The Exercise Regime of the Future Needs to Check Your Genes
Credit: Stocksnap via Pixabay
Exercise in the future could be customized for individuals based on genomics, according to a study by Arizona State University (ASU) and the Translational Genomics Research Institute (TGen), an affiliate of City of Hope.
For years, scientists have studied the effects of different types of exercise on the human body, but never before at this level of molecular precision, according to the TGen-ASU study published in the Journal of Applied Physiology.
“We hope to leverage these findings into more precise exercise recommendations in the future — ones that are tailored to an individual not only based on their physiological needs but also based on their molecular response to exercise,” said Dr. Matt Huentelman, professor in TGen’s Neurogenomics Division, and one of the study’s senior authors.
This study begins to characterize some of the molecular changes that happen in muscle tissue following different types of exercise, specifically resistance exercise (lifting weights), versus that of aerobic exercise (in this study, cycling).
Researchers used advanced technology — whole-transcriptome RNA sequencing — to identify genes that were affected uniquely by each type of exercise. Muscle samples were obtained from six men, ages 27-30, before their exercises, and again at 1 hour and 4 hours following both weight lifting and cycling.
The study found 48 unique genes following aerobic exercise, and 348 unique genes following weight lifting, that were “differentially expressed,” meaning the exercises made the genes more powerful or less powerful, like a dimmer switch on a chandelier.
“These data show that different exercises elicit unique molecular activity in skeletal muscle,” said Dr. Jared Dickinson, an assistant professor in the ASU College of Health Solutions, and the study’s lead author. “These findings support the need for additional research that better identifies how exercise strategies can be used to target specific molecular responses in the muscle tissue, which could have implications for those that suffer from abnormalities in muscle.”
By better understanding the unique molecular processes stimulated by different types of exercise, the researchers hope to find better ways to promote muscle health. They also maintain that this research could lead to more effective exercise interventions that target abnormalities associated with specific muscle dysfunctions.
A very important aspect of the study was the use of RNA sequencing, which provided: a broader range of analysis, especially for genes expressed at low levels; increased specificity; and the ability to identify novel genes that otherwise might not be detected through lesser technologies.
The study also found that aerobic exercise increased expression of one specific gene associated with greater oxygen capacity. The ESRRG gene improved endurance, enhanced development of blood vessels and was also important in improving function of mitochondria, the powerhouse of cells.
This article has been republished from materials provided by the Translational Genomics Research Institute (TGen). Note: material may have been edited for length and content. For further information, please contact the cited source.
Reference: Dickinson, J. M., D’Lugos, A. C., Naymik, M. A., Siniard, A. L., Wolfe, A. J., Curtis, D. P., … Carroll, C. C. (2018). Transcriptome response of human skeletal muscle to divergent exercise stimuli. Journal of Applied Physiology (Bethesda, Md.: 1985). https://doi.org/10.1152/japplphysiol.00014.2018
Mechanism Controlling Multiple Sclerosis Risk IdentifiedNews
Researchers at Karolinska Institutet have now discovered a new mechanism of a major risk gene for multiple sclerosis (MS) that triggers disease through so-called epigenetic regulation. They also found a protective genetic variant that reduces the risk for MS through the same mechanism.
Synthetic DNA Shuffling Enzyme Outpaces Natural CounterpartNews
A new synthetic enzyme, crafted from DNA rather than protein, flips lipid molecules within the cell membrane, triggering a signal pathway that could be harnessed to induce cell death in cancer cells. Researchers say their lipid-scrambling DNA enzyme is the first in its class to outperform naturally occurring enzymes – and does so by three orders of magnitudeREAD MORE
Antarctic Worm and Machine Learning Help Identify Cerebral Palsy EarlierNews
A research team has released a study in the peer-reviewed journal BMC Bioinformatics showing that DNA methylation patterns in circulating blood cells can be used to help identify spastic cerebral palsy (CP) patients. The technique which makes use of machine learning, data science and even analysis of Antarctic worms, raises hopes for earlier targeted CP therapies.