A machine-learning algorithm integrating baseline serum proteomic signatures predicts exercise responsiveness in overweight males with prediabetes

Candela Diaz-Canestro; Jiarui Chen; Yan Liu; Hao Han; Yao Wang; Eric Honoré; Chi-Ho Lee; Karen S L Lam; Michael Andrew Tse; Aimin Xu

doi:10.1016/j.xcrm.2023.100944

A machine-learning algorithm integrating baseline serum proteomic signatures predicts exercise responsiveness in overweight males with prediabetes

Cell Rep Med. 2023 Feb 21;4(2):100944. doi: 10.1016/j.xcrm.2023.100944. Epub 2023 Feb 13.

Authors

Affiliations

¹ State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China; Department of Medicine, The University of Hong Kong, Hong Kong, China.
² Université Côte d'Azur, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médicale, Institut de Pharmacologie Moléculaire et Cellulaire, Labex ICST, Valbonne, France.
³ State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China; Centre for Sports and Exercise, The University of Hong Kong, Hong Kong, China. Electronic address: matse@hku.hk.
⁴ State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China; Department of Medicine, The University of Hong Kong, Hong Kong, China; Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong, China. Electronic address: amxu@hku.hk.

Abstract

The molecular transducers conferring the benefits of chronic exercise in diabetes prevention remain to be comprehensively investigated. Herein, serum proteomic profiling of 688 inflammatory and metabolic biomarkers in 36 medication-naive overweight and obese men with prediabetes reveals hundreds of exercise-responsive proteins modulated by 12-week high-intensity interval exercise training, including regulators of metabolism, cardiovascular system, inflammation, and apoptosis. Strong associations are found between proteins involved in gastro-intestinal mucosal immunity and metabolic outcomes. Exercise-induced changes in trefoil factor 2 (TFF2) are associated with changes in insulin resistance and fasting insulin, whereas baseline levels of the pancreatic secretory granule membrane major glycoprotein GP2 are related to changes in fasting glucose and glucose tolerance. A hybrid set of 23 proteins including TFF2 are differentially altered in exercise responders and non-responders. Furthermore, a machine-learning algorithm integrating baseline proteomic signatures accurately predicts individualized metabolic responsiveness to exercise training.

Keywords: exercise; insulin resistance; machine learning algorithm; metabolic outcomes; personalized medicine; prediabetes; proteomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Exercise
Glucose
Humans
Male
Overweight*
Prediabetic State*
Proteomics

Substances

Glucose