Advancing sports and exercise genomics: moving from hypothesis-driven single study approaches to large multi-omics collaborative science

Interaction Between ACTN3 (R577X), ACE (I/D), and BDKRB2 (-9/+9) Polymorphisms and Endurance Phenotypes in Brazilian Long-Distance Swimmers

ABSTRACT

Neto, SLdA, Herrera, JJB, Rosa, TS, de Almeida, SS, Silva, GCB, Ferreira, CES, dos Santos, MAP, Silvino, VO, de Melo, GF. Interaction between ACTN3 (R577X), ACE (I/D), and BDKRB2 (-9/+9) polymorphisms and endurance phenotypes in Brazilian long-distance swimmers. J Strength Cond Res 36(6): 1591-1595, 2022-This study investigated the interactions between the polymorphisms ACTN3 (R577X), ACE (I/D), and BDKRB2 (-9/+9) and their association with endurance phenotypes in Brazilian long-distance swimmers. Twenty-six volunteers (aged 18-30 years) were divided into 2 groups as follows: 19 subelite athletes formed the pool swimming experts (PSE: 400-1500 m) group and 7 elite athletes the open water swimming experts (OWSE: 5-25 km) group. ACTN3 (R577X), ACE (I/D), and BDKRB2 (-9/+9) polymorphisms were genotyped through polymerase chain reaction. A nonathletes control (CON) group derived from studies with the Brazilian population was created. Hardy-Weinberg equilibrium (X2) was observed in all groups. The total genotype score (TGS) associated with endurance phenotypes was used in this study. A significance level was established at p ≤ 0.05. PSE and CON groups had very similar genotyping distribution. The OWSE group had a greater frequency for the genotypes XX (57.1%), ID (57.1%), and the alleles X (71.4%) and I (57.2%) than CON and PSE groups (XX = 21.1 and 21.1%; ID = 47.1 and 52.6% [p > 0.05]; X = 44.0 and 42.1%; I = 45.3 and 42.1%, respectively). Considering BDKRB2, OWSE and PSE groups had a greater frequency of +9/+9 than the CON group (42.9% and 31.6 vs. 27.5%, respectively). Although the expected genotypic distribution was not verified among athletes, the TGS revealed small supremacy of 3-5 typical alleles in the OWSE group (54.8 ± 26.7%) compared with the PSE group (41.2 ± 17.8%) (p = 0.072; confidence interval = 95%; effect size = 0.95). The OWSE group seem to have benefited from the best genotype profile verified for ACTN3 and ACE. However, the results of this work should be approached with caution because of the small number of athletes and polymorphisms assessed.

Association Between Changes in Serum and Skeletal Muscle Metabolomics Profile With Maximum Power Output Gains in Response to Different Aerobic Training Programs: The Times Study

Purpose: High heterogeneity of the response of cardiorespiratory fitness (CRF) to standardized exercise doses has been reported in different training programs, but the associated mechanisms are not widely known. This study investigated whether changes in the metabolic profile and pathways in blood serum and the skeletal muscle are associated with the inter-individual variability of CRF responses to 8-wk of continuous endurance training (ET) or high-intensity interval training (HIIT).

Methods: Eighty men, young and sedentary, were randomized into three groups, of which 70 completed 8 wk of intervention (> 90% of sessions): ET, HIIT, or control. Blood and vastus lateralis muscle tissue samples, as well as the measurement of CRF [maximal power output (MPO)] were obtained before and after the intervention. Blood serum and skeletal muscle samples were analyzed by 600 MHz ¹H-NMR spectroscopy (metabolomics). Associations between the pretraining to post-training changes in the metabolic profile and MPO gains were explored via three analytical approaches: (1) correlation between pretraining to post-training changes in metabolites' concentration levels and MPO gains; (2) significant differences between low and high MPO responders; and (3) metabolite contribution to significantly altered pathways related to MPO gains. After, metabolites within these three levels of evidence were analyzed by multiple stepwise linear regression. The significance level was set at 1%.

