Prediction and Identification of Power Performance Using Polygenic Models of Three Single-Nucleotide Polymorphisms in Chinese Elite Athletes

Genetics and athletic performance: a systematic SWOT analysis of non-systematic reviews

Exercise genetics/genomics is a growing research discipline comprising several Strengths and Opportunities but also deals with Weaknesses and Threats. This "systematic SWOT overview of non-systematic reviews" (sSWOT) aimed to identify the Strengths, Weaknesses, Opportunities, and Threats linked to exercise genetics/genomics. A systematic search was conducted in the Medline and Embase databases for non-systematic reviews to provide a comprehensive overview of the current literature/research area. The extracted data was thematically analyzed, coded, and categorized into SWOT clusters. In the 45 included reviews five Strengths, nine Weaknesses, six Opportunities, and three Threats were identified. The cluster of Strengths included "advances in technology", "empirical evidence", "growing research discipline", the "establishment of consortia", and the "acceptance/accessibility of genetic testing". The Weaknesses were linked to a "low research quality", the "complexity of exercise-related traits", "low generalizability", "high costs", "genotype scores", "reporting bias", "invasive methods", "research progress", and "causality". The Opportunities comprised of "precision exercise", "omics", "multicenter studies", as well as "genetic testing" as "commercial"-, "screening"-, and "anti-doping" detection tool. The Threats were related to "ethical issues", "direct-to-consumer genetic testing companies", and "gene doping". This overview of the present state of the art research in sport genetics/genomics indicates a field with great potential, while also drawing attention to the necessity for additional advancement in methodological and ethical guidance to mitigate the recognized Weaknesses and Threats. The recognized Strengths and Opportunities substantiate the capability of genetics/genomics to make significant contributions to the performance and wellbeing of athletes.

Effects of the Trp64Arg Polymorphism in the ADRB3 Gene on Body Composition, Cardiorespiratory Fitness, and Physical Activity in Healthy Adults

The ADRB3 gene plays a role in energy expenditure by participating in lipolysis, which affects body composition and performance. The ADRB3 rs4994 polymorphism has been studied in groups of athletes, overweight individuals, and obese and diabetic patients, but it has not been studied in young and healthy adults so far. In the present study, we examined the association of ADRB3 rs4994 polymorphism with body composition, somatotype, cardiorespiratory fitness and physical activity in young, healthy adults (N = 304). All subjects had anthropometric measurements, and somatotypes were assessed using the Heath-Carter method. In addition, cardiorespiratory fitness and physical activity levels were assessed. Genotyping for the ADRB3 gene was performed using a PCR-RFLP method. In the male group, body components were associated with the Trp64Trp genotype (waist circumference (p = 0.035), hip circumference (p = 0.029), BF (%) (p = 0.008), and BF (kg) (p = 0.010), BMI (p = 0.005), WHtR (p = 0.021), and BAI (p = 0.006)). In addition, we observed that the Trp64Trp genotype was associated with somatotype components (p = 0.013). In contrast, the Arg allele was associated with the ectomorphic components (0.006). We also observed a positive impact of the Trp64Trp genotype with maximal oxygen uptake (p= 0.023) and oxygen pulse (p = 0.024). We observed a negative relationship of the Trp64Trp genotype in the female group with reported moderate-intensity exercise (p = 0.036). In conclusion, we found an association of the Trp64 allele with anthropometric traits, somatotype and parameters describing physical performance in the male group. In the female subpopulation, we only found an effect of the polymorphism Trp64Arg on the level of physical activity for moderate-intensity exercise.

Genes and Athletic Performance: The 2023 Update

Phenotypes of athletic performance and exercise capacity are complex traits influenced by both genetic and environmental factors. This update on the panel of genetic markers (DNA polymorphisms) associated with athlete status summarises recent advances in sports genomics research, including findings from candidate gene and genome-wide association (GWAS) studies, meta-analyses, and findings involving larger-scale initiatives such as the UK Biobank. As of the end of May 2023, a total of 251 DNA polymorphisms have been associated with athlete status, of which 128 genetic markers were positively associated with athlete status in at least two studies (41 endurance-related, 45 power-related, and 42 strength-related). The most promising genetic markers include the AMPD1 rs17602729 C, CDKN1A rs236448 A, HFE rs1799945 G, MYBPC3 rs1052373 G, NFIA-AS2 rs1572312 C, PPARA rs4253778 G, and PPARGC1A rs8192678 G alleles for endurance; ACTN3 rs1815739 C, AMPD1 rs17602729 C, CDKN1A rs236448 C, CPNE5 rs3213537 G, GALNTL6 rs558129 T, IGF2 rs680 G, IGSF3 rs699785 A, NOS3 rs2070744 T, and TRHR rs7832552 T alleles for power; and ACTN3 rs1815739 C, AR ≥21 CAG repeats, LRPPRC rs10186876 A, MMS22L rs9320823 T, PHACTR1 rs6905419 C, and PPARG rs1801282 G alleles for strength. It should be appreciated, however, that elite performance still cannot be predicted well using only genetic testing.

