Purpose: The aim of the current study was to construct a genetic model with a new algorithm for predicting athletic-performance variability based on genetic variations.
Methods: The influence of 6 polymorphisms (ACE, ACTN-3, BDKRB2, VDR-ApaI, VDR-BsmI, and VDR-FokI) on vertical jump was studied in top-level male Italian soccer players (n = 90). First, the authors calculated the traditional total genotype score and then determined the total weighting genotype score (TWGS), which accounts for the proportion of significant phenotypic variance predicted by the polymorphisms. Genomic DNA was extracted from saliva samples using a standard protocol. Genotyping was performed using polymerase chain reaction (PCR).
Results: The results obtained from the new genetic model (TWGS) showed that only 3 polymorphisms entered the regression equation (ACTN-3, ACE, and BDKRB2), and these polymorphisms explained 17.68-24.24% of the vertical-jump variance. With the weighting given to each polymorphism, it may be possible to identify a polygenic profile that more accurately explains, at least in part, the individual variance of athletic-performance traits.
Conclusions: This model may be used to create individualized training programs based on a player's genetic predispositions, as well as to identify athletes who need an adapted training routine to account for individual susceptibility to injury.