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Genomic and transcriptomic predictors of response levels to endurance exercise training
Author(s) -
Sarzynski Mark A.,
Ghosh Sujoy,
Bouchard Claude
Publication year - 2016
Publication title -
the journal of physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.802
H-Index - 240
eISSN - 1469-7793
pISSN - 0022-3751
DOI - 10.1113/jp272559
Subject(s) - cardiorespiratory fitness , heritability , vo2 max , endurance training , genome wide association study , biology , skeletal muscle , transcriptome , phenotype , genetics , gene , computational biology , bioinformatics , physiology , single nucleotide polymorphism , heart rate , gene expression , endocrinology , genotype , blood pressure
Predicting the responsiveness to regular exercise is a topic of great relevance due to its potential role in personalized exercise medicine applications. The present review focuses on cardiorespiratory fitness (commonly measured by maximal oxygen uptake,V ̇O 2 max), a trait with wide‐ranging impact on health and performance indicators. Gains inV ̇O 2 maxdemonstrate large inter‐individual variation even in response to standardized exercise training programmes. The estimated Δ V O 2maxheritability of 47% suggests that genomic‐based predictors alone are insufficient to account for the total trainability variance. Candidate gene and genome‐wide linkage studies have not significantly contributed to our understanding of the molecular basis of trainability. A genome‐wide association study suggested thatV ̇O 2 maxtrainability is influenced by multiple genes of small effects, but these findings still await rigorous replication. Valuable evidence, however, has been obtained by combining skeletal muscle transcript abundance profiles with common DNA variants for the prediction of theV ̇O 2 maxresponse to exercise training. Although the physiological determinants ofV ̇O 2 maxmeasured at a given time are largely enunciated, what is poorly understood are the details of tissue‐specific molecular mechanisms that limitV ̇O 2 maxand related signalling pathways in response to exercise training. Bioinformatics explorations based on thousands of variants have been used to interrogate pathways and systems instead of single variants and genes, and the main findings, along with those from exercise experimental studies, have been summarized here in a working model ofV ̇O 2 maxtrainability.