Results: The metabolomics profile panel yielded 43 serum and 70 muscle metabolites. From the metabolites within the three levels of evidence (15 serum and 4 muscle metabolites for ET; 5 serum and 1 muscle metabolites for HIIT), the variance in MPO gains was explained: 77.4% by the intervention effects, 6.9, 2.3, 3.2, and 2.2% by changes in skeletal muscle pyruvate and valine, serum glutamine and creatine phosphate, respectively, in ET; and 80.9% by the intervention effects; 7.2, 2.2, and 1.2% by changes in skeletal muscle glycolate, serum creatine and creatine phosphate, respectively, in HIIT. The most changed and impacted pathways by these metabolites were: arginine and proline metabolism, glycine, serine and threonine metabolism, and glyoxylate and dicarboxylate metabolism for both ET and HIIT programs; and additional alanine, aspartate and glutamate metabolism, arginine biosynthesis, glycolysis/gluconeogenesis, and pyruvate metabolism for ET.

Conclusion: These results suggest that regulating the metabolism of amino acids and carbohydrates may be a potential mechanism for understanding the inter-individual variability of CRF in responses to ET and HIIT programs.

Establishment of a post-race biomarkers database and application of pathway analysis to identify potential biomarkers in post-race equine plasma

In the context of doping control, conventional direct chemical testing detects only a limited scope of target substances in equine biological samples. To expand the ability to detect doping agents and their detection windows, metabolomics has recently become a common approach for monitoring alteration of biomarkers caused by doping agents in relevant metabolic pathways. In horse racing, remarkable changes in metabolic profiles between the rest state and racing are likely to affect the identification of doping biomarkers. Previously, we reported a limited number of significantly upregulated metabolites after racing, based on a non-targeted metabolomics approach using out-of-competition and post-race equine plasma samples. In this study, we performed a more thorough analysis of the data set, using pathway analysis to establish a post-race biomarkers database (PBD) that includes upregulated and downregulated metabolites, their fold changes, and relevant pathways, with the main objective of improving our understanding of changes in physiological status related to horse racing. Statistical analysis of the PBD revealed that two peak combinations of pentadecanoyl carnitine/galactosylglycerol (P/G) and heptadecanoyl carnitine/galactosylglycerol (H/G) could be used as potential biomarkers for the discrimination of the rest and post-race groups. To demonstrate the applicability of the PBD, we validated the post-race biomarkers P/G and H/G (highly involved in lipid metabolism) by a single-blind test. This strategy, which combines establishment of a biomarker database with pathway analysis, represents a powerful tool for discovering potential doping biomarkers in the future.

Genetic test for the personalization of sport training

Genetic variants may contribute to confer elite athlete status. However, this does not mean that a person with favourable genetic traits would become a champion because multiple genetic interactions and epigenetic contributions coupled with confounding environmental factors shape the overall phenotype. This opens up a new area in sports genetics with respect to commercial genetic testing. The analysis of genetic polymorphisms linked to sport performance would provide insights into the potential of becoming an elite endurance or power performer. This mini-review aims to highlight genetic interactions that are associated with performance phenotypes and their potentials to be used as markers for talent identification and trainability.

Sport and exercise genomics: the FIMS 2019 consensus statement update

Rapid advances in technologies in the field of genomics such as high throughput DNA sequencing, big data processing by machine learning algorithms and gene-editing techniques are expected to make precision medicine and gene-therapy a greater reality. However, this development will raise many important new issues, including ethical, moral, social and privacy issues. The field of exercise genomics has also advanced by incorporating these innovative technologies. There is therefore an urgent need for guiding references for sport and exercise genomics to allow the necessary advancements in this field of sport and exercise medicine, while protecting athletes from any invasion of privacy and misuse of their genomic information. Here, we update a previous consensus and develop a guiding reference for sport and exercise genomics based on a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. This SWOT analysis and the developed guiding reference highlight the need for scientists/clinicians to be well-versed in ethics and data protection policy to advance sport and exercise genomics without compromising the privacy of athletes and the efforts of international sports federations. Conducting research based on the present guiding reference will mitigate to a great extent the risks brought about by inappropriate use of genomic information and allow further development of sport and exercise genomics in accordance with best ethical standards and international data protection principles and policies. This guiding reference should regularly be updated on the basis of new information emerging from the area of sport and exercise medicine as well as from the developments and challenges in genomics of health and disease in general in order to best protect the athletes, patients and all other relevant stakeholders.

