Literature DB >> 27183119

Advances in Exercise, Fitness, and Performance Genomics in 2015.

Mark A Sarzynski1, Ruth J F Loos, Alejandro Lucia, Louis Pérusse, Stephen M Roth, Bernd Wolfarth, Tuomo Rankinen, Claude Bouchard.   

Abstract

This review of the exercise genomics literature encompasses the highest-quality articles published in 2015 across seven broad topics: physical activity behavior, muscular strength and power, cardiorespiratory fitness and endurance performance, body weight and adiposity, insulin and glucose metabolism, lipid and lipoprotein metabolism, and hemodynamic traits. One study used a quantitative trait locus for wheel running in mice to identify single nucleotide polymorphisms (SNPs) in humans associated with physical activity levels. Two studies examined the association of candidate gene ACTN3 R577X genotype on muscular performance. Several studies examined gene-physical activity interactions on cardiometabolic traits. One study showed that physical inactivity exacerbated the body mass index (BMI)-increasing effect of an FTO SNP but only in individuals of European ancestry, whereas another showed that high-density lipoprotein cholesterol (HDL-C) SNPs from genome-wide association studies exerted a smaller effect in active individuals. Increased levels of moderate-to-vigorous-intensity physical activity were associated with higher Matsuda insulin sensitivity index in PPARG Ala12 carriers but not Pro12 homozygotes. One study combined genome-wide and transcriptome-wide profiling to identify genes and SNPs associated with the response of triglycerides (TG) to exercise training. The genome-wide association study results showed that four SNPs accounted for all of the heritability of △TG, whereas the baseline expression of 11 genes predicted 27% of △TG. A composite SNP score based on the top eight SNPs derived from the genomic and transcriptomic analyses was the strongest predictor of ΔTG, explaining 14% of the variance. The review concludes with a discussion of a conceptual framework defining some of the critical conditions for exercise genomics studies and highlights the importance of the recently launched National Institutes of Health Common Fund program titled "Molecular Transducers of Physical Activity in Humans."

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27183119     DOI: 10.1249/MSS.0000000000000982

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  19 in total

Review 1.  Metabolomics, physical activity, exercise and health: A review of the current evidence.

Authors:  Rachel S Kelly; Michael P Kelly; Paul Kelly
Journal:  Biochim Biophys Acta Mol Basis Dis       Date:  2020-08-19       Impact factor: 5.187

Review 2.  Programming Plyometric-Jump Training in Soccer: A Review.

Authors:  Rodrigo Ramirez-Campillo; Jason Moran; Jon L Oliver; Jason S Pedley; Rhodri S Lloyd; Urs Granacher
Journal:  Sports (Basel)       Date:  2022-06-10

3.  Exercise Physiology From 1980 to 2020: Application of the Natural Sciences.

Authors:  Jane A Kent; Kate L Hayes
Journal:  Kinesiol Rev (Champaign)       Date:  2021-06-30

4.  Genetic Basis of Aerobically Supported Voluntary Exercise: Results from a Selection Experiment with House Mice.

Authors:  David A Hillis; Liran Yadgary; George M Weinstock; Fernando Pardo-Manuel de Villena; Daniel Pomp; Alexandra S Fowler; Shizhong Xu; Frank Chan; Theodore Garland
Journal:  Genetics       Date:  2020-09-25       Impact factor: 4.562

5.  Preface: genomics and biology of exercise is undergoing a paradigm shift.

Authors:  Nir Eynon; Sarah Voisin; Alejandro Lucia; Guan Wang; Yannis Pitsiladis
Journal:  BMC Genomics       Date:  2017-11-14       Impact factor: 3.969

6.  Both Light Intensity and Moderate-to-Vigorous Physical Activity Measured by Accelerometry Are Favorably Associated With Cardiometabolic Risk Factors in Older Women: The Objective Physical Activity and Cardiovascular Health (OPACH) Study.

Authors:  Michael J LaMonte; Cora E Lewis; David M Buchner; Kelly R Evenson; Eileen Rillamas-Sun; Chongzhi Di; I-Min Lee; John Bellettiere; Marcia L Stefanick; Charles B Eaton; Barbara V Howard; Chloe Bird; Andrea Z LaCroix
Journal:  J Am Heart Assoc       Date:  2017-10-17       Impact factor: 5.501

7.  Letter to the editor: A genetic-based algorithm for personalized resistance training.

Authors:  A Karanikolou; G Wang; Y Pitsiladis
Journal:  Biol Sport       Date:  2016-11-11       Impact factor: 2.806

8.  Long-term leisure-time physical activity and other health habits as predictors of objectively monitored late-life physical activity - A 40-year twin study.

Authors:  Katja Waller; Henri Vähä-Ypyä; Timo Törmäkangas; Pekka Hautasaari; Noora Lindgren; Paula Iso-Markku; Kauko Heikkilä; Juha Rinne; Jaakko Kaprio; Harri Sievänen; Urho M Kujala
Journal:  Sci Rep       Date:  2018-06-20       Impact factor: 4.379

9.  Microfluidic Quantitative PCR Detection of 12 Transgenes from Horse Plasma for Gene Doping Control.

Authors:  Teruaki Tozaki; Aoi Ohnuma; Mio Kikuchi; Taichiro Ishige; Hironaga Kakoi; Kei-Ichi Hirota; Kanichi Kusano; Shun-Ichi Nagata
Journal:  Genes (Basel)       Date:  2020-04-23       Impact factor: 4.096

10.  A meta-analysis of the association of CKM gene rs8111989 polymorphism with sport performance.

Authors:  Chunyang Chen; Yan Sun; Hao Liang; Dan Yu; Songnian Hu
Journal:  Biol Sport       Date:  2017-09-01       Impact factor: 2.806

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.