Factors affecting muscle fiber size in athletes

Biomedical Basis of Elite Performance 2022 (University of Nottingham, UK) (2022) Proc Physiol Soc 49, OC2

Oral Communications: Factors affecting muscle fiber size in athletes

Ildus Ahmetov1,2, Ekaterina Semenova2,3, Andrey Larin2, Evgeny Lysenko4, Tatiana Vepkhvadze4, Egor Lednev4, Daniil Popov4, Edward Generozov2

1 Liverpool John Moores University 2 Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency 3 Volga Region State University of Physical Culture, Sport and Tourism 4 Institute of Biomedical Problems of the Russian Academy of Sciences

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Introduction: Muscle fiber cross-sectional area (CSA) significantly contributes to gains in strength after resistance training, and can be affected by numerous factors, including genetics, age, nutrition, training parameters and habits. However, the majority of research seems to include only males in the sampled cohort. The aim of the study was to identify the associations between various factors and muscle fiber CSA of the vastus lateralis in 157 physically active subjects. Methods: The retrospective, observational study involved 55 power-trained (19 females) and 102 endurance-trained (27 females) subjects. Athletes’ nutrition, training parameters and habits were recorded using a survey. Muscle fiber composition and CSA of m. vastus lateralis were determined by immunohistochemistry. Genotyping was performed using micro-array analysis. This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Federal Research and Clinical Center of Physical-chemical Medicine. Written informed consent was obtained from each participant. Results: As expected, power-trained subjects had significantly greater fast- and slow-twitch muscle fiber CSA than endurance-trained subjects (P<0.05). In female power-trained subjects, the CSA of the fast-twitch muscle fibers negatively correlated with age (r=-0.48, P=0.037), but positively associated with training frequency (r=0.68, P=0.0014), protein/BCAA intake (r=0.46, P=0.046), meat consumption (r=0.65, P=0.0028), water consumption (r=0.48, P=0.037) and sleep duration (r=0.48, P=0.039). Multiple regression analysis showed that these factors explained 76.6% of fast-twitch muscle fiber CSA variation in female power-trained subjects. In female endurance-trained subjects, only sleep duration (r=0.52, P=0.0059) reported a significant interrelation with CSA of the fast-twitch muscle fibers. In the whole group (n=157), the CSA of the fast-twitch muscle fibers negatively correlated with age (r=–0.26, P=0.0011) and alcohol consumption (r=–0.17, P=0.032). Furthermore, in the combined group of male and female endurance-trained subjects, the CSA of the fast-twitch muscle fibers positively correlated with creatine consumption (r=0.24, P=0.015). Next, using two panels of DNA-markers associated with fat-free mass (1981 SNPs) and testosterone levels (855 SNPs) in the UK Biobank cohort, we identified that 40 SNPs (rs11632750, rs12040325, rs12564492, rs12602084, rs1321080, rs13237404, rs1480474, rs150352963, rs1582931, rs190930099, rs2227138, rs2241388, rs2306862, rs2595104, rs26866, rs2926247, rs343935, rs34706136, rs3803573, rs4309038, rs4665244, rs6121042, rs62260729, rs693906, rs6988769, rs7184768, rs72630041, rs73198802, rs77031559, rs7727774, rs7740107, rs8086627, rs8192589, rs850294, rs853985, rs9268249, rs9271657, rs9291834, rs9329259, rs9599996) were significantly (P<0.05) associated with both CSA of the fast-twitch muscle fibers in our group (n=157) and handgrip strength in the UK Biobank cohort. Conclusions: These results demonstrate that genetics, training parameters, nutrition and habits are associated with muscle fiber CSA in physically active subjects.



Where applicable, experiments conform with Society ethical requirements.

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