Genome-Wide Association Study Reveals a Novel Association Between MYBPC3 Gene Polymorphism, Endurance Athlete Status, Aerobic Capacity and Steroid Metabolism

Background

The genetic predisposition to elite athletic performance has been a controversial subject due to the underpowered studies and the small effect size of identified genetic variants. The aims of this study were to investigate the association of common single-nucleotide polymorphisms (SNPs) with endurance athlete status in a large cohort of elite European athletes using GWAS approach, followed by replication studies in Russian and Japanese elite athletes and functional validation using metabolomics analysis.

Results

The association of 476,728 SNPs of Illumina DrugCore Gene chip and endurance athlete status was investigated in 796 European international-level athletes (645 males, 151 females) by comparing allelic frequencies between athletes specialized in sports with high (n = 662) and low/moderate (n = 134) aerobic component. Replication of results was performed by comparing the frequencies of the most significant SNPs between 242 and 168 elite Russian high and low/moderate aerobic athletes, respectively, and between 60 elite Japanese endurance athletes and 406 controls. A meta-analysis has identified rs1052373 (GG homozygotes) in Myosin Binding Protein (MYBPC3; implicated in cardiac hypertrophic myopathy) gene to be associated with endurance athlete status (P = 1.43 × 10^-8, odd ratio 2.2). Homozygotes carriers of rs1052373 G allele in Russian athletes had significantly greater VO_{2 max} than carriers of the AA + AG (P = 0.005). Subsequent metabolomics analysis revealed several amino acids and lipids associated with rs1052373 G allele (1.82 × 10^-05) including the testosterone precursor androstenediol (3beta,17beta) disulfate.

Conclusions

This is the first report of genome-wide significant SNP and related metabolites associated with elite athlete status. Further investigations of the functional relevance of the identified SNPs and metabolites in relation to enhanced athletic performance are warranted.

Genetic association research in football: A systematic review

Genetic variation is responsible for a large amount of the inter-individual performance disparities seen in sport. As such, in the last ten years genetic association studies have become more common; with one of the most frequently researched sports being football. However, the progress and methodological rigour of genetic association research in football is yet to be evaluated. Therefore, the aim of this paper was to identify and evaluate all genetic association studies involving football players and outline where and how future research should be directed. Firstly, a systematic search was conducted in the Pubmed and SPORTDiscus databases, which identified 80 eligible studies. Progression analysis revealed that 103 distinct genes have been investigated across multiple disciplines; however, research has predominately focused on the association of the ACTN3 or ACE gene. Furthermore, 55% of the total studies have been published within the last four years; showcasing that genetic association research in football is increasing at a substantial rate. However, there are several methodological inconsistencies which hinder research implications, such as; inadequate description or omission of ethnicity and on-field positions. Furthermore, there is a limited amount of research on several key areas crucial to footballing performance, in particular; psychological related traits. Moving forward, improved research designs, larger sample sizes, and the utilisation of genome-wide and polygenic profiling approaches are recommended. Finally, we introduce the Football Gene Project, which aims to address several of these limitations and ultimately facilitate greater individualised athlete development within football.

Metabolic GWAS of elite athletes reveals novel genetically-influenced metabolites associated with athletic performance

Genetic research of elite athletic performance has been hindered by the complex phenotype and the relatively small effect size of the identified genetic variants. The aims of this study were to identify genetic predisposition to elite athletic performance by investigating genetically-influenced metabolites that discriminate elite athletes from non-elite athletes and to identify those associated with endurance sports. By conducting a genome wide association study with high-resolution metabolomics profiling in 490 elite athletes, common variant metabolic quantitative trait loci (mQTLs) were identified and compared with previously identified mQTLs in non-elite athletes. Among the identified mQTLs, those associated with endurance metabolites were determined. Two novel genetic loci in FOLH1 and VNN1 are reported in association with N-acetyl-aspartyl-glutamate and Linoleoyl ethanolamide, respectively. When focusing on endurance metabolites, one novel mQTL linking androstenediol (3alpha, 17alpha) monosulfate and SULT2A1 was identified. Potential interactions between the novel identified mQTLs and exercise are highlighted. This is the first report of common variant mQTLs linked to elite athletic performance and endurance sports with potential applications in biomarker discovery in elite athletic candidates, non-conventional anti-doping analytical approaches and therapeutic strategies.

