Abstract
There has been limited research on genome-wide association with physical activity (PA). This study ascertained genetic associations between PA and 344,893 single nucleotide polymorphism (SNP) markers in 8842 Korean samples. PA data were obtained from a validated questionnaire that included information on PA intensity and duration. Metabolic equivalent of tasks were calculated to estimate the total daily PA level for each individual. In addition to single- and multiple-SNP association tests, a pathway enrichment analysis was performed to identify the biological significance of SNP markers. Although no significant SNP was found at genome-wide significance level via single-SNP association tests, 59 genetic variants mapped to 76 genes were identified via a multiple SNP approach using a bootstrap selection stability measure. Pathway analysis for these 59 variants showed that maturity onset diabetes of the young (MODY) was enriched. Joint identification of SNPs could enable the identification of multiple SNPs with good predictive power for PA and a pathway enriched for PA.
Highlights
Physical activity (PA) is any bodily movement produced by skeletal muscles that requires energy expenditure [1]
A novel approach has been proposed to identify genetic variants that are related to leisure-time exercise behavior, by conducting Genome-Wide Association (GWA) analyses using logistic regression to find genes associated with exercisers and non-exercisers [7]
Was higher than that of the Ansan cohort (1038, SD 534 metabolic equivalent task (MET)·min·day−1), suggesting that people in the rural community tended to be more active than their city counterparts
Summary
Physical activity (PA) is any bodily movement produced by skeletal muscles that requires energy expenditure [1]. It includes exercise as well as work and recreational activities which involve bodily movements. The behavior of PA may be determined by genetic factors [4,5,6]. 71% of the variability in adult exercise behavior can be explained by genetic factors [6]. A novel approach has been proposed to identify genetic variants that are related to leisure-time exercise behavior, by conducting Genome-Wide Association (GWA) analyses using logistic regression to find genes associated with exercisers and non-exercisers [7]. A genome-wide study with quantitative PA as a phenotype was performed for the Korean population [8]
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