Interindividual- and blood-correlated sweat phenylalanine multimodal analytical biochips for tracking exercise metabolism

Bowen Zhong, Xiaokun Qin, Hao Xu, Lingchen Liu, Linlin Li, Zhexin Li, Limin Cao, Zheng Lou, Joshua A. Jackman, Nam-Joon Cho and Lili Wang ()
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Bowen Zhong: Institute of Semiconductors, Chinese Academy of Sciences
Xiaokun Qin: Institute of Semiconductors, Chinese Academy of Sciences
Hao Xu: Institute of Semiconductors, Chinese Academy of Sciences
Lingchen Liu: Institute of Semiconductors, Chinese Academy of Sciences
Linlin Li: Institute of Semiconductors, Chinese Academy of Sciences
Zhexin Li: Institute of Semiconductors, Chinese Academy of Sciences
Limin Cao: Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital
Zheng Lou: Institute of Semiconductors, Chinese Academy of Sciences
Joshua A. Jackman: Sungkyunkwan University
Nam-Joon Cho: Nanyang Technological University
Lili Wang: Institute of Semiconductors, Chinese Academy of Sciences

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract In situ monitoring of endogenous amino acid loss through sweat can provide physiological insights into health and metabolism. However, existing amino acid biosensors are unable to quantitatively assess metabolic status during exercise and are rarely used to establish blood-sweat correlations because they only detect a single concentration indicator and disregard sweat rate. Here, we present a wearable multimodal biochip integrated with advanced electrochemical electrodes and multipurpose microfluidic channels that enables simultaneous quantification of multiple sweat indicators, including phenylalanine and chloride, as well as sweat rate. This combined measurement approach reveals a negative correlation between sweat phenylalanine levels and sweat rates among individuals, which further enables identification of individuals at high metabolic risk. By tracking phenylalanine fluctuations induced by protein intake during exercise and normalizing the concentration indicator by sweat rates to reduce interindividual variability, we demonstrate a reliable method to correlate and analyze sweat-blood phenylalanine levels for personal health monitoring.

Date: 2024
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DOI: 10.1038/s41467-024-44751-z

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