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Can the ability to adapt to exercise be considered a talent—and if so, can we test for it?

Sports Medicine - Open volume 3, Article number: 43 (2017) Cite this article

Abstract

Talent identification (TI) is a popular and hugely important topic within sports performance, with an ever-increasing amount of resources dedicated to unveiling the next sporting star. However, at present, most TI processes appear to select high-performing individuals at the present point in time, as opposed to identifying those individuals with the greatest capacity to improve. This represents a potential inefficiency within the TI process, reducing its effectiveness. In this article, we discuss whether the ability to adapt favorably, and with a large magnitude, to physical training can be considered a talent, testing it against proposed criteria. We also discuss whether, if such an ability can be considered a talent, being able to test for it as part of the TI process would be advantageous. Given that such a capacity is partially heritable, driven by genetic variation between individuals that mediate the adaptive response, we also explore whether the information gained from genetic profiling can be used to identify those with the greatest capacity to improve. Although there are some ethical hurdles which must be considered, the use of genetic information to identify those individuals with the greatest capacity appears to hold promise and may improve both the efficiency and effectiveness of contemporary TI programmes.

Key points

  1. 1.

    Talent identification programmes often identify those with the greatest current ability, as opposed to the greatest capacity to improve.

  2. 2.

    This capacity to improve is linked to physical adaptation to exercise, which is partially genetically mediated.

  3. 3.

    Genetic profiling holds promise in being able to identify those individuals with the greatest capacity to improve, as well as the best methods through which to yield these improvements.

Background

The accurate identification of youth sporting talent has, in recent decades, emerged as a hugely important and yet controversial topic [1, 2]. Interest in talent identification (TI) is illustrated by a growing academic literature [1,2,3], along with a number of best-selling popular-science books on the topic [4,5,6,7]. Traditionally, sporting TI programmes have, through a mix of subjective and objective tests, sought to identify young athletes with “talent,” using this identification as a prediction of adult performance. However, despite the massive allocation of resources into the identification and development of young talent, it remains unclear whether or not early TI processes are either empirically justified or practically effective.

One fundamental limiting factor is that physical performance tests employed to discern between those who have the talent to excel in the future, and those who do not, actually only provide a snapshot of current abilities. The subsequent logical leap is the presumption that those who perform well at that given time are most likely to be successful as adults. Yet, due to the inherently non-linear complex nature of biological maturation, these performance snapshots offer inherently poor predictive value. As an illustration, within athletes competing in the 2012 Olympic 100 m final, personal bests at age 18 ranged from 10.27–10.48 s. In comparison, one of this paper’s authors (CP) ran 10.22 s at this age, faster than all the finalists. Yet, whilst these athletes progressed to achieve multiple sub-10s 100 m times, CP peaked at 10.14 s.

The reasons why CP, along with countless other high-performing juniors, did not maintain their relative world standings are obviously complex, varied and multifactorial [8, 9]. This illustrates the gross inaccuracies associated with current approaches to predicting future senior potential based on youthful performance. Similarly, where TI processes have been empirically evaluated, these inefficiencies remain, with fewer than 2% of athletes identified as having the potential to be elite within a school sports programme winning senior international medals [10].

Despite these inefficiencies, however, clubs and organizations invest exorbitant sums on TI and development initiatives in the hope of unearthing future talent. Manchester City’s Academy programme, for example, reportedly costs £12 million per year [11]. Yet such large investment is perceived as both economically feasible and justified by the occasional unearthing of exceptional talent; 15 Manchester City Academy graduates have been capped at senior international level, and one, Shaun-Wright Phillips, was sold by the club for £21 million.

A clear limitation of the TI process is that, during maturation, current performance is not directly indicative of future potential. In fact, no standard physical assessment provides insight into how an individual is likely to respond to future training. In this article, we explore the possibility that the utilization of genetic markers associated with the capacity to favorably respond to imposed training stress may provide valuable, and currently missing, insights relating to future trainability, rather than current ability, thus providing clues as to whether the athlete has the innate “talent” to respond to training.