Omics and the molecular exercise physiology

Exercise is a well-known non-pharmacologic agent used to prevent and treat a wide range of pathologic conditions such as metabolic and cardiovascular disease. In this sense, the classic field of exercise physiology has determined the main theoretical and practical bases of physiologic adaptations in response to exercise. However, the last decades were marked by significant advances in analytical laboratory techniques, where the field of biochemistry, genetics and molecular biology promoted exercise science to enter a new era. Regardless of its application, whether in the field of disease prevention or performance, the association of molecular biology with exercise physiology has been fundamental for unveiling knowledge of the molecular mechanisms related to the adaptation to exercise. This chapter will address the natural evolution of exercise physiology toward genetics and molecular biology, emphasizing the collection of integrated analytical approaches that composes the OMICS and their contribution to the field of molecular exercise physiology.

Omics and Exercise: Global Approaches for Mapping Exercise Biological Networks

The application of global "-omics" technologies to exercise has introduced new opportunities to map the complexity and interconnectedness of biological networks underlying the tissue-specific responses and systemic health benefits of exercise. This review will introduce major research tracks and recent advancements in this emerging field, as well as critical gaps in understanding the orchestration of molecular exercise dynamics that will benefit from unbiased omics investigations. Furthermore, significant research hurdles that need to be overcome to effectively fill these gaps related to data collection, computation, interpretation, and integration across omics applications will be discussed. Collectively, a cross-disciplinary physiological and omics-based systems approach will lead to discovery of a wealth of novel exercise-regulated targets for future mechanistic validation. This frontier in exercise biology will aid the development of personalized therapeutic strategies to improve athletic performance and human health through precision exercise medicine.

Letter to the editor: A genetic-based algorithm for personalized resistance training

In a recent paper entitled “A genetic-based algorithm for personalized resistance training”, Jones et al. [1] presented an algorithm of 15 performance-associated gene polymorphisms that they propose can determine an athlete’s training response by predicting power and endurance potential. However, from the design of their studies and the data provided, there is no evidence to support these authors’ assertions. Progress towards such a significant development in the field of sport and exercise genomics will require a paradigm shift in line with recent recommendations for international collaborations such as the Athlome Project (see www.athlomeconsortium.org). Large-scale initiatives, involving numerous multi-centre and well-phenotyped exercise training and elite performance cohorts, will be necessary before attempting to derive and replicate training and/or performance algorithms.

The TreadWheel: A Novel Apparatus to Measure Genetic Variation in Response to Gently Induced Exercise for Drosophila

Obesity is one of the dramatic health issues affecting developed and developing nations, and exercise is a well-established intervention strategy. While exercise-by-genotype interactions have been shown in humans, overall little is known. Using the natural negative geotaxis of Drosophila melanogaster, an important model organism for the study of genetic interactions, a novel exercise machine, the TreadWheel, can be used to shed light on this interaction. The mechanism for inducing exercise with the TreadWheel is inherently gentle, thus minimizing possible confounding effects of other stressors. Using this machine, we were able to assess large cohorts of adult flies from eight genetic lines for their response to exercise after one week of training. We measured their triglyceride, glycerol, protein, glycogen, glucose content, and body weight, as well as their climbing ability and feeding behavior in response to exercise. Exercised flies showed decreased stored triglycerides, glycogen, and body weight, and increased stored protein and climbing ability. In addition to demonstrating an overall effect of TreadWheel exercise on flies, we found significant interactions of exercise with genotype, sex, or genotype-by-sex effects for most of the measured phenotypes. We also observed interaction effects between exercise, genotype, and tissue (abdomen or thorax) for metabolite profiles, and those differences can be partially linked to innate differences in the flies' persistence in maintaining activity during exercise bouts. In addition, we assessed gene expression levels for a panel of 13 genes known to be associated with respiratory fitness and found that many responded to exercise. With this study, we have established the TreadWheel as a useful tool to study the effect of exercise in flies, shown significant genotype-specific and sex-specific impacts of exercise, and have laid the ground work for more extensive studies of how genetics, sex, environment, and aging interact with exercise to influence metabolic fitness in Drosophila.