Preliminary Investigation Into the Effect of ACTN3 and ACE Polymorphisms on Muscle and Performance Characteristics

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.

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.

The Impact of ACTN3 Gene Polymorphisms on Susceptibility to Exercise-Induced Muscle Damage and Changes in Running Economy Following Downhill Running

This study aimed to investigate if ACTN3 gene polymorphism impacts the susceptibility to exercise-induced muscle damage (EIMD) and changes in running economy (RE) following downhill running. Thirty-five healthy men were allocated to the two groups based on their ACTN3 gene variants: RR and X allele carriers. Neuromuscular function [knee extensor isometric peak torque (IPT), rate of torque development (RTD), and countermovement, and squat jump height], indirect markers of EIMD [muscle soreness, mid-thigh circumference, knee joint range of motion, and serum creatine kinase (CK) activity], and RE (oxygen uptake, minute ventilation, blood lactate concentration, and perceived exertion) for 5-min of running at a speed equivalent to 80% of individual maximal oxygen uptake speed were assessed before, immediately after, and 1-4 days after a 30-min downhill run (-15%). Neuromuscular function was compromised (P < 0.05) following downhill running with no differences between the groups, except for IPT, which was more affected in the RR individuals compared with the X allele carriers immediately (-24.9 ± 6.9% vs. -16.3 ± 6.5%, respectively) and 4 days (-16.6 ± 14.9% vs. -4.2 ± 9.5%, respectively) post-downhill running. EIMD manifested similarly for both the groups except for serum CK activity, which was greater for RR (398 ± 120 and 452 ± 126 U L^-1 at 2 and 4 days following downhill running, respectively) compared with the X allele carriers (273 ± 121 and 352 ± 114 U L^-1 at the same time points). RE was compromised following downhill running (16.7 ± 8.3% and 11 ± 7.5% increases in oxygen uptake immediately following downhill running for the RR and X allele carriers, respectively) with no difference between the groups. We conclude that although RR individuals appear to be more susceptible to EIMD following downhill running, this does not extend to the changes in RE.

Muscle Work and Its Relationship with ACE and ACTN3 Polymorphisms Are Associated with the Improvement of Explosive Strength

Background: The potential influence of genetics in athletic performance allows the search for genetic profiles associated with muscular work for the orientation of strength training and sports selection. The purpose of the study was to analyze four muscular exercises for effectiveness in improving explosive strength variables, associated to the genetics in Angiotensin Converting Enzyme (ACE) and α-actinin-3 (ACTN3) polymorphisms. Methods: A randomized controlled trial was conducted on a sample of 80 subjects allocated into four groups: concentric muscle work (CMW), eccentric muscle work (EMW), concentric-eccentric muscle (C-EMW) work and isometric muscular work (IMW), by block and gender randomization. Vertical jump, long jump, power jump, and speed were measured to study explosive strength. Genotypic frequencies of ACE (rs4646994) and ACTN3 (rs1815739) were obtained by polymerase chain reaction. Results: ACE gen showed significant improvements regarding the DD genotype in the Sargent test (p = 0.003) and sprint velocity test (p = 0.017). In the ACTN3 gene, the RR variable obtained improvement results with regard to RX and XX variables in long jump (p < 0.001), Sargent test (p < 0.001) and power jump (p = 0.004). Conclusions: The selected genes demonstrated an influence on the muscle work and the improvement in explosive strength variables with a decisive role regarding the type of muscle work performed.

Responses to Maximal Strength Training in Different Age and Gender Groups

Purpose

The present study aimed to investigate the potential impact of age, gender, baseline strength, and selected candidate polymorphisms on maximal strength training (MST) adaptations.

Methods

A total of 49 subjects (22 men and 27 women) aged 20–76 years, divided into five age groups, completed an 8 weeks MST intervention. Each MST session consisted of 4 sets with 4 repetitions at ∼85–90% of one-repetition maximum (1RM) intensity in leg-press, three times per week. 1RM was tested pre and post the intervention and blood samples were drawn to genotype candidate polymorphisms ACE I/D (rs1799752), ACTN3 R577X (rs1815739), and PPARGC1A Gly482Ser (rs8192678).

Results

All age groups increased leg-press 1RM (p < 0.01), with a mean improvement of 24.2 ± 14.0%. There were no differences in improvements between the five age groups or between male and female participants, and there were no non-responders. Baseline strength status did not correlate with 1RM improvements. PPARGC1A rs8192678 T allele carriers had a 15% higher age- and gender corrected baseline 1RM than the CC genotype (p < 0.05). C allele carriers improved 1RM (%) by 34.2% more than homozygotes for the T allele (p < 0.05).

Conclusion

To the best of our knowledge, this is the first study to report improvement in leg-press maximal strength regardless of gender, baseline strength status in all age groups. The present study is also first to demonstrate an association between the PPARGC1A rs8192678 and maximal strength and its trainability in a moderately trained cohort. MST may be beneficial for good health and performance of all healthy individuals.

The Development of a Personalised Training Framework: Implementation of Emerging Technologies for Performance

Over the last decade, there has been considerable interest in the individualisation of athlete training, including the use of genetic information, alongside more advanced data capture and analysis techniques. Here, we explore the evidence for, and practical use of, a number of these emerging technologies, including the measurement and quantification of epigenetic changes, microbiome analysis and the use of cell-free DNA, along with data mining and machine learning. In doing so, we develop a theoretical model for the use of these technologies in an elite sport setting, allowing the coach to better answer six key questions: (1) To what training will my athlete best respond? (2) How well is my athlete adapting to training? (3) When should I change the training stimulus (i.e., has the athlete reached their adaptive ceiling for this training modality)? (4) How long will it take for a certain adaptation to occur? (5) How well is my athlete tolerating the current training load? (6) What load can my athlete handle today? Special consideration is given to whether such an individualised training framework will outperform current methods as well as the challenges in implementing this approach.