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Genomic analysis reveals association of specific SNPs with athletic performance and susceptibility to injuries in professional soccer players
Author(s) -
Montagna Raffaele,
Caico Raffaele,
Alfano Luigi,
Bucci Enrico,
Boffo Silvia,
Staiano Leopoldo,
Fulco Beniamino,
D'Andrea Enrico,
Nicola Antonio,
Maiorano Patrizia,
D'Angelo Costantino,
Chirico Andrea,
Nicola Alfonso,
Giordano Antonio
Publication year - 2020
Publication title -
journal of cellular physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 174
eISSN - 1097-4652
pISSN - 0021-9541
DOI - 10.1002/jcp.29118
Subject(s) - athletes , context (archaeology) , single nucleotide polymorphism , medicine , physical therapy , genotype , biology , gene , genetics , paleontology
The development of specific and individualized training programs is a possible way to improve athletic performance and minimize injuries in professional athletes. The information regarding the sport's physical demands and the athletes’ physical profile have been, so far, considered as exhaustive for the design of effective training programs. However, it is currently emerging that the genetic profile has to be also taken into consideration. By merging medical and genetic data, it is thus possible to identify the athlete's specific attitude to respond to training, diet, and physical stress. In this context, we performed a study in which 30 professional soccer players, subjected to standard sport medical evaluation and practices, were also screened for genetic polymorphism in five key genes ( ACTN3, COL5A1, MCT1, VEGF , and HFE ). This genetic analysis represents the central point of a multidisciplinary method that can be adopted by elite soccer teams to obtain an improvement in athletic performance and a concomitant reduction of injuries by tailoring training and nutritional programs. The genetic fingerprinting of single athletes led to the identification of two performance‐enhancing polymorphisms (ACTN3 18705C>T, VEGF‐634C>G) significantly enriched. Moreover, we derived a genetic model based on the gene set analyzed, which was tentatively used to reduce athletes’ predisposition to injuries, by dictating a personalized nutrition and training program. The potential usefulness of this approach is concordant with data showing that this team has been classified as the healthiest and least injured team in Europe while covering the highest distance/match with the highest number of high‐intensity actions/match.