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Med Sci Sports Exerc. 2018 Feb;50(2):361-368. doi: 10.1249/MSS.0000000000001434.

Genetic Variants and Hamstring Injury in Soccer: An Association and Validation Study.

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Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, SPAIN.



This study aimed to investigate the association of candidate single nucleotide polymorphisms (SNP) with noncontact hamstring muscle injuries in elite soccer players and to create and validate a model to assess the risk of hamstring injury.


A total of 107 elite male outfield players were prospectively followed for six seasons. Players were genotyped for 37 SNP previously investigated in relation to musculoskeletal injuries. The association of SNP, previous injury, age, level of play, position, and anthropometric data with 129 hamstring injuries (413 observations) was investigated in the discovery phase (2010-2015), and a multivariable Cox frailty model was created using forward selection. The model's discriminative ability was tested in the validation phase (2015-2016, 31 injuries, 98 observations) using Harrell's C index.


Five SNP were found to be significantly associated with hamstring injury in a multivariable model: matrix metalloproteinase 3 rs679620 (A vs G, hazard ratio [HR] = 2.06, 95% confidence interval [CI] = 1.51-2.81), tenascin C rs2104772 (A vs T, HR = 1.65, 95% CI = 1.17-2.32), interleukin 6 rs1800795 (GG vs GC + CC, HR = 1.68, 95% CI = 1.11-2.53), nitric oxide synthase 3 rs1799983 (G vs T, HR = 1.35, 95% CI = 1.01-1.79), and hypoxia-inducible factor-1α rs11549465 (CC vs CT, HR = 2.08, 95% CI = 1.00-4.29). Age also entered the model (≥24 vs <24 yr, HR = 2.10, 95% CI = 1.29-3.42). The model showed acceptable discrimination in the discovery phase (C index = 0.74), but not in the validation phase (C index = 0.52).


Genetic variants appear to be involved in the etiology of hamstring injuries but were not found to have predictive value by themselves. Further research, increasing the number of genetic variants and including environmental factors in complex multifactorial risk models, is necessary.

[Indexed for MEDLINE]

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