“Advances in technology” was identified by the thematic analysis and clustered as a Strength. According to several reviewers, the completion of the Human Genome Project in 2003 and HapMap enabled to analyze complex traits. (Bouchard et al., 2015; Yan et al., 2016; Pickering and Kiely, 2019; Gomes et al., 2020; Griswold et al., 2021) Advances in methodology and technology, such as the development of genome-wide association studies (i.e., hypothesis free approaches), the use of high-throughput sequencing technologies (fast and inexpensive), as well as innovative analytical approaches (e.g., artificial intelligence, machine learning) contributed to the progress of exercise genomics/genetics. (Bray, 2000; Brutsaert and Parra, 2006; Sharp, 2008; McNamee et al., 2009; Lippi et al., 2010; Bouchard, 2011; Bouchard et al., 2011; Eynon et al., 2011; Pérusse et al., 2013; Wang et al., 2013; Breitbach et al., 2014; Wolfarth et al., 2014; Ahmetov and Fedotovskaya, 2015; Bouchard, 2015; Bouchard et al., 2015; Loos et al., 2015; Webborn et al., 2015; Gibson, 2016; Mattsson et al., 2016; Sarzynski et al., 2016; Wang et al., 2016; Yan et al., 2016; Moran and Pitsiladis, 2017; Vlahovich et al., 2017; Vellers et al., 2018; Landen et al., 2019; Pickering et al., 2019; Pickering and Kiely, 2019; Gomes et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021)

The thematic analysis also identified “empirical evidence” as one of the Strengths of exercise genetics/genomics. Highlighted by many authors, the heritability estimates of exercise-related traits vary between 40% and 70%, depending on the trait under investigation. (Brutsaert and Parra, 2006; Ostrander et al., 2009; Wackerhage et al., 2009; Lippi et al., 2010; Bouchard, 2011; Eynon et al., 2011; Guth and Roth, 2013; Wang et al., 2013; Breitbach et al., 2014; Ahmetov and Fedotovskaya, 2015; Bouchard et al., 2015; Wang et al., 2016; Yan et al., 2016; Moran and Pitsiladis, 2017; Vellers et al., 2018; Landen et al., 2019; Pickering et al., 2019; Gomes et al., 2020; Naureen et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Wang and Ashokan, 2021; Kim et al., 2022; Varillas-Delgado et al., 2022; Viecelli and Ewald, 2022) For instance, the heritability for “achieving elite athletic status” has been estimated approximately 66%, (Guth and Roth, 2013; Ahmetov and Fedotovskaya, 2015; Varillas-Delgado et al., 2022), the “change in maximal oxygen uptake in response to training” around 50%, (Brutsaert and Parra, 2006; Wackerhage et al., 2009; Bouchard, 2011; Bouchard et al., 2015; Moran and Pitsiladis, 2017; Gomes et al., 2020; Griswold et al., 2021; Wang and Ashokan, 2021; Kim et al., 2022), and the “transmissibility of muscle mass to be greater than 90%.” (Viecelli and Ewald, 2022) According to several authors, “more than 200 performance enhancing polymorphisms exist.” (Ostrander et al., 2009; Eynon et al., 2011; Guth and Roth, 2013; Wang et al., 2013; Wang et al., 2016; Yan et al., 2016; Naureen et al., 2020) Thus, empirical evidence (e.g., high heritability estimates) supports the role of genetics within athletic performance.

Several reviewers described exercise genetics/genomics as a “growing research field” which therefore has been clustered into Strengths. (Brutsaert and Parra, 2006; Wolfarth et al., 2014; Ahmetov and Fedotovskaya, 2015; Loos et al., 2015; Gibson, 2016; Vlahovich et al., 2017; Pickering and Kiely, 2019; Varillas-Delgado et al., 2022. For example, Ahmetov and Fedotovskaya (2015) reported: “By the end of 2014, the total number of DNA polymorphisms related to exercise genetics was 120. Most of these polymorphisms (70%) were discovered in the last 5 years (2010–2014), indicating a growing interest in the field of sports genomics.” (Ahmetov and Fedotovskaya, 2015)

