Sports genetics moving forward: lessons learned from medical research

Abstract

Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, we can magnify the breadth and depth of knowledge in the field. We present an outline of challenges facing sports genetics in the light of experiences from medical research. Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes. Improving sports genetics will foremost require analyses based on detailed phenotyping. To find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved. Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between sexes and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology, which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy.

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

“…Notably, the works of four publications have elucidated the sexspecific implications of exercise genetics, which we consider to be a significant yet inadequately represented subject matter within the present body of literature. (Mattsson et al, 2016;Vlahovich et al, 2017;Landen et al, 2019;Kim et al, 2022) We also noticed a trend in time when extracting the data for the present sSWOT analysis: Reviews published around 2000 mainly described genetics, environment, and its interactions. (Bray, 2000;Brutsaert and Parra, 2006;Sharp, 2008) We then recognized a shift from reviews reporting on candidate gene studies (2000-2010) (Bray, 2000;Brutsaert and Parra, 2006;Ostrander et al, 2009;Rankinen et al, 2010) towards RNA expression profiling (2011) and genome-wide and whole exome association studies (2015).…”

“…( Patel and Greydanus, 2002 ) Finally, 45 records were included in this overview based on full text reading. ( Tanisawa et al, 2020 ; Sellami et al, 2021 ; Bouchard, 2015 ; Ahmetov and Fedotovskaya, 2015 ; Vlahovich et al, 2017 ; Bray, 2000 ; Brutsaert and Parra, 2006 ; Sharp, 2008 ; McNamee et al, 2009 ; Ostrander et al, 2009 ; Wackerhage et al, 2009 ; Lippi et al, 2010 ; 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 ; Pérusse et al, 2013 ; Wang et al, 2013 ; Breitbach et al, 2014 ; Wolfarth et al, 2014 ; Bouchard et al, 2015 ; Loos et al, 2015 ; Webborn et al, 2015 ; Gibson, 2016 ; Mattsson et al, 2016 ; Pitsiladis et al, 2016 ; Sarzynski et al, 2016 ; Wang et al, 2016 ; Yan et al, 2016 ; Moran and Pitsiladis, 2017 ; Vellers et al, 2018 ; Landen et al, 2019 ; Pickering and Kiely, 2019 ; Pickering et al, 2019 ; Gomes et al, 2020 ; Gray and Semsarian, 2020 ; Naureen et al, 2020 ; Griswold et al, 2021 ; Wang and Ashokan, 2021 ; Kim et al, 2022 ) The flow chart of the study selection is presented in Figure 1 . The main reasons for exclusion were “discipline specific” reviews (n = 15), ( Eynon et al, 2013 ; Maffulli et al, 2013 ; Tucker et al, 2013 ; Vancini et al, 2014 ; Heffernan et al, 2015 ; Lundby et al, 2017 ; Costello et al, 2018 ; Southward et al, 2018 ...…”

“…( 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 )…”

“…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 ; …”

“…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 ( Rankine...…”

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

“…Notably, the works of four publications have elucidated the sexspecific implications of exercise genetics, which we consider to be a significant yet inadequately represented subject matter within the present body of literature. (Mattsson et al, 2016;Vlahovich et al, 2017;Landen et al, 2019;Kim et al, 2022) We also noticed a trend in time when extracting the data for the present sSWOT analysis: Reviews published around 2000 mainly described genetics, environment, and its interactions. (Bray, 2000;Brutsaert and Parra, 2006;Sharp, 2008) We then recognized a shift from reviews reporting on candidate gene studies (2000-2010) (Bray, 2000;Brutsaert and Parra, 2006;Ostrander et al, 2009;Rankinen et al, 2010) towards RNA expression profiling (2011) and genome-wide and whole exome association studies (2015).…”

“…( Patel and Greydanus, 2002 ) Finally, 45 records were included in this overview based on full text reading. ( Tanisawa et al, 2020 ; Sellami et al, 2021 ; Bouchard, 2015 ; Ahmetov and Fedotovskaya, 2015 ; Vlahovich et al, 2017 ; Bray, 2000 ; Brutsaert and Parra, 2006 ; Sharp, 2008 ; McNamee et al, 2009 ; Ostrander et al, 2009 ; Wackerhage et al, 2009 ; Lippi et al, 2010 ; 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 ; Pérusse et al, 2013 ; Wang et al, 2013 ; Breitbach et al, 2014 ; Wolfarth et al, 2014 ; Bouchard et al, 2015 ; Loos et al, 2015 ; Webborn et al, 2015 ; Gibson, 2016 ; Mattsson et al, 2016 ; Pitsiladis et al, 2016 ; Sarzynski et al, 2016 ; Wang et al, 2016 ; Yan et al, 2016 ; Moran and Pitsiladis, 2017 ; Vellers et al, 2018 ; Landen et al, 2019 ; Pickering and Kiely, 2019 ; Pickering et al, 2019 ; Gomes et al, 2020 ; Gray and Semsarian, 2020 ; Naureen et al, 2020 ; Griswold et al, 2021 ; Wang and Ashokan, 2021 ; Kim et al, 2022 ) The flow chart of the study selection is presented in Figure 1 . The main reasons for exclusion were “discipline specific” reviews (n = 15), ( Eynon et al, 2013 ; Maffulli et al, 2013 ; Tucker et al, 2013 ; Vancini et al, 2014 ; Heffernan et al, 2015 ; Lundby et al, 2017 ; Costello et al, 2018 ; Southward et al, 2018 ...…”

