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The aim of the current study was to investigate interindividual differences in muscle thickness of the rectus femoris (MTRF) following 12 wk of resistance training (RT) or high-intensity interval training (HIIT) to explore the genetic architecture underlying skeletal muscle hypertrophy and to construct predictive models. We conducted musculoskeletal ultrasound assessments of the MTRF response in 440 physically inactive adults after the 12-wk exercise period. A genome-wide association study was used to identify variants associated with the MTRF response, separately for RT and HIIT. Using the polygenic predictor score (PPS), we estimated the genetic contribution to exercise-induced hypertrophy. Predictive models for the MTRF response were constructed using random forest (RF), support vector mac (SVM), and generalized linear model (GLM) in 10 cross-validated approaches. MTRF increased significantly after both RT (8.8%, P < 0.05) and HIIT (5.3%, P < 0.05), but with considerable interindividual differences (RT: −13.5 to 38.4%, HIIT: −14.2 to 30.7%). Eleven lead single-nucleotide polymorphisms in RT and eight lead single-nucleotide polymorphisms in HIIT were identified at a significance level of P < 1 × 10−5. The PPS was associated with the MTRF response, explaining 47.2% of the variation in response to RT and 38.3% of the variation in response to HIIT. Notably, the GLM and SVM predictive models exhibited superior performance compared with RF models (P < 0.05), and the GLM demonstrated optimal performance with an area under curve of 0.809 (95% confidence interval: 0.669–0.949). Factors such as PPS, baseline MTRF, and exercise protocol exerted influence on the MTRF response to exercise, with PPS being the primary contributor. The GLM and SVM predictive model, incorporating both genetic and phenotypic factors, emerged as promising tools for predicting exercise-induced skeletal muscle hypertrophy. NEW & NOTEWORTHY: The interindividual variability induced muscle hypertrophy by resistance training (RT) or high-intensity interval training (HIIT) and the associated genetic architecture remain uncertain. We identified genetic variants that underlie RT- or HIIT-induced muscle hypertrophy and established them as pivotal factors influencing the response regardless of the training type. The genetic-phenotype predictive model developed has the potential to identify nonresponders or individuals with low responsiveness before engaging in exercise training. [ABSTRACT FROM AUTHOR]

Recent research has analyzed the genetic factors that influence world-class athletic status. Much of what we know comes from association studies, with the ACE I/D and ACTN3 R577X polymorphisms having been extensively studied. The association between the ACTN3 R577X variation and elite athlete status in power sports is strongly documented, yet whether the current body of knowledge on other variants can be extrapolated to athletic champion status remains to be determined. Athletic champion status is a complex polygenic trait in which numerous candidate genes, complex gene-gene interactions, and environment—gene interactions are involved. Besides the need for more studies and new approaches taking into account the complexity of the problem, we believe that factors beyond genetic endowment are likely to have a stronger influence in the attainment of athletic champion status. [ABSTRACT FROM AUTHOR]

Cardiorespiratory fitness, as assessed through peak oxygen uptake (VO2peak), is a powerful health indicator. We aimed to evaluate the influence of several candidate causal genetic variants on VO2peak level in untrained Han Chinese people. A total of 1009 participants (566 women; age [mean ± SD] 40 ± 14 years, VO2peak 29.9 ± 7.1 mL/kg/min) performed a maximal incremental cycling test for VO2peak determination. Genomic DNA was extracted from peripheral whole blood, and genotyping analysis was performed on 125 gene variants. Using age, sex, and body mass as covariates, and setting a stringent threshold p-value of 0.0004, only one single nucleotide polymorphism (SNP), located in the gene encoding angiotensin-converting enzyme (rs4295), was associated with VO2peak (β = 0.87; p < 2.9 × 10−4). Stepwise multiple regression analysis identified a panel of three SNPs (rs4295 = 1.1%, angiotensin II receptor type 1 rs275652 = 0.6%, and myostatin rs7570532 = 0.5%) that together accounted for 2.2% (p = 0.0007) of the interindividual variance in VO2peak. Participants carrying six 'favorable' alleles had a higher VO2peak (32.3 ± 8.1 mL/kg/min) than those carrying only one favorable allele (24.6 ± 5.2 mL/kg/min, p < 0.0001). In summary, VO2peak at the pre-trained state is partly influenced by several polymorphic variations in candidate genes, but they represent a minor portion of the variance. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to analyze the interindividual differences of the maximal oxygen uptake (V̇O 2max ) response to 12 wk of high-intensity interval training (HIIT), and the genotype-phenotype models were constructed to predict the effect of HIIT on V̇O 2max ., Methods: A total of 228 physically inactive adults who completed a 12-wk HIIT were analyzed. A genome-wide association study (GWAS) was conducted to identify genetic variants associated with the V̇O 2max response. Nonresponders, responders, and the highest training responders were defined as the effect sizes (ES) <0.2, ≥0.2, and ≥0.8, respectively. We generated polygenic predictor score (PPS) using lead variants and constructed a predictive model for V̇O 2max response based on a linear stepwise regression analysis., Results: The V̇O 2max increased significantly after HIIT (~14%, P < 0.001), but with interindividual differences (-7.8 to 17.9 mL·kg -1 ·min -1 ). In 27% of participants, the V̇O 2max showed no improvement. We identified one genetic locus near the γ-aminobutyric acid type A receptor subunit beta 3 gene ( GABRB3 , rs17116985) associated with V̇O 2max response at the genome-wide significance level ( P < 5 × 10 -8 ), and an additional nine single nucleotide polymorphisms (SNPs) at the suggestive significance level ( P < 1 × 10 -5 ). The SNPs rs474377, rs9365605, and rs17116985, respectively, explained 11%, 9%, and 6.2% of variance in V̇O 2max response. The 13 SNPs ( P < 1 × 10 -5 ) were found on chromosome 6 (position: 148209316-148223568). Individuals with a PPS greater than 1.757 had the highest response, and those with a PPS lower than -3.712 were nonresponders. The PPS, baseline V̇O 2max , sex, and body mass explained 56.4% of the variance in the V̇O 2max response; the major predictor was the PPS, which explained 39.4% of the variance., Conclusions: The PPS, baseline V̇O 2max , sex, and body mass could explain the variance in V̇O 2max response. Individuals who had a PPS greater than 1.757 had the highest training response after 12 wk of HIIT. Genetic variants in a region on chromosome 6, especially the sterile alpha motif domain containing 5 gene ( SAMD5 ), which had been explored influencing angiogenesis, might have a potential role in the V̇O 2max response., (Copyright © 2023 by the American College of Sports Medicine.)