He, L, Van Roie, E, Bogaerts, A, Morse, CI, Delecluse, C, Verschueren, S and Thomis, M (2018) Genetic predisposition score predicts the increases of knee strength and muscle mass after one-year exercise in healthy elderly. Experimental Gerontology, 111. pp. 17-26. ISSN 0531-5565
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Abstract
This study aims to identify a genetic predisposition score from a set of candidate gene variants that predicts the response to a one-year exercise intervention. 200 participants (aged 60–83 years) were randomly assigned to a fitness (FIT), whole-body vibration (WBV) and control group. Participants in the exercise (FIT and WBV) groups performed a one-year intervention program. Whole-body skeletal muscle mass (SMM) and isometric knee extension strength (PTIM60) were measured before and after the intervention. A set of 170 muscle-related single nucleotide polymorphisms (SNPs) were genotyped. Stepwise regression analysis was applied to select significantly contributing SNPs for baseline and relative change parameters. A data-driven genetic predisposition score (GPS) was calculated by adding up predisposing alleles for each of the phenotypes. GPS was calculated based on 4 to 8 SNPs which were significantly related to the corresponding phenotypes. These SNPs belong to genes that are involved in myoblast differentiation, muscle and bone growth, myofiber contraction, cytokines and DNA methylation. GPS was related to baseline PTIM60and relative changes of SMM and PTIM60in the exercise groups, explaining the variance of the corresponding parameter by 3.2%, 14% and 27%, respectively. Adding one increasing allele in the GPS increased baseline PTIM60by 4.73 Nm, and exercise-induced relative changes of SMM and PTIM60by 1.78% and 3.86% respectively. The identified genetic predisposition scores were positively related to baseline knee extension strength and muscle adaptations to exercise in healthy elderly. These findings provide supportive genetic explanations for high and low responders in exercise-induced muscle adaptations.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.