Carbohydrate supplementation is a common practice among endurance athletes participating in long-distance competitions. However, glycogen storage regulation, in-competition blood glucose levels, and their relationship with athletic performance are influenced by multiple factors. This review summarizes the recent research progress on carbohydrate supplementation, addressing its applications in the pre-, during-, and post-competition phases. It explores variables that influence the effectiveness of carbohydrate supplementation and provides a summary of strategies, based on six key aspects: carbohydrate properties, multi-nutrient interactions, gastrointestinal function, individual differences (such as age and gender), environmental conditions, and psychological factors. The combination of different types, ratios, and concentrations of carbohydrates has been demonstrated to enhance the efficiency of carbohydrate digestion and absorption. The synergistic combination of protein, sodium, and caffeine intake demonstrates enhanced efficacy in carbohydrate supplementation strategies. Gastrointestinal tolerance training for carbohydrate supplementation has been identified as an effective measure to alleviate gastrointestinal discomfort during high-dose carbohydrate intake. The adjustment of the carbohydrate-to-fat ratio and the type of carbohydrate intake has been found to mitigate the impact of gender and menstrual cycles on glycogen storage and substrate utilization. Modifying the timing of glycogen storage and regulating the concentration and temperature of carbohydrate solutions during competition have been demonstrated to facilitate coping with the elevated energy expenditure and metabolic substrate shift from fat to carbohydrates, triggered by a combination of environmental and psychological factors, including special environmental and climatic conditions (e.g., high altitude, high temperature, high humidity, and cold) and emotional states (e.g., pre-competition stress and anxiety during the competition). To achieve precise carbohydrate supplementation for athletes in major events under various competitive environments, it is necessary to quantitatively assess the effects of carbohydrate supplementation, supported by mechanistic studies. This can be achieved by utilizing wearable devices to monitor the entire competition, coupled with data collection technologies, such as high-throughput profiling. Furthermore, emerging data analytics techniques, such as machine learning and causal inference, should be leveraged to refine supplementation strategies.

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.

Objectives: The aim of this study was to assess the relationship between variant loci significantly associated with sports-related traits in the GWAS Catalog database and sprint/power athlete status, as well as to explore the polygenic profile of elite athletes. Methods: Next-generation sequencing and microarray technology were used to genotype samples from 211 elite athletes who had achieved success in national or international competitions in power-based sports and from 522 non-athletes, who were healthy university students with no history of professional sports training. Variant loci collected from databases were extracted after imputation. Subsequently, 80% of the samples were randomly selected as the training set, and the remaining 20% as the validation set. Results: Association analysis of variant loci was conducted in the training set, and individual Total Genotype Score (TGS) were calculated using genotype dosage and lnOR, followed by the establishment of a logistic model, with predictive performance evaluated in the validation set. Association analysis was performed on 2075 variant loci, and after removing linked loci (r² > 0.2), 118 Tag SNPs (p ≤ 0.05) were identified. A logistic model built using 30 Tag SNPs (p ≤ 0.01) showed better performance in the validation set (AUC = 0.707). Conclusions: Our study identified 30 new genetic molecular markers and demonstrated that elite sprint/power athlete status is polygenic.

This study develops a comprehensive genotype-phenotype model for predicting the effects of resistance training on leg press performance. A cohort of physically inactive adults (N=193) underwent 12 weeks of resistance training, and measurements of maximum isokinetic leg press peak force, muscle mass, and thickness were taken before and after the intervention. Whole-genome genotyping was performed, and genome-wide association analysis identified 85 novel SNPs significantly associated with changes in leg press strength after training. A prediction model was constructed using stepwise linear regression, incorporating seven lead SNPs that explained 40.4% of the training effect variance. The polygenic score showed a significant positive correlation with changes in leg press strength. By integrating genomic markers and phenotypic indicators, the comprehensive prediction model explained 75.4% of the variance in the training effect. Additionally, five SNPs were found to potentially impact muscle contraction, metabolism, growth, and development through their association with REACTOME pathways. Individual responses to resistance training varied, with changes in leg press strength ranging from −55.83% to 151.20%. The study highlights the importance of genetic factors in predicting training outcomes and provides insights into the potential biological functions underlying resistance training effects. The comprehensive model offers valuable guidance for personalized fitness programs based on individual genetic profiles and phenotypic characteristics.

