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. 2021 Oct 13;12:5993. doi: 10.1038/s41467-021-26245-4

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — A straight-forward workflow for sweat sampling and processing was established and successfully applied to proof-of-principle studies to investigate caffeine metabolism in an individualised fashion. a Graphical summary of the workflow including consumption of a cup of coffee or a caffeine capsule, sampling sweat from fingertips, the extraction of analytes and subsequent LC-MS/MS analysis as well as data analysis with respective durations in minutes. Panel a was modified from Servier Medical Art, licensed under a Creative Common Attribution 3.0 Generic License (http://smart.servier.com/) and BioRender (https://biorender.com/). Tf Tracefinder Software, Cd Compound Discoverer Software (both Thermo Fisher Scientific). b Extracted ion chromatograms of exemplary sweat components are shown. Based on their retention time, analytes were assigned to three groups as listed in c. c Identities of sweat constituents according to order of elution. CA chlorogenic acid, MX methylxanhine, PX paraxanthine, TB theobromine, TP theophylline, Progest. progesterone. d Principal component analysis (PCA) of finger sweat samples derived from the left (square) and right (circle) hand of three participants is depicted before and after coffee consumption at two different days (light and dark colour). PCA was calculated with a set of 250 metabolites (Supplementary Data 1) and successfully clustered the finger sweat samples according to the participants.