Frontiers in Genetics (Nov 2022)

Genetic profile in genes associated with muscle injuries and injury etiology in professional soccer players

  • Antonio Maestro,
  • Juan Del Coso,
  • Millán Aguilar-Navarro,
  • Jorge Gutiérrez-Hellín,
  • Esther Morencos,
  • Gonzalo Revuelta,
  • Eva Ruiz Casares,
  • Eva Ruiz Casares,
  • Teresa Perucho,
  • Teresa Perucho,
  • David Varillas-Delgado

DOI
https://doi.org/10.3389/fgene.2022.1035899
Journal volume & issue
Vol. 13

Abstract

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Many causes define injuries in professional soccer players. In recent years, the study of genetics in association with injuries has been of great interest. The purpose of this study was to examine the relationship between muscle injury-related genes, injury risk and injury etiology in professional soccer players. In a cross-sectional cohort study, one hundred and twenty-two male professional football players were recruited. AMPD1 (rs17602729), ACE (rs4646994), ACTN3 (rs1815739), CKM (rs8111989) and MLCK (rs2849757 and rs2700352) polymorphisms were genotyped by using Single Nucleotide Primer Extension (SNPE). The combined influence of the six polymorphisms studied was calculated using a total genotype score (TGS). A genotype score (GS) of 2 was assigned to the “protective” genotype for injuries, a GS of 1 was assigned to the heterozygous genotype while a GS of 0 was assigned to the “worst” genotype. Injury characteristics and etiology during the 2021/2022 season were classified following a Consensus Statement for injuries recording. The distribution of allelic frequencies in the AMPD1 and MLCK c.37885C>A polymorphisms were different between non-injured and injured soccer players (p < 0.001 and p = 0.003, respectively). The mean total genotype score (TGS) in non-injured soccer players (57.18 ± 14.43 arbitrary units [a.u.]) was different from that of injured soccer players (51.71 ± 12.82 a.u., p = 0.034). There was a TGS cut-off point (45.83 a.u.) to discriminate non-injured from injured soccer players. Players with a TGS beyond this cut-off had an odds ratio of 1.91 (95%CI: 1.14–2.91; p = 0.022) to suffer an injury when compared with players with lower TGS. In conclusion, TGS analysis in muscle injury-related genes presented a relationship with professional soccer players at increased risk of injury. Future studies will help to develop this TGS as a potential tool to predict injury risk and perform prevention methodology in this cohort of football players.

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