Background/Objectives: To investigate associations between Follistatin (FST) gene polymorphisms (SNPs) and baseline musculoskeletal traits, and their interactions with 16-week exercise interventions. Methods: A cohort of 470 untrained Northern Han Chinese adults (208 males, 262 females), sourced from the “Research on Key Technologies for an Exercise and Fitness Expert Guidance System” project, was analyzed. These participants were previously randomly assigned to one of four exercise groups (Hill, Running, Cycling, Combined) or a non-exercising Control group, and completed their respective 16-week protocols. Body composition, bone mineral content (BMC), bone mineral density (BMD), and serum follistatin levels were all assessed pre- and post-intervention. Dual-energy X-ray absorptiometry (DXA) was utilized for the body composition, BMC, and BMD measurements. FST SNPs (rs3797296, rs3797297) were genotyped using matrix assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-TOF MS) or microarrays. To elucidate the biological mechanisms, we performed in silico functional analyses for rs3797296 and rs3797297. Results: Baseline: In females only, the rs3797297 T allele was associated with higher muscle mass (β = 1.159, 95% confidence interval (CI): 0.202–2.116, P_{_adj} = 0.034) and BMC (β = 0.127, 95% CI: 0.039–0.215, P_{_adj} = 0.009), with the BMC effect significantly mediated by muscle mass. Exercise Response: Interventions improved body composition, particularly in females. Gene-Exercise Interaction: A significant interaction occurred exclusively in women undertaking hill climbing: the rs3797296 G allele was associated with attenuated muscle mass gains (β = −1.126 kg, 95% CI: −1.767 to −0.485, P_{_adj} = 0.034). Baseline follistatin correlated with body composition (stronger in males) and increased post-exercise (primarily in males, Hill/Running groups) but did not mediate SNP effects on exercise adaptation. Functional annotation revealed that rs3797297 is a likely causal variant, acting as a skeletal muscle eQTL for the mitochondrial gene NDUFS4, suggesting a mechanism involving muscle bioenergetics. Conclusions: Findings indicate that FST polymorphisms associate with musculoskeletal traits in Northern Han Chinese. Mechanistic insights from functional annotation reveal potential pathways for these associations, highlighting the potential utility of these genetic markers for optimizing training program design.

This study aimed to explore genetic variants associated with serum albumin (ALB) levels in Chinese winter sports athletes using genome-wide association analysis (GWAS) and to investigate potential regulatory mechanisms using bioinformatics annotation. A total of 382 Chinese winter sports athletes were recruited. ALB levels were compared between elite and non-elite athletes. GWAS was conducted using PLINK v1.9, with ALB as the phenotype and sex, age, and principal components as covariates. Associated SNPs were annotated using GTEx and SNPnexus. No significant differences were observed in ALB levels between elite and non-elite male or female athletes, and ALB levels in all groups followed a normal distribution. We identified 113 SNPs reaching a suggestive significance threshold (p < 1 × 10⁻⁵), with per-variant variance explained estimates (7.11–11.76%) reflecting model fit within this cohort. A stepwise regression model highlighted nine candidate SNPs that together explained 51.1% of ALB variance in the study sample. Functional annotation suggested that several variants show eQTL or sQTL signals in tissues relevant to ALB biology (e.g., liver and kidney), and pathway enrichment analyses implicated amino acid and hormone metabolism. Overall, these findings are hypothesis-generating; independent replication in additional and ancestry-matched cohorts (and follow-up functional studies) is required to confirm the robustness of the associations and clarify causal mechanisms.