these biomarker concentrations and their rate of production are due to stress-related physiological enzyme activation, rather than passive degradation in sweat. The physiological status of enzyme activation is thus captured and preserved in human eccrine sweat samples. This is advantageous for the development of wearable devices and methodologies which can assess human health, stress, wellbeing and performance.

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Submission Keywords: 
Human Eccrine Sweat
Stress response
Sweat Gland
HPA axis
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
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