“Consortia, consensus statements and guidelines” were identified by the present sSWOT as Strengths. Several narratives mentioned the establishment of “international, large-scale, and well-funded” consortia (e.g., www.athlomeconsortium.org). (Wang et al., 2013; Pitsiladis et al., 2016; Wang et al., 2016; Vlahovich et al., 2017; Gomes et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Sellami et al., 2021) According to these findings, the “interdisciplinary consortia” but also the “consensus statements” and “guidelines” for conducting good exercise genetic/genomic research may contribute to an increased research quality providing sufficient scientific evidence. (Tanisawa et al., 2020)

“Acceptance and accessibility of genetic performance testing” was additionally classified as Strengths. The thematic analysis identified one report emphasizing “athletes are generally open for genetic performance testing” (Pickering and Kiely, 2019) and, in addition, genetic testing was described as “non-invasive and quick method for performance testing” which may contribute to generally accepting genetic testing within a sporting context. (Lippi et al., 2010)

Most Weaknesses identified by the thematic analysis were related to methodological shortcomings resulting from “low quality studies.” (Brutsaert and Parra, 2006; Ostrander et al., 2009; Wackerhage et al., 2009; Rankinen et al., 2010; Bouchard, 2011; Bouchard et al., 2011; Eynon et al., 2011; Hagberg et al., 2011; Roth et al., 2012; Guth and Roth, 2013; Wang et al., 2013; Breitbach et al., 2014; Ahmetov and Fedotovskaya, 2015; Bouchard, 2015; Loos et al., 2015; Webborn et al., 2015; Gibson, 2016; Mattsson et al., 2016; Pitsiladis et al., 2016; Wang et al., 2016; Moran and Pitsiladis, 2017; Vlahovich et al., 2017; Vellers et al., 2018; Landen et al., 2019; Pickering et al., 2019; Gomes et al., 2020; Naureen et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Kim et al., 2022; Varillas-Delgado et al., 2022) Numerous scholars have contended that the present body of knowledge in the field of sport genetics/genomics is primarily rooted in investigations of candidate genes (i.e., research designed to test a priori hypotheses using case-control designs), which typically involve limited sample sizes and, as a result, frequently exhibit insufficient statistical power. (Brutsaert and Parra, 2006; Wang et al., 2013; Ahmetov and Fedotovskaya, 2015; Loos et al., 2015; Mattsson et al., 2016; Pitsiladis et al., 2016; Yan et al., 2016; Moran and Pitsiladis, 2017; Vlahovich et al., 2017) Some authors acknowledged that candidate gene studies produced “inconclusive results” or “false positives” (Wang et al., 2013; Ahmetov and Fedotovskaya, 2015; Loos et al., 2015; Gibson, 2016; Mattsson et al., 2016; Moran and Pitsiladis, 2017; Varillas-Delgado et al., 2022). Furthermore, Kim et al. (2020) (Kim et al., 2022) highlighted that “only a handful of genome-wide association studies” have been performed in a exercise science context, and according to Griswold et al., (2021) (Griswold et al., 2021) “even the largest genome-wide association study to date in elite endurance athletes (a total of 1,520 athletes and 2,760 controls) was not able to identify any significantly associated genetic markers”. Other reviewers argued that “inconsistent study protocols”, (Vellers et al., 2018; Gomes et al., 2020; Kim et al., 2022), poor “definitions and measurements of phenotypes”, (Bouchard, 2011; Eynon et al., 2011; Roth et al., 2012; Ahmetov and Fedotovskaya, 2015; Gibson, 2016; Mattsson et al., 2016; Wang et al., 2016; Vellers et al., 2018; Gomes et al., 2020; Naureen et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Varillas-Delgado et al., 2022), and poor “classifications of sport disciplines and performance level” (Ostrander et al., 2009; Eynon et al., 2011; Breitbach et al., 2014; Naureen et al., 2020) would increase the “(phenotypic) heterogeneity.” (Ostrander et al., 2009; Bouchard et al., 2011; Eynon et al., 2011; Breitbach et al., 2014; Gibson, 2016; Wang et al., 2016; Moran and Pitsiladis, 2017; Vlahovich et al., 2017; Naureen et al., 2020; Griswold et al., 2021; Varillas-Delgado et al., 2022) Finally, some authors mentioned that the employment of inappropriate (sedentary) control groups, (Bouchard et al., 2011; Moran and Pitsiladis, 2017; Varillas-Delgado et al., 2022), the lack of blinding, (Gibson, 2016), not accounting for multiple testing, (Rankinen et al., 2010; Bouchard, 2011; Hagberg et al., 2011; Roth et al., 2012; Wang et al., 2013; Wang et al., 2016), as well as a low genotyping quality and errors (Rankinen et al., 2010; Gibson, 2016) may contribute to a “low internal validity” of exercise genetic/genomic studies.

