TY - JOUR
T1 - Finger sweat analysis enables short interval metabolic biomonitoring in humans
AU - Brunmair, Julia
AU - Gotsmy, Mathias
AU - Niederstaetter, Laura
AU - Neuditschko, Benjamin
AU - Bileck, Andrea
AU - Slany, Astrid
AU - Feuerstein, Max Lennart
AU - Langbauer, Clemens
AU - Janker, Lukas
AU - Zanghellini, Jürgen
AU - Meier-Menches, Samuel M.
AU - Gerner, Christopher
N1 - © 2021. The Author(s).
PY - 2021/10/13
Y1 - 2021/10/13
N2 - Metabolic biomonitoring in humans is typically based on the sampling of blood, plasma or urine. Although established in the clinical routine, these sampling procedures are often associated with a variety of compliance issues, which are impeding time-course studies. Here, we show that the metabolic profiling of the minute amounts of sweat sampled from fingertips addresses this challenge. Sweat sampling from fingertips is non-invasive, robust and can be accomplished repeatedly by untrained personnel. The sweat matrix represents a rich source for metabolic phenotyping. We confirm the feasibility of short interval sampling of sweat from the fingertips in time-course studies involving the consumption of coffee or the ingestion of a caffeine capsule after a fasting interval, in which we successfully monitor all known caffeine metabolites as well as endogenous metabolic responses. Fluctuations in the rate of sweat production are accounted for by mathematical modelling to reveal individual rates of caffeine uptake, metabolism and clearance. To conclude, metabotyping using sweat from fingertips combined with mathematical network modelling shows promise for broad applications in precision medicine by enabling the assessment of dynamic metabolic patterns, which may overcome the limitations of purely compositional biomarkers.
AB - Metabolic biomonitoring in humans is typically based on the sampling of blood, plasma or urine. Although established in the clinical routine, these sampling procedures are often associated with a variety of compliance issues, which are impeding time-course studies. Here, we show that the metabolic profiling of the minute amounts of sweat sampled from fingertips addresses this challenge. Sweat sampling from fingertips is non-invasive, robust and can be accomplished repeatedly by untrained personnel. The sweat matrix represents a rich source for metabolic phenotyping. We confirm the feasibility of short interval sampling of sweat from the fingertips in time-course studies involving the consumption of coffee or the ingestion of a caffeine capsule after a fasting interval, in which we successfully monitor all known caffeine metabolites as well as endogenous metabolic responses. Fluctuations in the rate of sweat production are accounted for by mathematical modelling to reveal individual rates of caffeine uptake, metabolism and clearance. To conclude, metabotyping using sweat from fingertips combined with mathematical network modelling shows promise for broad applications in precision medicine by enabling the assessment of dynamic metabolic patterns, which may overcome the limitations of purely compositional biomarkers.
KW - Adult
KW - Biological Monitoring/methods
KW - Biotransformation
KW - Caffeine/analysis
KW - Chlorogenic Acid/analysis
KW - Chromatography, Liquid
KW - Coffee/metabolism
KW - Female
KW - Fingers
KW - Humans
KW - Male
KW - Metabolomics/methods
KW - Middle Aged
KW - Principal Component Analysis
KW - Sweat/chemistry
KW - Tandem Mass Spectrometry
KW - Theobromine/analysis
KW - Theophylline/analysis
UR - http://www.scopus.com/inward/record.url?scp=85117417982&partnerID=8YFLogxK
U2 - 10.1038/s41467-021-26245-4
DO - 10.1038/s41467-021-26245-4
M3 - Article
C2 - 34645808
AN - SCOPUS:85117417982
SN - 2041-1723
VL - 12
SP - 5993
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 5993
ER -