An Association Between FNDC5, PGC-1α Genetic Variants and Obesity in Chinese Children: A Case-Control Study

BACKGROUND

Fibronectin type III domain containing protein 5 (FNDC5) gene encodes irisin that regulates adipose tissue metabolism. Peroxide-proliferator-activated receptor γ coactivator 1α (PGC-1α) is a powerful promoter of mitochondrial biosynthesis and oxidative metabolism, which plays an important role in inducing heat production and energy consumption of brown fat. PGC1-α expression stimulated an increase in expression of FNDC5.

PURPOSE

The aims of this study were to analyze the association between FNDC5, PGC-1α genetic variants and overweight or obesity in Chinese children and adolescents.

METHODS

A total of 198 children and adolescents with overweight or obesity and 198 children and adolescents with normal weight were screened according to gender and age 1:1. The healthy eating behaviors, moderate-to-vigorous physical activity time were surveyed using food frequency questionnaire and CLASS questionnaire, respectively. Genotypes of FNDC5 and PGC-1α gene were detected using SNaPshot method.

RESULTS

GT genotype of FNDC5 (rs16835198) increased the risk of overweight or obesity in boys (OR (95% CI): 1.68 (1.00, 2.93)) based on overdominant model; GG genotype of FNDC5 (rs16835198) decreased the risk of overweight or obesity in girls and boys (OR (95% CI): 0.45 (0.21,0.97), 0.45 (0.24, 0.83), respectively) based on dominant model; TT genotype of FNDC5 (rs16835198) increased the risk of overweight or obesity in girls based on recessive model (OR (95% CI): 2.46 (1.19, 5.05)), and based on the additive model (OR (95% CI): 3.82 (1.49, 9.80)). There was significant interaction between FNDC5 (rs16835198) and PGC-1α (rs3755863, rs8192678), healthy eating behaviors, moderate-to-vigorous physical activity time, interaction between PGC-1α (rs8192678) and moderate-to-vigorous physical activity time in the occurrence of overweight or obesity in Chinese children and adolescents.

CONCLUSION

FNDC5 (rs16835198) played an independent or interactive role with PGC-1α (rs3755863, rs8192678), healthy eating behaviors, moderate-to-vigorous physical activity time in the occurrence of overweight or obesity in Chinese children and adolescents.

The Athlete's Heart-Challenges and Controversies: JACC Focus Seminar 4/4

Regular exercise promotes structural, functional, and electrical remodeling of the heart, often referred to as the "athlete's heart," with intense endurance sports being associated with the greatest degree of cardiac remodeling. However, the extremes of exercise-induced cardiac remodeling are potentially associated with uncommon side effects. Atrial fibrillation is more common among endurance athletes and there is speculation that other arrhythmias may also be more prevalent. It is yet to be determined whether this arrhythmic susceptibility is a result of extreme exercise remodeling, genetic predisposition, or other factors. Gender may have the greatest influence on the cardiac response to exercise, but there has been far too little research directed at understanding differences in the sportsman's vs sportswoman's heart. Here in part 4 of a 4-part seminar series, the controversies and ambiguities regarding the athlete's heart, and in particular, its arrhythmic predisposition, genetic, and gender influences are reviewed in depth.

Blood Metabolomics Analysis Identifies Differential Serum Metabolites in Elite and Sub-elite Swimmers

Objective: Metabolites in body fluids, such as lactate, glucose, and creatinine, have been measured by conventional methods to evaluate physical function and performance or athletic status. The objectives of the current study were to explore the novel metabolite biomarkers in professional swimmers with different competition levels using nuclear magnetic resonance (NMR) metabolomics, and try to establish a model to identify the athletic status or predict the competitive potential.

Methods: Serum samples were collected from 103 elite and 84 sub-elite level Chinese professional swimmers, and were profiled by NMR analysis.

Results: Out of the thirty-six serum metabolites profiled, ten were associated with the athletic status of swimmers (with p < 0.05). When compared with sub-elite swimmers, elite swimmers had higher levels of high-density lipoprotein (HDL), unsaturated fatty acid, lactic acid, and methanol. Elite swimmers had lower levels of isoleucine, 3-hydroxybutyric acid, acetoacetate, glutamine, glycine, and α-glucose. A model with four metabolites, including HDL, glutamine, methanol, and α-glucose, was established to predict athletic status by adjusting with different covariates. The area under the curve (AUC) of the best model was 0.904 (95% CI: 0.862-0.947), with a sensitivity and specificity of 75.5 and 90.2%, respectively.

Conclusion: We have identified ten metabolite biomarkers with differentially expressed levels between elite and sub-elite swimmers, the differences could result from genetic or sports level between the two cohorts. A model with four metabolites has successfully differentiated professional swimmers with different competitive levels.