Many reviewers described the “complexity of exercise-related traits”, which was identified as a Weakness in the present overview. (Bray, 2000; Brutsaert and Parra, 2006; Wackerhage et al., 2009; Lippi et al., 2010; Bouchard, 2011; Bouchard et al., 2011; Eynon et al., 2011; Roth et al., 2012; Guth and Roth, 2013; Wang et al., 2013; Wolfarth et al., 2014; Ahmetov and Fedotovskaya, 2015; Bouchard, 2015; Loos et al., 2015; Gibson, 2016; Mattsson et al., 2016; Wang et al., 2016; Yan et al., 2016; Moran and Pitsiladis, 2017; Vellers et al., 2018; Landen et al., 2019; Pickering et al., 2019; Pickering and Kiely, 2019; Gomes et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Varillas-Delgado et al., 2022) Multifaceted characteristics, such as exercise-related traits, are considered polygenic in nature, meaning that they are influenced by numerous variants, gene-gene and gene-environment interactions, epigenetic modifications, and other factors. The individual impact of each variant is typically minor. A consensus among several authors is that current research on exercise genetics/genomics has primarily concentrated on exploring common genetic variants, while paying less attention to rare genetic variants. (Bouchard, 2011; Roth et al., 2012; Wang et al., 2013; Mattsson et al., 2016; Moran and Pitsiladis, 2017; Pickering et al., 2019; Gomes et al., 2020; Griswold et al., 2021) For example, Bouchard et al., (Bouchard, 2011), among others, stated that “rare variants are most likely the high-impact variants” but challenging to uncover. In addition, other types of genomic variation, such as structural variations (e.g., copy number variations, insertions and deletions) and non-coding RNA (e.g., micro-RNA) also contribute to exercise-related traits but “would not be captured by current genotyping methods”. (Bouchard, 2011; Bouchard et al., 2011; Roth et al., 2012; Wang et al., 2013; Vellers et al., 2018) The “generalizability” of exercise genetic/genomic study results has also been identified as Weakness by the thematic analysis. (Rankinen et al., 2010; Bouchard et al., 2011; Eynon et al., 2011; Ahmetov and Fedotovskaya, 2015; Webborn et al., 2015; Mattsson et al., 2016; Wang et al., 2016; Vlahovich et al., 2017; Landen et al., 2019; Pickering et al., 2019; Naureen et al., 2020; Griswold et al., 2021; Kim et al., 2022) Several reviewers mentioned a low generalizability due to “sex imbalances”, (Mattsson et al., 2016; Vlahovich et al., 2017; Landen et al., 2019; Kim et al., 2022), or “lack of population stratification.” (Rankinen et al., 2010; Bouchard et al., 2011; Eynon et al., 2011; Ahmetov and Fedotovskaya, 2015; Mattsson et al., 2016; Wang et al., 2016; Landen et al., 2019; Naureen et al., 2020; Griswold et al., 2021; Kim et al., 2022)

The sSWOT analysis additionally identified a Weakness related to the significant “costs” of genetic research on one hand, and the inadequate funding available on the other hand. (Brutsaert and Parra, 2006; Wackerhage et al., 2009; Lippi et al., 2010; Hagberg et al., 2011; Roth et al., 2012; Loos et al., 2015; Gibson, 2016; Sarzynski et al., 2016) Another Weakness was linked to “genotype scores”. (Eynon et al., 2011; Wang et al., 2013; Breitbach et al., 2014; Webborn et al., 2015; Mattsson et al., 2016; Pickering et al., 2019; Naureen et al., 2020; Varillas-Delgado et al., 2022) According to some reviewers, genotype scores in an exercise science context have “zero predictive capability”, “limited real world sensitivity and specificity, (Wang et al., 2016), and “lack appropriate weighing factors”. (Varillas-Delgado et al., 2022) The content analysis additionally revealed “reporting bias” as a Weakness. (Rankinen et al., 2010; Eynon et al., 2011; Wang et al., 2013; Gibson, 2016) For example, Rankinen et al. (2019) stated: “very few negative studies reach publication.” (Rankinen et al., 2010)