The hereditary aspect of talent

A standardized, widely accepted definition of talent is hard to find. A review of the complexities surrounding an adequate definition of talent is beyond the scope of this article; however, Issurin recently utilized a broad definition of talent as “a special ability that allows someone to reach excellence in some activity in a given domain” [2]. In conceptualizing this definition, Issurin leaned heavily on Howe and colleagues [12], who proposed that talent has five properties: it is partially innate; its full effect may not be evident at an early stage; it has early indications that provide a basis for predicting who might excel; only a few possess it; and it is domain specific.

Implicit within any definition of talent is the assumption that it is at least partially genetically determined. This is most obvious when considering the physiological underpinnings of elite performance, all of which are, to some degree, genetically influenced. Approximately 50% of baseline maximal oxygen uptake (VO2max) is heritable [13], as is 45–99.5% of muscle fibre type [14, 15]. Muscle strength is estimated to be ~ 52% heritable [16]. Anthropometric qualities, often used as TI indicators, are also genetically mediated, with height approximately 80% heritable [17]. So too are non-physical traits associated with elite performance; for example, stress resilience has a genetic component [18, 19], as does motivation to exercise [20]. All of these findings suggest that talent is at least partially mediated by genetic factors. Indeed, de Moor et al. reported that 66% of the variance in elite status is heritable [21].

Whilst elite athlete status appears to have a strong genetic component, to date, it remains apparent that the available genetic information is insufficient to reliably predict those most likely to reach elite status in the future. Gene variants (polymorphisms) most frequent in elite athletes appear to hold little to no predictive ability on their own. For example, a single nucleotide polymorphism (SNP) in ACTN3, a gene encoding for a protein found in fast-twitch muscle fibres, is associated with elite sprint athlete status [22]. Here, between 97 and 100% of elite sprinters have at least one R allele, making the XX genotype rare [23]. However, the fact that at least some elite sprint and speed-power athletes have the XX genotype [24] illustrates that it perhaps lacks the sensitivity required to correctly identify talent. In addition, approximately 82% of the world’s population possess at least one R allele [25], thereby illustrating its lack of discriminatory power in discerning between potential athlete and non-athlete.

The inability of single SNP to effectively discriminate between eventual phenotype has led to the suggestion that utilizing a panel of SNPs, each associated with a physical capacity deemed contributory to elite performance, may provide greater predictive ability. Using such an approach, a total genotype score (TGS) is calculated, with a higher TGS indicative of a greater chance of achieving elite status. This approach has had some success, with mean TGS in athlete groups greater than controls [26, 27], although it does not yet appear to distinguish between competitive levels within athlete groups [28]. Again, however, the sensitivity and specificity are not sufficient to rule out false positives (identifying someone as a future athlete who is later unsuccessful in this endeavor) or false negatives (identifying someone as a future non-athlete, who goes on to become a world-class athlete). As such, the current consensus is that genetic testing has no role to play in the TI process [29, 30], although this opinion is formed on the assumption that elite athletes have common genotypes.

Discussion

Is the ability to adapt to exercise a talent?

Whilst traditional TI programmes attempt to identify future elite performers through the application of physical, psychological and subjective evaluations, it is not clear whether this is the best approach. One issue with the use of such performance tests is that they measure the current status of the athlete, as opposed to the potential for that athlete to improve and develop. Consider the use of a 60-m sprint test in order to identify talented sprinters in a cohort of 15-year-olds. Whilst the test is valid and will accurately identify the quickest athletes, it is not clear that the fastest athletes at age 15 will be fastest at age 25. There is, therefore, a mismatch between what the test measures—current ability—and the TI processes goal—identifying future ability [31]. Instead, the focus of the TI process should be to find individuals with the potential to develop their skills and physiology in order to become successful senior athletes [31], commonly referred to as talent development (TD).

TI programmes, therefore, should attempt to identify those with the greatest ability to develop, provided that their maximal ability is sufficient to be an elite athlete. This fits into a model proposed by Tucker and Collins [8], detailed in Fig. 1, whereby athletes have different baseline abilities that reflect the untrained state, but also different maximal abilities, which represent the performance ceiling for each athlete. There is not necessarily a relationship between the two; an athlete with a high start point might have a low ceiling. Conversely, an athlete with a low start point might have a higher ceiling. In this model, what becomes key is the potential of the athlete to improve with training—and whether they maximize this potential. For exercise adaptation to be considered a talent, it needs to fit the following five criteria proposed by Howe and colleagues [12].

