Genetic Profile in Genes Associated with Sports Injuries in Elite
                    Endurance Athletes

David Varillas-Delgado; Jorge Gutierrez-Hellín; Antonio Maestro

doi:10.1055/a-1917-9212

International Journal of Sports Medicine, Table of Contents

Int J Sports Med 2023; 44(01): 64-71
DOI: 10.1055/a-1917-9212

Genetics and Molecular Biology

Genetic Profile in Genes Associated with Sports Injuries in Elite Endurance Athletes

Authors

David Varillas-Delgado

¹Faculty of Health Sciences, Universidad Francisco de Vitoria, Pozuelo de Alarcon, Spain
Jorge Gutierrez-Hellín

¹Faculty of Health Sciences, Universidad Francisco de Vitoria, Pozuelo de Alarcon, Spain
Antonio Maestro

²Faculty of Medicine, University of Oviedo, Oviedo, Spain

Abstract

Injuries are a complex trait that can stem from the interaction of several genes. The aim of this research was to examine the relationship between muscle performance-related genes and overuse injury risk in elite endurance athletes, and to examine the feasibility of determining a total genotype score that significantly correlates with injury. A cohort of 100 elite endurance athletes (50 male and 50 female) was selected. AMPD1 (rs17602729), ACE (rs4646994), ACTN3 (rs1815739), CKM (rs8111989) and MLCK ([rs2849757] and [rs2700352]) polymorphisms were genotyped by using real-time polymerase chain reaction (real time-PCR). Injury characteristics during the athletic season were classified following the Consensus Statement for injuries evaluation. The mean total genotype score (TGS) in non-injured athletes (68.263±13.197 arbitrary units [a.u.]) was different from that of injured athletes (50.037±17.293 a.u., p<0.001). The distribution of allelic frequencies in the AMPD1 polymorphism was also different between non-injured and injured athletes (p<0.001). There was a TGS cut-off point (59.085 a.u.) to discriminate non-injured from injured athletes with an odds ratio of 7.400 (95% CI 2.548–21.495, p<0.001). TGS analysis appears to correlate with elite endurance athletes at higher risk for injury. Further study may help to develop this as one potential tool to help predict injury risk in this population.

Key words

athletic performance - muscle performance - genes - injuries - single-nucleotide polymorphisms

Full Text

References

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