Exercise is well known to prevent disease and improve health, yet the molecular mechanisms through which it achieves these outcomes are not well understood. Many smaller studies have been performed, but it is difficult to find small biological changes using information from few participants. Furthermore, the data from these studies usually cannot be directly combined with each other due to variation in study methods and participant characteristics. Without considering variables during the data analysis process like the type of exercise intervention used, or the sex and age of the participants, it is impossible to accurately understand which molecular changes are due to biological variation and which result from the exercise training.

The Molecular Transducers of Physical Activity in Humans (MoTrPAC) program is conducting what will be the largest study of its kind, recruiting participants of different ages, sexes, racial/ethnic backgrounds, and activity levels to study the effects of endurance and resistance exercise at the molecular level. The MoTrPAC Bioinformatics Center (BIC) is readying its data analysis toolbox to find meaning in the vast amounts of data the program will generate (publicly available here). Part of this effort includes examining the data from previous exercise studies that looked at the transcriptome of exercisers. The transcriptome is the collection of RNA sequences transcribed from DNA that are present in the cells or tissue being analyzed. These RNA transcripts reflect gene activity patterns at a specific timepoint and give valuable insight into the behavior of cells and tissue in response to exercise.

The BIC team, led by Dr. Euan Ashley, systematically analyzed transcriptome data sets from previous studies through a meta-analysis, which is a specialized way of combining results from multiple studies to yield often more powerful findings. The research team created a pipeline to combine and analyze data from 43 previous human exercise training studies. The pipeline considered the differences both in the study protocols and in the volunteers who were studied. The results of the researchers’ meta-analysis substantially expand our knowledge of how gene activity patterns vary in people of different sexes and ages in response to short- and long-term exercise training programs. By using a meta-analysis, the authors uncovered biological pathways involved in the response to long-term exercise interventions that small individual studies did not previously catalog. The researchers also made it possible for others to add to their findings by sharing all their results in more detail through an open access, online resource (www.extrameta.org). The meta-analysis technique and its findings bring us one step closer to the goal of enabling clinicians in the future to make personalized exercise recommendations to patients to improve their health.

Reference:

Time trajectories in the transcriptomic response to exercise - a meta-analysis. Amar D, Lindholm ME, Norrbom J, Wheeler MT, Rivas MA, Ashley EA. Nature Communications. 2021 Jun 9;12(1):3471. doi: 10.1038/s41467-021-23579-x.