Fig. 1
figure 1

A theoretical model illustrating inter-individual variation in performance and potential (reproduced from [8]). Here, six individuals (A–F) have differing initial performance levels (performance level range on first exposure); F has the lowest, and C has the highest. The individuals also have different ceilings to his/her performance (innate max performance range), with A having the highest potential. However, training represents the journey from baseline potential to final potential; A and E do not train, and so will never reach their ceiling. Whilst C is the current world record holder, B has the potential to outperform them—but only if B can maximize their training to drive the required response. Legend: Max = maximum; asterisk = maximum performance threshold for each individual; triangle = current performance level; black-white circle = initial performance level. Reproduced from [8]. Permission has been granted for reproduction

Full size image

Is exercise adaptation partially innate?

An ever-increasing body of research now suggests that genetic factors modify the adaptive response to exercise. The seminal research in this regard is the HERITAGE (Health, RIsk factors, exercise Training and GEnetics) Family Study, in which sedentary adults undertook a 20-week aerobic exercise training programme. The mean post-intervention improvement in VO2max in this cohort was 384 mL O2 min−1. However, some subjects saw no improvement, whilst others exhibited much larger improvements than the mean, as high as 1100 mL O2 min−1 [32]. Genetic factors accounted for almost 50% of this inter-individual variation [33]. Genetic association studies also show the modifying impact of single SNP on exercise adaptation. For example, R allele carriers of ACTN3 appear to show greater improvements in power following a strength training intervention than X allele carriers [34, 35]. It is clear that exercise adaptation is partly genetically driven, and is therefore innate.

Are the full effects of this talent not fully evident at an early age?

Growth, maturation and the physical development of youth athletes are non-linear in nature [36, 37]. Children and adolescents are physically less able than adult elite athletes due to differences in muscle size, strength [38, 39] and energy system development [40, 41], which may limit the magnitude and type of adaptations that are possible [1, 42]. This was illustrated by Radnor et al. [43], who reported that maturation modified the adaptive response to resistance and plyometric training in a group of adolescent males. Based on these findings, it appears that knowledge of the full ability of a person to be able to adapt to exercise is likely not fully understood until maturation has occurred [42], fulfilling this talent criterion.

Are there early indications of this talent?

This is perhaps the most difficult question to answer as part of these criteria. In part, this is due to a lack of research examining the magnitude of exercise adaptation in youths, and comparing that to either the magnitude of adaptation in those same youths as adults, or associating that adaptive response with sporting success later in life. There are responders and non-responders to specific training interventions in youths [43, 44], but it is not clear how this affects adaptation in adulthood. Nevertheless, the ability to adapt favorably to exercise as a youth will positively impact development by taking the athlete from their baseline towards their performance ceiling, increasing the possibility of adult success.

Do only a minority of people possess this talent?

Overwhelmingly, research suggests that almost everyone has the ability to adapt to exercise, with the small number whom show no improvements labelled as non-responders [45]. However, emerging research suggests such exercise non-response abates with modification of training parameters, such as an increase in training intensity [46] or frequency [47]. However, the magnitude of training response differs between individuals. As detailed earlier, this was apparent in HERITAGE, with a mean post-training VO2max improvement of 19%, although some subjects exhibited improvements of less than 5%, and others improvements of > 40% [48]. Similar wide-ranging magnitudes of adaptation have been reported after strength training and combined strength and endurance training [49,50,51]. It appears that, whilst almost everyone exhibits positive adaptations to exercise, those of the greatest magnitude are limited to a smaller number of individuals, a hallmark of a talent.

Is this talent domain specific?

