Muscle hypertrophy is the increase in the size of the transverse diameter of muscle fibers. Although the mechanisms and signaling pathways that regulate hypertrophy are known, it is still unclear how much genetics and epigenetics contribute to this process; whether both mechanisms participate jointly, or whether there is a more significant influence of one event than the other. Therefore, this study aimed to extensively review the literature and determine the role of genes and epigenetic mechanisms in regulating muscle hypertrophy associated with physical activity and sport. For this purpose, the Scopus and ScienceDirect databases were reviewed, and the PubMed and Google Scholar search engines were used, where 25 articles met the inclusion criteria. Results demonstrated that there are several regulatory genes of muscle hypertrophy, such as MSTN, PGC-1 α, STARS, and JunB, among others, as well as genetic polymorphisms and vital participation of DNA methylation, which together would control signaling pathways and gene networks necessary for the development of this process.

Special exercises are routinely used to monitor strength qualities in weightlifting when recent maximal snatch and clean-and-jerk performances are unavailable. This study developed and internally assessed an exploratory model for estimating a training total from special-exercise strength measures while accounting for sex and body mass. Retrospective records from 27 senior high-performance weightlifters (14 men and 13 women) were analyzed. The training total was calculated from the most recent maximal snatch and clean-and-jerk records obtained within an approximately two-week precompetition window. Simple and partial correlations, hierarchical linear regression, collinearity diagnostics, residual analyses, and leave-one-out cross-validation were examined. Sex and body mass explained 94.3% of the variance. Adding front squat and strict military press increased explained variance to 97.9% and reduced the standard error of estimate from 16.58 to 10.52 kg. The internally assessed RMSE was 11.47 kg and MAE was 9.25 kg; however, front squat showed substantial collinearity. The model may provide a provisional monitoring reference under comparable conditions, but the small sample, predictor selection within the same dataset, collinearity, and absence of external validation preclude treating it as a confirmed predictive equation.