Can Genetic Testing Predict Talent? A Case Study of 5 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.

Genetics of long-distance runners and road cyclists-A systematic review with meta-analysis

The aim of this systematic review and meta-analysis was to identify the genetic variants of (inter)national competing long-distance runners and road cyclists compared with controls. The Medline and Embase databases were searched until 15 November 2021. Eligible articles included genetic epidemiological studies published in English. A homogenous group of endurance athletes competing at (inter)national level and sedentary controls were included. Pooled odds ratios based on the genotype frequency with corresponding 95% confidence intervals (95%CI) were calculated using random effects models. Heterogeneity was addressed by Q-statistics, and I² . Sources of heterogeneity were examined by meta-regression and risk of bias was assessed with the Clark Baudouin scale. This systematic review comprised of 43 studies including a total of 3938 athletes and 10 752 controls in the pooled analysis. Of the 42 identified genetic variants, 13 were investigated in independent studies. Significant associations were found for five polymorphisms. Pooled odds ratio [95%CI] favoring athletes compared with controls was 1.42 [1.12-1.81] for ACE II (I/D), 1.66 [1.26-2.19] for ACTN3 TT (rs1815739), 1.75 [1.34-2.29] for PPARGC1A GG (rs8192678), 2.23 [1.42-3.51] for AMPD1 CC (rs17602729), and 2.85 [1.27-6.39] for HFE GG + CG (rs1799945). Risk of bias was low in 25 (58%) and unclear in 18 (42%) articles. Heterogeneity of the results was low (0%-20%) except for HFE (71%), GNB3 (80%), and NOS3 (76%). (Inter)national competing runners and cyclists have a higher probability to carry specific genetic variants compared with controls. This study confirms that (inter)national competing endurance athletes constitute a unique genetic make-up, which likely contributes to their performance level.

Genetic profiles to identify talents in elite endurance athletes and professional football players

The genetic profile that is needed to identify talents has been studied extensively in recent years. The main objective of this investigation was to approach, for the first time, the study of genetic variants in several polygenic profiles and their role in elite endurance and professional football performance by comparing the allelic and genotypic frequencies to the non-athlete population. In this study, genotypic and allelic frequencies were determined in 452 subjects: 292 professional athletes (160 elite endurance athletes and 132 professional football players) and 160 non-athlete subjects. Genotyping of polymorphisms in liver metabolisers (CYP2D6, GSTM1, GSTP and GSTT), iron metabolism and energy efficiency (HFE, AMPD1 and PGC1a), cardiorespiratory fitness (ACE, NOS3, ADRA2A, ADRB2 and BDKRB2) and muscle injuries (ACE, ACTN3, AMPD1, CKM and MLCK) was performed by Polymerase Chain Reaction-Single Nucleotide Primer Extension (PCR-SNPE). The combination of the polymorphisms for the “optimal” polygenic profile was quantified using the genotype score (GS) and total genotype score (TGS). Statistical differences were found in the genetic distributions between professional athletes and the non-athlete population in liver metabolism, iron metabolism and energy efficiency, and muscle injuries (p<0.001). The binary logistic regression model showed a favourable OR (odds ratio) of being a professional athlete against a non-athlete in liver metabolism (OR: 1.96; 95% CI: 1.28–3.01; p = 0.002), iron metabolism and energy efficiency (OR: 2.21; 95% CI: 1.42–3.43; p < 0.001), and muscle injuries (OR: 2.70; 95% CI: 1.75–4.16; p < 0.001) in the polymorphisms studied. Genetic distribution in professional athletes as regards endurance (professional cyclists and elite runners) and professional football players shows genetic selection in these sports disciplines.

The Relationship between ACE, ACTN3 and MCT1 Genetic Polymorphisms and Athletic Performance in Elite Rugby Union Players: A Preliminary Study

Athletic performance is influenced by many factors such as the environment, diet, training and endurance or speed in physical effort and by genetic predisposition. Just a few studies have analyzed the impact of genotypes on physical performance in rugby. The aim of this study was to verify the modulation of genetic influence on rugby-specific physical performance. Twenty-seven elite rugby union players were involved in the study during the in-season phase. Molecular genotyping was performed for: angiotensin-converting enzyme (ACE rs4646994), alfa-actinin-3 (ACTN3 rs1815739) and monocarboxylate transporter 1 (MCT1 rs1049434) and their variants. Lean mass index (from skinfolds), lower-limb explosive power (countermovement jump), agility (505), speed (20 m), maximal aerobic power (Yo-yo intermittent recovery test level 1) and repeated sprint ability (12 × 20 m) were evaluated. In our rugby union players ACE and ACTN3 variants did not show any influence on athletic performance. MCT1 analysis showed that TT-variant players had the highest peak vertical power (p = 0.037) while the ones with the AA genotype were the fastest in both agility and sprint tests (p = 0.006 and p = 0.012, respectively). Considering the T-dominant model, the AA genotype remains the fastest in both tests (agility: p = 0.013, speed: p = 0.017). Only the MCT1 rs1049434 A allele seems to be advantageous for elite rugby union players, particularly when power and speed are required.

