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Obesity-Related Genetic Variants and their Associations with Physical Activity

BACKGROUND: Meta-analysis of genome-wide association studies identified obesity-related genetic variants. Due to the pleiotropic effects of related phenotypes, we tested six of these obesity-related genetic variants for their association with physical activity: fat mass and obesity-associated (FTO)(...

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Detalles Bibliográficos
Autores principales: Lee, Harold, Ash, Garrett I., Angelopoulos, Theodore J., Gordon, Paul M., Moyna, Niall M., Visich, Paul S., Zoeller, Robert F., Gordish-Dressman, Heather, Deshpande, Ved, Chen, Ming-Hui, Thompson, Paul D., Hoffman, Eric P., Devaney, Joseph M., Pescatello, Linda S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4607705/
https://www.ncbi.nlm.nih.gov/pubmed/26495240
http://dx.doi.org/10.1186/s40798-015-0036-6
Descripción
Sumario:BACKGROUND: Meta-analysis of genome-wide association studies identified obesity-related genetic variants. Due to the pleiotropic effects of related phenotypes, we tested six of these obesity-related genetic variants for their association with physical activity: fat mass and obesity-associated (FTO)(rs9939609)T>A, potassium channel tetramerization domain containing (KCTD15) (rs11084753)G>A, melanocortin receptor4 (MC4R)(rs17782313)T>C, neuronal growth regulator 1 (NEGR1)(rs2815752)A>G, SH2B adapter protein 1 (SH2B1)(rs7498665)A>G, and transmembrane protein18 (TMEM18)(rs6548238)C>T. METHOD: European-American women (n = 263) and men (n = 229) (23.5 ± 0.3 years, 24.6 ± 0.2 kg/m(2)) were genotyped and completed the Paffenbarger physical activity Questionnaire. Physical activity volume in metabolic energy equivalents [MET]-hour/week was derived from the summed time spent (hour/week) times the given MET value for vigorous, moderate, and light intensity physical activity, and sitting and sleeping, respectively. Multivariable adjusted [(age, sex, and body mass index (BMI)] linear regression tested associations among genotype (dominant/recessive model) and the log of physical activity volume. RESULT: MC4R (rs17782313)T>C explained 1.1 % (p = 0.02), TMEM18(rs6548238)C>T 1.2 % (p = 0.01), and SH2B1 (rs7498665)A>G 0.6 % (p = 0.08) of the variability in physical activity volume. Subjects with the MC4R C allele spent 3.5 % less MET-hour/week than those with the TT genotype (p = 0.02). Subjects with the TMEM18 T allele spent 4.1 % less MET-hour/week than those with the CC genotype (p = 0.01). Finally, subjects with the SH2B1 GG genotype spent 3.6 % less MET-hour/week than A allele carriers (p = 0.08). CONCLUSION: Our findings suggest a shared genetic influence among some obesity-related gene loci and physical activity phenotypes that should be explored further. Physical activity volume differences by genotype have public health importance equating to 11–13 lb weight difference annually.