Whilst genetic variation exhibits a modifying effect on exercise adaptation, the final point to consider is whether this is global (i.e. all types of exercise) or modality specific (i.e. individuals exhibiting large resistance training adaptations do not necessarily exhibit the same adaptive magnitudes to aerobic training). As previously discussed, the ACTN3 R allele is associated with greater improvements in muscle phenotype following resistance training [34, 35]. However, regarding VO2max adaptation, the X allele appears to be associated with larger improvements [52], illustrating that the genetic predisposition to exhibit a greater adaptive response is domain specific. Karavirta et al. [51] randomized subjects to receive strength training only, endurance training only, concurrent strength and endurance training or no training. Within each group, subjects exhibited the expected range of adaptation; however, in the concurrent training group, no subject was in the highest quintile of improvement for both VO2peak and maximal voluntary contraction, again indicating that an ability to respond aerobically is separate to the ability to respond to strength training. It appears, therefore, that the ability to adapt favorably to exercise is specific to particular domains, as opposed to a global ability.

Can we consider exercise adaptation a talent?

Exercise adaptation is a highly complex and individualized process, mediated by genetic, environmental and epigenetic factors [53]. The influence of variation at the genetic level accounting for large amounts of the inter-individual adaptive response to exercise is clear [32, 45, 53], allowing the conclusion that the magnitude of adaptation is partially innate. It is also domain specific, with those possessing the ability to exhibit large improvements following one type of training not guaranteed to exhibit improvements of the same magnitude following a different modality [51]. The presence of a small number of individuals who have very large post-training improvements in a physical trait [48] illustrates that only a few possess this ability. The ability to exhibit large adaptations to exercise is also potentially masked by maturation effects. So far, there is a paucity of evidence examining whether those athletes who are highly adaptable during their youth remain so during their adult years. Nevertheless, based on the evidence available, it does appear that the ability to respond favorably, and with a large magnitude, to exercise can be considered a talent.

Can we test for this talent?

Traditional TI processes appear to identify athletes who are already more able than their peer group, as opposed to those who represent the greatest ability to improve. The ability to test for this latter trait would therefore enhance the TI process, providing some predictive measure as to the future level of the athlete. As Abbott and Collins [31] state, successful prediction of future accomplishments requires identification of characteristics indicating that an individual has the potential to both develop in sport and become a successful senior athlete. Crucially, recent research suggests that individuals respond optimally to different types of training [44, 54, 55], illustrating that being able to match promising youngsters with the training type most likely to elicit the greatest improvements could be invaluable. This can reduce the trial-and-error process, increasing the time period available for an athlete to maximize their potential by minimizing ineffective and inefficient training methods.

Since the ability to respond to exercise is partially mediated by genetic factors, being able to test for these factors holds promise. Given that the impact of any one SNP on this process is likely to be small, a more promising approach is the use of whole genome or large (> 600,000) SNP sequencing. A small number of studies have used this process, with early evidence suggesting they could have some predictive ability [44, 56]. This process is separate from the use of genetic testing to identify the commonly held definition of sporting talent—adult performance—whereby promising athletes’ genetic profiles are compared to a pool of elite athletes to look for commonalities, the assumption being that a greater number of commonalities is associated with a greater chance of being elite. At present, there is no evidence to support this [29]. Indeed, it is likely that different genes impact baseline ability (what is commonly identified in traditional TI processes) and ability to adapt to exercise, as detailed in Fig. 1. Certainly, a greater body of research is required before evidence-based guidelines for the use of genetic testing to support talent development (as opposed to pure TI) can be utilized, but these early findings hold promise. Given the issues discussed within the current TI process, it could be argued that anything that improves the current offering should be utilized.

In addition, there are a host of ethical questions that surround genetic testing, not just within sports, but also public health [57]. For example, is it acceptable to test under 18s, who may not have the required maturity to both fully understand the results in context and give informed consent? What happens if, as part of a routine genetic test, a disease-associated SNP is discovered? To avoid this, should such gene variants be removed from the testing panels? Can clubs insist that their contracted players must undertake a genetic test, and who owns that data when the test is completed? The resolution of such considerations is a challenge to the translation of laboratory-based genetic research to the field, but they are related to how the information is presented and interpreted, as opposed to whether genetic information should or should not be used.