The thematic analysis identified three more Weaknesses related to “invasive methods”, (Eynon et al., 2011; Gibson, 2016; Mattsson et al., 2016; Pickering and Kiely, 2019), “research progress”, (Wang et al., 2013; Yan et al., 2016), and “causality”. (Mattsson et al., 2016) Some authors highlighted that more “invasive methods” (e.g., biopsies) may be necessary to entangle the complexity of exercise genetics/genomics. (Eynon et al., 2011; Gibson, 2016; Mattsson et al., 2016; Pickering and Kiely, 2019) Further, based on the report of Wang et al. (2013) there has been “limited research progress” and output of the consortia and multi-center studies. (Wang et al., 2013; Yan et al., 2016) Finally, Mattson et al. (2016) stated: “It is important to emphasize that genetic association, regardless of how robust, does not infer causality.” (Mattsson et al., 2016)

The present sSWOT identified “precision exercise” approaches based on “genetic profiling” as an Opportunity as highlighted by many reviewers. (Sharp, 2008; Lippi et al., 2010; Bouchard, 2011; Eynon et al., 2011; Guth and Roth, 2013; Pérusse et al., 2013; Wolfarth et al., 2014; Ahmetov and Fedotovskaya, 2015; Bouchard et al., 2015; Loos et al., 2015; Mattsson et al., 2016; Pitsiladis et al., 2016; Sarzynski et al., 2016; Vlahovich et al., 2017; Landen et al., 2019; Pickering et al., 2019; Pickering and Kiely, 2019; Gomes et al., 2020; Naureen et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Sellami et al., 2021; Wang and Ashokan, 2021; Kim et al., 2022; Varillas-Delgado et al., 2022). According to these authors, exercise genetics/genomics has the potential to “optimize and maximize physical performance” (Sellami et al., 2021) by implementing precision exercise methods. Several reviewers suggested, “once genetic associations have been identified in a robust and valid manner”, (Mattsson et al., 2016), improved genotype scores may be developed by integrating (among others) “data science”, “algorithms”, or “machine learning”. (Eynon et al., 2011; Pickering et al., 2019; Pickering and Kiely, 2019; Kim et al., 2022) By using “genetic profiling”, coaches and athletes might be able “to match individuals to the type of training to which they are most suited, and from which they will elicit the greatest adaptations”, according to Pickering and others (2019). (Pickering et al., 2019). Some reviewers also mentioned a possible impact on “injury risks”, (Guth and Roth, 2013; Varillas-Delgado et al., 2022), “recovery periods”, (Sharp, 2008; Guth and Roth, 2013; Ahmetov and Fedotovskaya, 2015; Pitsiladis et al., 2016; Naureen et al., 2020; Varillas-Delgado et al., 2022), and “talent identification” (Pickering et al., 2019) as a field of application.

“Omics and technology” were identified as Opportunities in the current overview. (Bray, 2000; Brutsaert and Parra, 2006; Bouchard, 2011; Bouchard et al., 2011; Eynon et al., 2011; Pérusse et al., 2013; Wang et al., 2013; Wolfarth et al., 2014; Ahmetov and Fedotovskaya, 2015; Bouchard, 2015; Bouchard et al., 2015; Gibson, 2016; Mattsson et al., 2016; Pitsiladis et al., 2016; Sarzynski et al., 2016; Wang et al., 2016; Moran and Pitsiladis, 2017; Landen et al., 2019; Pickering and Kiely, 2019; Gomes et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Sellami et al., 2021; Kim et al., 2022; Varillas-Delgado et al., 2022) Many reviewers agreed that by integrating “multi-omics” research approaches (e.g., epigenomics, transcriptomics, proteomics, metabolomics, etc.) more complex molecular pathways could be analyzed, which may allow to “explore a more comprehensive picture of athletic performance and its exercise-related traits”. (Bouchard, 2011; Bouchard et al., 2011; Eynon et al., 2011; Pérusse et al., 2013; Wolfarth et al., 2014; Ahmetov and Fedotovskaya, 2015; Bouchard, 2015; Bouchard et al., 2015; Gibson, 2016; Mattsson et al., 2016; Sarzynski et al., 2016; Wang et al., 2016; Moran and Pitsiladis, 2017; Landen et al., 2019; Pickering and Kiely, 2019; Gomes et al., 2020; Tanisawa et al., 2020; Sellami et al., 2021; Kim et al., 2022; Varillas-Delgado et al., 2022) In addition, others’ argued that “whole genome/exome sequencing” and “RNA expression profiling” next to other cutting-edge technologies would provide promising approaches in future to explore rare variants, copy number variation, and other structural variants. (Bray, 2000; Brutsaert and Parra, 2006; Bouchard, 2011; Wang et al., 2013; Ahmetov and Fedotovskaya, 2015; Bouchard, 2015; Gibson, 2016; Pitsiladis et al., 2016; Vellers et al., 2018; Pickering and Kiely, 2019; Tanisawa et al., 2020; Sellami et al., 2021; Varillas-Delgado et al., 2022) For example, according to Griswold et al. (2021) both advances in technologies together with multi-omics approaches will be necessary to “truly have a holistic view of genomics.” (Griswold et al., 2021)

