Research Paper Volume 12, Issue 1 pp 740—755
Network analysis of human muscle adaptation to aging and contraction
- 1 Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX1 2LU, UK
- 2 Biosciences, University of Exeter, Exeter EX4 4QD, UK
- 3 MRC-ARUK Centre for Musculoskeletal aging Research and National Institute of Health Research, Biomedical Research Centre, Royal Derby Hospital Centre, School of Medicine, University of Nottingham, Derby DE22 3DT, UK
- 4 Department of Surgery, Postgraduate Entry Medical School, Royal Derby Hospital Centre, School of Medicine, University of Nottingham, Derby DE22 3DT, UK
- 5 School of Health Sciences, Örebro University, Örebro 70182, Sweden
received: August 29, 2019 ; accepted: December 24, 2019 ; published: January 7, 2020 ;https://doi.org/10.18632/aging.102653
How to Cite
Copyright © 2020 Willis et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Resistance exercise (RE) remains a primary approach for minimising aging muscle decline. Understanding muscle adaptation to individual contractile components of RE (eccentric, concentric) might optimise RE-based intervention strategies. Herein, we employed a network-driven pipeline to identify putative molecular drivers of muscle aging and contraction mode responses. RNA-sequencing data was generated from young (21±1 y) and older (70±1 y) human skeletal muscle before and following acute unilateral concentric and contralateral eccentric contractions. Application of weighted gene co-expression network analysis identified 33 distinct gene clusters (‘modules’) with an expression profile regulated by aging, contraction and/or linked to muscle strength. These included two contraction ‘responsive’ modules (related to ‘cell adhesion’ and ‘transcription factor’ processes) that also correlated with the magnitude of post-exercise muscle strength decline. Module searches for ‘hub’ genes and enriched transcription factor binding sites established a refined set of candidate module-regulatory molecules (536 hub genes and 60 transcription factors) as possible contributors to muscle aging and/or contraction responses. Thus, network-driven analysis can identify new molecular candidates of functional relevance to muscle aging and contraction mode adaptations.