Abstract: The most significant and scientifically sound articles in exercise genomics that were published in 2013 are reviewed in this report. No article on the genetic basis of sedentary behavior or physical activity level was identified. A calcineurin- and alpha actinin-2–based mechanism has been identified as the potential molecular basis for the observed lower muscular strength and power in alpha actinin-3–deficient individuals. Although baseline muscle transcriptomic signatures were found to be associated with strength training-induced muscle hypertrophy, no predictive genomic variants could be identified as of yet. One study found no clear evidence that the inverse relation between physical activity level and incident CHD events was influenced by 58 genomic variants clustered into four genetic scores. Lower physical activity level in North American populations may be driving the apparent risk of obesity in fat mass- and obesity-associated gene (FTO)-susceptible individuals compared with more active populations. Two large studies revealed that common genetic variants associated with baseline levels of plasma HDL cholesterol and triglycerides are not clear predictors of changes induced by interventions focused on weight loss, diet, and physical activity behavior. One large study from Japan reported that a higher fitness level attenuated the arterial stiffness-promoting effect of the Ala54 allele at the fatty acid binding protein 2 locus, which is a controversial finding because previous studies have suggested that Thr54 was the risk allele. Using transcriptomics to generate genomic targets in an unbiased manner for subsequent DNA sequence variants studies appears to be a growing trend. Moreover, exercise genomics is rapidly embracing gene and pathway analysis to better define the underlying biology and provide a foundation for the study of human variation.
1Preventive and Rehabilitative Sports Medicine, Technical University Munich, Munich, GERMANY; 2Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA; 3Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD; 4The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute of Personalized Medicine, The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY; and 5Department of Kinesiology, Laval University, Ste-Foy, Québec, CANADA
Address for correspondence: Claude Bouchard, Ph.D., Human Genomics Laboratory, Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808-4124; E-mail: email@example.com.
Submitted for publication January 2013.
Accepted for publication February 2013.