Several narratives described “multicenter (genome-wide association) studies” as an Opportunity for detecting new variants by increasing the studies’ statistical power. (Bouchard, 2011; Eynon et al., 2011; Hagberg et al., 2011; Wang et al., 2013; Ahmetov and Fedotovskaya, 2015; Bouchard, 2015; Loos et al., 2015; Mattsson et al., 2016; Wang et al., 2016; Moran and Pitsiladis, 2017; Vlahovich et al., 2017; Vellers et al., 2018; Landen et al., 2019; Gomes et al., 2020; Griswold et al., 2021; Sellami et al., 2021; Kim et al., 2022; Varillas-Delgado et al., 2022) For example, the large scale and multicenter Athlome Project was launched in 2015 with the goal to “generate an ethically sound environment, interest, and capacity needed to develop the specialist knowledge to inform personalized training and injury prevention, as well as doping detection”. (Pitsiladis et al., 2016) Wang and others (2016) stated: “This unique collaborative initiative has the greatest chance to succeed where individual efforts have failed, to increase our understanding of the biology of exercise performance and related performance traits.” (Wang et al., 2016)

Other themes identified by the thematic analysis and highlighted by various reviewers were linked to genetic “screening, prevention, and therapy”—which may contribute to the “health of athletes”. (Sharp, 2008; McNamee et al., 2009; Wackerhage et al., 2009; Lippi et al., 2010; Bouchard, 2011; Pérusse et al., 2013; Breitbach et al., 2014; Bouchard, 2015; Vlahovich et al., 2017; Pickering and Kiely, 2020; Tanisawa et al., 2020; Griswold et al., 2021) For example, according to the “Sport and Exercise Genomics” consensus statement from 2020, (Tanisawa et al., 2020), genetic testing “may have a potential role in cardiac screening”. Gene editing may also offer therapeutic opportunities, for instance gene editing may help to heal ligament and tendon injuries. (Lippi et al., 2010; Tanisawa et al., 2020) Additionally, Lippi et al. (2010) stated: “genetic testing might be helpful in the anti-doping context”, which was also raised by Varillas-Delgado and others (2022). (Lippi et al., 2010; Varillas-Delgado et al., 2022). Finally, according to Tanisawa et al. (2020) exercise genetics/genomics has the potential for “commercial use”, which was also an identified Opportunity by the current sSWOT. (Tanisawa et al., 2020)

