A recent study explored the significance of quantifying amino acids in small volumes of sweat using high-performance liquid chromatography (HPLC) with fluorescence detection. This method offers a non-invasive and efficient way to screen for diseases by detecting amino acids in minimal sweat samples.
Conducted by the Graduate School of Pharmaceutical Sciences at the University of Tokyo and Pico Device (Nagoya, Japan), the study focused on the importance of detecting amino acids in minute sweat volumes. This innovative approach, published in Heliyon, provides a promising method for disease screening and has the potential to extend its applications to analyze other biomolecules in sweat.
The growing interest in non-invasive analytical methods has shifted attention to biological samples beyond blood. Sweat, saliva, and tears have emerged as key sources for analysis, with sweat being particularly valuable for continuous, real-time health monitoring. Produced by bodily glands, sweat serves to regulate body temperature, hydrate the skin, and provide protection. While it is about 99% water, sweat contains essential ions like chloride, sodium, potassium, as well as trace amounts of calcium, magnesium, lactate, and other minor electrolytes. The presence of these substances offers valuable insights into a person’s health, making sweat analysis a critical tool in non-invasive health monitoring. Continuous monitoring of sweat metabolites can provide real-time data on physiological and metabolic changes, supporting personalized medicine and disease management.
For the study, sweat samples were collected from four healthy male volunteers (ages 21–24) in a temperature-controlled room set to 26°C. Although humidity was not regulated, sweat production was monitored at 1-minute intervals over a 5-minute period. The average sweat volume from these readings was used as the representative measurement. A sophisticated perspiration meter ensured accurate readings of palm sweat.
The HPLC system used in the study consisted of a PU-2080 pump, AS-950 autosampler, Inertsil ODS-4V column, a CO-965 column oven, and an FP-2020 fluorescence detector. After derivatization, samples containing varying concentrations (0.01 to 10 μM) of each amino acid were injected into the system. Calibration curves were created by plotting the ratio of the peak area of each sample to that of the internal standard, ε-amino-n-caproic acid, against the compound concentrations.
The researchers successfully quantified amino acid concentrations in human sweat samples, identifying 14 amino acids with robust validation data. They believe that their technique holds potential for non-invasive, straightforward disease screening, as it requires minimal sweat volumes, eliminating the need for excessive sweat production through exercise. Furthermore, the method could be applied to detect other biomolecules in sweat, extending its usefulness beyond amino acids.
This study highlights the potential of HPLC with fluorescence detection as a tool for non-invasive health monitoring and disease detection, offering a glimpse into future applications for personalized medicine.
References
1. Tsunoda, M.;Tsuda, T. Quantification of Amino Acids in Small Volumes of Palm Sweat Samples. Heliyon 2024, 10 (17), e36286. DOI: 10.1016/j.heliyon.2024.e36286
2. Nair, R. R.; An, J. M.; Kim, J.; Kim, D. Recent Progress in Fluorescent Molecular Systems for the Detection of Disease-Related Biomarkers in Biofluids. Coord. Chem. Rev. 2023, 494, 215336. DOI: 10.1016/j.ccr.2023.215336
3. Davis, N.; Heikenfeld, J.; Milla, C.; Javey, A. The Challenges and Promise of Sweat Sensing. Nat. Biotech. 2024, 42, 860–871. DOI: 10.1038/s41587-023-02059-1
4. Sarwar, M.; Rodriguez, P.; Li, C. Z. Sweat-Based in vitro Diagnostics (IVD): From Sample Collection to Point-of-Care Testing (POCT). J. Anal. Test. 2019, 3, 80–88. DOI: 10.1007/s41664-019-00097-w
5. Yang, D. S.; Ghaffari, R.; Rogers, J. A. Sweat as a Diagnostic Biofluid. Science 2023, 379 (6634), 760–761. DOI: 10.1126/science.abq5916
6. Brasier, Noé et al.Next-Generation Digital Biomarkers: Continuous Molecular Health Monitoring Using Wearable Devices. Trends Biotechnol. 2024, 42 (3), 255–257. DOI: 10.1016/j.tibtech.2023.12.001
7. Hussain, J. N.; Mantri, N.; Cohen, M. M. Working up a Good Sweat–The Challenges of Standardising Sweat Collection for Metabolomics Analysis. Clin. Biochem. Rev. 2017, 38 (1), 13–34.
8. Baker, L. B.; Wolfe, A. S. Physiological Mechanisms Determining Eccrine Sweat Composition. Eur. J. Appl. Physiol. 2020, 120, 719–752. DOI: 10.1007/s00421-020-04323-7
9. Tsunoda, M.; Hirayama, M.; Tsuda, T.; Ohno, K. Noninvasive Monitoring of Plasma L-dopa Concentrations Using Sweat Samples in Parkinson’s Disease. Clin. Chim. Acta 2015, 442, 52–55.DOI: 10.1016/j.cca.2014.12.032
10. Hirayama, M.; Tsunoda, M.; Yamamoto, M.; Tsuda, T.; Ohno, K. Serum Tyrosine-to-Phenylalanine Ratio is Low in Parkinson’s Disease. J. Parkinson’s Dis. 2016, 6 (2), 423–431. DOI: 10.3233/JPD-150736