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.

Photoplethysmography-derived pulse rate variability (PPG-derived PRV) is increasingly used in wearable and camera-based biomedical sensors as a low-burden alternative to electrocardiography-derived heart rate variability (ECG-derived HRV), but its agreement with ECG-derived measurements remains uncertain. This systematic review and meta-analysis evaluated the accuracy of PPG-derived PRV compared with ECG-derived HRV in healthy or apparently healthy non-clinical populations, focusing on the root mean square of successive differences (RMSSD) and the standard deviation of normal-to-normal intervals (SDNN). Forty-three studies were included in the qualitative synthesis; 33 were summarized narratively, and 10 unique studies provided sufficient data for quantitative synthesis. Eight studies contributed to each RMSSD and SDNN meta-analysis. The pooled absolute standardized error was 0.188 (95% CI: 0.066 to 0.309; I² = 11.69%) for RMSSD and 0.134 (95% CI: 0.014 to 0.255; I² = 0%) for SDNN. Sensitivity analyses supported the robustness of RMSSD findings, whereas SDNN estimates were directionally stable but less robust in statistical significance. Because the quantitative synthesis included only 10 studies and was based predominantly on selected resting or controlled conditions, the pooled estimates should not be generalized to sleep, exercise, stress, or free-living settings or interpreted as evidence of interchangeability.

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.