Randall F. D'Souza, Thomas Bjørnsen, Nina Zeng, Kirsten M. M. Aasen, Truls Raastad, David Cameron-Smith, Cameron J. Mitchell
Abstract
Powerlifters are the epitome of muscular adaptation and are able to generate extreme forces. The molecular mechanisms underpinning the significant capacity for force generation and hypertrophy are not fully elucidated. MicroRNAs (miRs) are short non-coding RNA sequences that control gene expression via promotion of transcript breakdown and/or translational inhibition. Differences in basal miR expression may partially account for phenotypic differences in muscle mass and function between powerlifters and untrained age-matched controls. Muscle biopsies were obtained from m. vastus lateralis of 15 national level powerlifters (25.1 ± 5.8 years) and 13 untrained controls (24.1 ± 2.0 years). The powerlifters were stronger than the controls (isokinetic knee extension at 60°/s: 307.8 ± 51.6 Nm vs. 211.9 ± 41.9 Nm, respectively P < 0.001), and also had larger muscle fibers (type I CSA 9,122 ± 1,238 vs. 4,511 ± 798 μm(2)p < 0.001 and type II CSA 11,100 ± 1,656 vs. 5,468 ± 1,477 μm(2)p < 0.001). Of the 17 miRs species analyzed, 12 were differently expressed (p < 0.05) between groups with 7 being more abundant in powerlifters and five having lower expression. Established transcriptionally regulated miR downstream gene targets involved in muscle mass regulation, including myostatin and MyoD, were also differentially expressed between groups. Correlation analysis demonstrates the abundance of eight miRs was correlated to phenotype including peak strength, fiber size, satellite cell abundance, and fiber type regardless of grouping. The unique miR expression profiles between groups allow for categorization of individuals as either powerlifter or healthy controls based on a five miR signature (miR-126, -23b, -16, -23a, -15a) with considerable accuracy (100%). Thus, this unique miR expression may be important to the characterization of the powerlifter phenotype.
This research output has an Altmetric Attention Score of 21. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 November 2019.
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#36
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Altmetric has tracked 24,766,831 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
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