exercise health lifestyle

Genes Predisposing To Active Lifestyle Likely Identified

MedicalResearch.com Interview with:

Marcel den Hoed, PhD Researcher,Department of Immunology, Genetics and Pathology Uppsala University

Dr. den Hoed

Marcel den Hoed, PhD
Researcher,Department of Immunology, Genetics and Pathology
Uppsala University

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: In this paper we performed a multi-ancestry meta-analysis of 51 genome-wide association studies, in data from over 700,000 individuals. This yielded 11 DNA regions that are robustly associated with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), and 88 DNA regions for self-reported leisure screen time (LST).

Around half of the identified DNA regions are also associated with objectively assessed physical activity traits in data from the UK Biobank. Causal inference using a Mendelian randomization approach subsequently showed bidirectional causal effects between LST and body mass index (BMI), with the effect of LST on BMI being 2-3-fold larger than vice versa. Less LST and more MVPA protect from diabetes, attention deficit hyperactivity disorder, depression, and earlier age at death, with all causal effects of MVPA and leisure screen time being mediated or confounded by BMI. Further analyses showed that DNA regions associated with LST are more often located close to genes whose expression in skeletal muscle is altered by strength training than expected by chance, suggesting that these genes may influence the likelihood of adopting an active lifestyle by influencing the response to training.


This enrichment analysis and six other approaches used to prioritize candidate genes – including overlapping loci with a GWAS for spontaneous physical activity in 100 mouse strains – yielded 46 genes in the associated DNA regions that were prioritized by at least two approaches. Together, these genes point to locomotion and myopathy as likely relevant pathways.

Finally, we identified a missense variant in the gene encoding alpha-actinin 3 that is associated with MVPA. Alpha-actinin 3 is a structural / elastic element that is only expressed in fast twitch skeletal muscle fibers. Haplotype analyses, molecular dynamics simulations and single fiber experiments in human muscle biopsies suggest that in the presence of the ancestral allele of this DNA variant, the alpha-actinin 3 element is stiffer and the muscle fiber can deliver a higher maximal force than in the presence of the other allele, which is associated with higher levels of physical activity. We think the more flexible version of the protein is less susceptible to exercise induced muscle damage and thereby facilitates a more physically active lifestyle.

Response: The first take home message of our report is that a physically active lifestyle has beneficial health effects that appear to be mediated by its effect on body mass.

The second important point is that we have improved our understanding of the molecular mechanisms that influence daily physical activity, which was previously very poorly understood.

MedicalResearch.com: What recommendations do you have for future research as a results of this study?

Response: We hope the 46 candidate genes we prioritized in physical activity-associated DNA regions will give researchers interested in studying the molecular background of physical activity a new starting point from which to further improve our understanding of this complex behaviour, as we have done for the variant in the gene encoding alpha-actinin 3.

MedicalResearch.com: Is there anything else you would like to add? Any disclosures?

Response: An important point to mention for genome-wide association studies in general is that the variance explained in the outcome (here MVPA and LST) that is explained by the common DNA variants that are studied is typically low. In our case, the 88 DNA regions associated with LST together explain only 2.75% of its variance. This implies that our results cannot be used to predict whether someone will be physically active or not. They can however help us identify genes that play a role, and improve our understanding of the mechanisms that influence physical activity. Maybe one day this information may even make it possible to enjoy some of the benefits of physical activity without the need to be physically active, e.g., through pharmacological intervention. 

Wang, Z., Emmerich, A., Pillon, N.J. et al. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention. Nat Genet (2022). https://doi.org/10.1038/s41588-022-01165-1

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