One Threat identified by the thematic analysis was related to “ethical concerns” of genetic testing as raised by many reviewers. (McNamee et al., 2009; Wackerhage et al., 2009; Guth and Roth, 2013; Breitbach et al., 2014; Webborn et al., 2015; Pitsiladis et al., 2016; Sarzynski et al., 2016; Wang et al., 2016; Vlahovich et al., 2017; Pickering et al., 2019; Gray and Semsarian, 2020; Naureen et al., 2020; Tanisawa et al., 2020) For instance, athletes must give informed consent when participating in genetic testing, which may already be problematic in adults—but is even more challenging in youth. (Guth and Roth, 2013; Wang et al., 2016; Vlahovich et al., 2017) According to the consensus statement concerning genetic testing from 2015, (Webborn et al., 2015), athletes must have received “sufficient relevant information to understand the risks, benefits, limitations, and implications of the genetic test”. In addition, several authors raised concerns about “autonomy”, (McNamee et al., 2009; Breitbach et al., 2014), “privacy”, (Webborn et al., 2015; Vlahovich et al., 2017), “reidentification”, (Pitsiladis et al., 2016; Tanisawa et al., 2020), “confidentiality”, (McNamee et al., 2009; Vlahovich et al., 2017), “social stigma” and “discrimination” (Vlahovich et al., 2017)—issues associated with genetic testing of athletes. (Webborn et al., 2015; Pitsiladis et al., 2016; Vlahovich et al., 2017; Tanisawa et al., 2020) Further, “sample and data storage”, (Pitsiladis et al., 2016; Vlahovich et al., 2017), “data sharing”, and “third-party access” (Webborn et al., 2015) have been highlighted by the reviewers. Also, the chance of incidental findings of mutations causing genetic disorders may have “severe psychological consequences such as depression or suicide” and consequences for “marriage, employment, life insurance, or reproductive choices”. (Wackerhage et al., 2009) Another ethical issue associated with genetic testing of athletes identified by the thematic analysis was “family relatedness” since the test results “may have direct health implications for other family members.” (Webborn et al., 2015)

“Direct-to-consumer genetic testing companies” were identified by the thematic analysis and clustered as Threats. Several reviews mentioned that companies e-commerce directly to consumers sport-related genetic tests (McNamee et al., 2009; Guth and Roth, 2013; Breitbach et al., 2014; Webborn et al., 2015; Sarzynski et al., 2016; Vlahovich et al., 2017; Pickering et al., 2019; Naureen et al., 2020; Tanisawa et al., 2020; Griswold et al., 2021; Varillas-Delgado et al., 2022) although the AIS-Athlome consortium-FIMS joint statement from 2017 specified that “there is no current clinical application for genetic testing in the area of exercise prescription and injury prevention”. (Vlahovich et al., 2017) Often, commercial pressure would result in the “premature exploitation of data that have limited or no scientific bases given no or limited replication and validation”. (Tanisawa et al., 2020) Other companies would not “be disclosing what variants are being tested” (Sarzynski et al., 2016) and may use “misleading marketing claims”. (Vlahovich et al., 2017) Some authors argued that athletes and coaches might not be able to “understand the limitations and implications of genetic test results”. (Guth and Roth, 2013) Further, most of the companies “would not provide genetic counselling”, a central criticism mentioned by several reviewers with respect to direct-to-consumer genetic testing. (McNamee et al., 2009; Webborn et al., 2015; Vlahovich et al., 2017; Gray and Semsarian, 2020; Tanisawa et al., 2020) Finally, the “lack of universally accepted guidelines and legislation for direct-to-consumer genetic testing companies” has been highlighted by one reviewer. (Varillas-Delgado et al., 2022)

The last theme identified by the thematic analysis and highlighted by several reviewers was linked to “gene doping/editing”. (Sharp, 2008; Ostrander et al., 2009; Lippi et al., 2010; Vlahovich et al., 2017; Tanisawa et al., 2020; Varillas-Delgado et al., 2022) Gene doping/editing involves manipulating genetic material and regulating gene expression (e.g., increasing or decreasing the production of certain enzymes or proteins) to enhance athletic performance. (Cantelmo et al., 2020) One author stressed the possible side effects of gene editing. (Varillas-Delgado et al., 2022) Furthermore, the AIS-Athlome consortium-FIMS joint statement (2017) stated: “There is no role for gene-editing for the purposes of performance enhancement and all genetic manipulations are banned under the World Anti-Doping Agency”. (Vlahovich et al., 2017) According to Varillas Delgado et al. (2022) it is “unclear if there will ever be capacity to detect any type of gene modification by traditional laboratory techniques”. (Varillas-Delgado et al., 2022) In addition, “DNA testing and gene editing with embryos” was outlined as potential Threat. (Tanisawa et al., 2020) “Designing athletes with extraordinary athletic performance by using gene-editing technique would be a real threat in terms of keeping sport fair, clean and protecting athlete health” according to the sport and exercise genomics consensus update 2019. (Tanisawa et al., 2020)