“…( 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 )…”

“…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 ; …”

“…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 ( Rankine...…”

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

“…Notably, the works of four publications have elucidated the sexspecific implications of exercise genetics, which we consider to be a significant yet inadequately represented subject matter within the present body of literature. (Mattsson et al, 2016;Vlahovich et al, 2017;Landen et al, 2019;Kim et al, 2022) We also noticed a trend in time when extracting the data for the present sSWOT analysis: Reviews published around 2000 mainly described genetics, environment, and its interactions. (Bray, 2000;Brutsaert and Parra, 2006;Sharp, 2008) We then recognized a shift from reviews reporting on candidate gene studies (2000-2010) (Bray, 2000;Brutsaert and Parra, 2006;Ostrander et al, 2009;Rankinen et al, 2010) towards RNA expression profiling (2011) and genome-wide and whole exome association studies (2015).…”

“…( Patel and Greydanus, 2002 ) Finally, 45 records were included in this overview based on full text reading. ( Tanisawa et al, 2020 ; Sellami et al, 2021 ; Bouchard, 2015 ; Ahmetov and Fedotovskaya, 2015 ; Vlahovich et al, 2017 ; Bray, 2000 ; Brutsaert and Parra, 2006 ; Sharp, 2008 ; McNamee et al, 2009 ; Ostrander et al, 2009 ; Wackerhage et al, 2009 ; Lippi et al, 2010 ; 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 ; Pérusse et al, 2013 ; Wang et al, 2013 ; Breitbach et al, 2014 ; Wolfarth et al, 2014 ; Bouchard et al, 2015 ; Loos et al, 2015 ; Webborn et al, 2015 ; Gibson, 2016 ; Mattsson et al, 2016 ; Pitsiladis et al, 2016 ; Sarzynski et al, 2016 ; Wang et al, 2016 ; Yan et al, 2016 ; Moran and Pitsiladis, 2017 ; Vellers et al, 2018 ; Landen et al, 2019 ; Pickering and Kiely, 2019 ; Pickering et al, 2019 ; Gomes et al, 2020 ; Gray and Semsarian, 2020 ; Naureen et al, 2020 ; Griswold et al, 2021 ; Wang and Ashokan, 2021 ; Kim et al, 2022 ) The flow chart of the study selection is presented in Figure 1 . The main reasons for exclusion were “discipline specific” reviews (n = 15), ( Eynon et al, 2013 ; Maffulli et al, 2013 ; Tucker et al, 2013 ; Vancini et al, 2014 ; Heffernan et al, 2015 ; Lundby et al, 2017 ; Costello et al, 2018 ; Southward et al, 2018 ...…”

“…( 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 )…”

“…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 ; …”

“…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 ( Rankine...…”

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

“…Notably, the works of four publications have elucidated the sexspecific implications of exercise genetics, which we consider to be a significant yet inadequately represented subject matter within the present body of literature. (Mattsson et al, 2016;Vlahovich et al, 2017;Landen et al, 2019;Kim et al, 2022) We also noticed a trend in time when extracting the data for the present sSWOT analysis: Reviews published around 2000 mainly described genetics, environment, and its interactions. (Bray, 2000;Brutsaert and Parra, 2006;Sharp, 2008) We then recognized a shift from reviews reporting on candidate gene studies (2000-2010) (Bray, 2000;Brutsaert and Parra, 2006;Ostrander et al, 2009;Rankinen et al, 2010) towards RNA expression profiling (2011) and genome-wide and whole exome association studies (2015).…”

“…( Patel and Greydanus, 2002 ) Finally, 45 records were included in this overview based on full text reading. ( Tanisawa et al, 2020 ; Sellami et al, 2021 ; Bouchard, 2015 ; Ahmetov and Fedotovskaya, 2015 ; Vlahovich et al, 2017 ; Bray, 2000 ; Brutsaert and Parra, 2006 ; Sharp, 2008 ; McNamee et al, 2009 ; Ostrander et al, 2009 ; Wackerhage et al, 2009 ; Lippi et al, 2010 ; 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 ; Pérusse et al, 2013 ; Wang et al, 2013 ; Breitbach et al, 2014 ; Wolfarth et al, 2014 ; Bouchard et al, 2015 ; Loos et al, 2015 ; Webborn et al, 2015 ; Gibson, 2016 ; Mattsson et al, 2016 ; Pitsiladis et al, 2016 ; Sarzynski et al, 2016 ; Wang et al, 2016 ; Yan et al, 2016 ; Moran and Pitsiladis, 2017 ; Vellers et al, 2018 ; Landen et al, 2019 ; Pickering and Kiely, 2019 ; Pickering et al, 2019 ; Gomes et al, 2020 ; Gray and Semsarian, 2020 ; Naureen et al, 2020 ; Griswold et al, 2021 ; Wang and Ashokan, 2021 ; Kim et al, 2022 ) The flow chart of the study selection is presented in Figure 1 . The main reasons for exclusion were “discipline specific” reviews (n = 15), ( Eynon et al, 2013 ; Maffulli et al, 2013 ; Tucker et al, 2013 ; Vancini et al, 2014 ; Heffernan et al, 2015 ; Lundby et al, 2017 ; Costello et al, 2018 ; Southward et al, 2018 ...…”

“…( 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 )…”

“…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 ; …”

“…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 ( Rankine...…”