Time trajectories in the transcriptomic response to exercise - a meta-analysis

Nat Commun. 2021 Jun 9;12(1):3471. doi: 10.1038/s41467-021-23579-x.


Exercise training prevents multiple diseases, yet the molecular mechanisms that drive exercise adaptation are incompletely understood. To address this, we create a computational framework comprising data from skeletal muscle or blood from 43 studies, including 739 individuals before and after exercise or training. Using linear mixed effects meta-regression, we detect specific time patterns and regulatory modulators of the exercise response. Acute and long-term responses are transcriptionally distinct and we identify SMAD3 as a central regulator of the exercise response. Exercise induces a more pronounced inflammatory response in skeletal muscle of older individuals and our models reveal multiple sex-associated responses. We validate seven of our top genes in a separate human cohort. In this work, we provide a powerful resource ( www.extrameta.org ) that expands the transcriptional landscape of exercise adaptation by extending previously known responses and their regulatory networks, and identifying novel modality-, time-, age-, and sex-associated changes.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adaptation, Physiological / genetics
  • Age Factors
  • Endurance Training
  • Exercise / physiology*
  • Extracellular Matrix Proteins / genetics
  • Gene Regulatory Networks
  • Humans
  • Inflammation / genetics
  • Muscle, Skeletal / physiology
  • Reproducibility of Results
  • Resistance Training
  • Smad3 Protein / genetics
  • Systems Biology
  • Time Factors
  • Transcriptome*


  • Extracellular Matrix Proteins
  • SMAD3 protein, human
  • Smad3 Protein