Genetics and sports performance: the present and future in the identification of talent for sports based on DNA testing

The impact of genetics on physiology and sports performance is one of the most debated research aspects in sports sciences. Nearly 200 genetic polymorphisms have been found to influence sports performance traits, and over 20 polymorphisms may condition the status of the elite athlete. However, with the current evidence, it is certainly too early a stage to determine how to use genotyping as a tool for predicting exercise/sports performance or improving current methods of training. Research on this topic presents methodological limitations such as the lack of measurement of valid exercise performance phenotypes that make the study results difficult to interpret. Additionally, many studies present an insufficient cohort of athletes, or their classification as elite is dubious, which may introduce expectancy effects. Finally, the assessment of a progressively higher number of polymorphisms in the studies and the introduction of new analysis tools, such as the total genotype score (TGS) and genome-wide association studies (GWAS), have produced a considerable advance in the power of the analyses and a change from the study of single variants to determine pathways and systems associated with performance. The purpose of the present study was to comprehensively review evidence on the impact of genetics on endurance- and power-based exercise performance to clearly determine the potential utility of genotyping for detecting sports talent, enhancing training, or preventing exercise-related injuries, and to present an overview of recent research that has attempted to correct the methodological issues found in previous investigations.

Effects of Genetic Variation on Endurance Performance, Muscle Strength, and Injury Susceptibility in Sports: A Systematic Review

The aim of this systematic review was to assess the effects of genetic variations and polymorphisms on endurance performance, muscle strength and injury susceptibility in competitive sports. The electronic databases PubMed and Web of Science were searched for eligible studies. The study quality was assessed using the RoBANS tool. Studies were included if they met the following criteria: (1) human study in English or German; (2) published in the period 2015–2019; (3) investigation of an association between genetic variants and endurance performance and/or muscle strength and/or endurance/strength training status as well as ligament, tendon, or muscle injuries; (4) participants aged 18–60 years and national or international competition participation; (5) comparison with a control group. Nineteen studies and one replication study were identified. Results revealed that the IGF-1R 275124 A>C rs1464430 polymorphism was overrepresented in endurance trained athletes. Further, genotypes of PPARGC1A polymorphism correlated with performance in endurance exercise capacity tests in athletes. Moreover, the RR genotype of ACTN3 R577X polymorphism, the C allele of IGF-1R polymorphism and the gene variant FTO T>A rs9939609 and/or their AA genotype were linked to muscle strength. In addition, gene variants of MCT1 (T1470A rs1049434) and ACVR1B (rs2854464) were also positively associated with strength athletes. Among others, the gene variants of the MMP group (rs591058 and rs679620) as well as the polymorphism COL5A1 rs13946 were associated with susceptibility to injuries of competitive athletes. Based on the identified gene variants, individualized training programs for injury prevention and optimization of athletic performance could be created for competitive athletes using gene profiling techniques.

Total Genotype Score Modelling of Polygenic Endurance-Power Profiles in Lithuanian Elite Athletes

Total genotype score (TGS) reflects additive effect of genotypes on predicting a complex trait such as athletic performance. Scores assigned to genotypes in the TGS should represent an extent of the genotype’s predisposition to the trait. Then, combination of genotypes highly ranks those individuals, who have a trait expressed. Usually, the genotypes are scored by the evidence of a genotype–phenotype relationship published in scientific studies. The scores can be revised computationally using genotype data of athletes, if available. From the available genotype data of 180 Lithuanian elite athletes we created an endurance-mixed-power performance TGS profile based on known ACE rs1799752, ACTN3 rs1815739, and AMPD1 rs17602729, and an emerging MB rs7293 gene markers. We analysed an ability of this TGS profile to stratify athletes according to the sport category that they practice. Logistic regression classifiers were trained to compute the genotype scores that represented the endurance versus power traits in the group of analysed athletes more accurately. We observed differences in TGS distributions in female and male group of athletes. The genotypes with possibly different effects on the athletic performance traits in females and males were described. Our data-driven analysis and TGS modelling tools are freely available to practitioners.