Conclusion

Whilst widespread across sport, traditional TI processes have a number of inherent problems. Perhaps the biggest issue is that they appear to identify current ability, as opposed to future potential, a fact which is not helped by the poor predictive ability of currently used tests of talent. Instead, TI programmes might be better placed to identify youngsters with the greatest capacity to improve, which is partially comprised of the ability to adapt to exercise. As genetic factors account for approximately 50% of the variation in adaptation to exercise, profiling to uncover these genetic underpinnings could be a useful future adjunct to the TI process, and also allow for athletes to undertake training that they are more likely to see favorable adaptations to, creating a personalized training process making athletes more likely to achieve their potential. With the many inefficiencies and high costs associated with TI, it is clear that we only need to be marginally better at the TI process in order to be disproportionately more effective at developing talent, and genetic testing potentially represents this marginal gain. Within this paper, we have focused on the physiological aspects of talent and talent identification. It is, however, worth noting that sporting prowess is not depending solely on physiology, and a number of psycho-emotional and cognitive traits are also associated with athletic achievement. Such traits include, for example, innate stress resilience, and a host of attitudinal factors, such as motivation, perseverance and personality dispositions [2, 3, 58]. Importantly, as with other phenotypes, these capacities are also partially mediated by hereditary influences and partly by life history [59, 60]. In summary, the ability to positively respond to the training stimuli imposed by physical exercise fulfils the required criteria to be considered a talent. The emergence of genetic testing may enable the more accurate identification of athletes who, thanks to a favorable genetic profile, possess a heightened ability to exhibit the greatest responses to training, thus improving the efficiency and efficacy of the talent identification process.

References

  1. Vaeyens R, Lenoir M, Williams AM, Philippaerts RM. Talent identification and development programmes in sport. Sports Med. 2008;38(9):703–14.

    Article  PubMed  Google Scholar 

  2. Issurin VB. Evidence-based prerequisites and precursors of athletic talent: a review. Sports Med. 2017; https://doi.org/10.1007/s40279-017-0740-0.

  3. Collins D, MacNamara Á, McCarthy N. Super champions, champions, and almosts: important differences and commonalities on the rocky road. Front Psychol. 2016;6:2009.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Colvin G. Talent is overrated. New York: Penguin Books; 2008.

  5. Coyle D. The talent code: greatness isn’t born, it’s grown. New York: Random House; 2010.

  6. Syed M. Bounce: Findaway World; 2010.

  7. Ericsson A, Pool R. Peak: secrets from the new science of expertise: Houghton Mifflin Harcourt; 2016.

  8. Tucker R, Collins M. What makes champions? A review of the relative contribution of genes and training to sporting success. Br J Sports Med. 2012;46(8):555–61.

    Article  PubMed  Google Scholar 

  9. Bergeron MF, Mountjoy M, Armstrong N, Chia M, Côté J, Emery CA, Faigenbaum A, Hall G, Kriemler S, Léglise M, Malina RM. International Olympic Committee consensus statement on youth athletic development. Br J Sports Med. 2015;49(13):843–51.

    Article  PubMed  Google Scholar 

  10. Vaeyens R, Güllich A, Warr CR, Philippaerts R. Talent identification and promotion programmes of Olympic athletes. J Sports Sci. 2009;27(13):1367–80.

    Article  PubMed  Google Scholar 

  11. Neil Ashton. Manchester United’s academy has been reduced to an underfunded afterthought… no wonder their youngsters are 30 points behind Manchester City. [internet]. Date [Cited August 27 2017]. Available from: http://www.dailymail.co.uk/sport/football/article-3410732/Manchester-United-s-academy-reduced-underfunded-afterthought-no-wonder-youngsters-30-points-Manchester-City.html

  12. Howe MJ, Davidson JW, Sloboda JA. Innate talents: reality or myth. Behav Brain Sci. 1998;21(3):399–407.

    Article  CAS  PubMed  Google Scholar 

  13. Bouchard C, Rankinen T, Chagnon YC, Rice T, Pérusse L, Gagnon J, Borecki I, An P, Leon AS, Skinner JS, Wilmore JH. Genomic scan for maximal oxygen uptake and its response to training in the HERITAGE Family Study. J Appl Physiol. 2000;88(2):551–9.

    CAS  PubMed  Google Scholar 

  14. Komi PV, Viitasalo JH, Havu M, Thorstensson A, Sjodin B, Karlsson J. Skeletal muscle fibres and muscle enzyme activities in monozygous and dizygous twins of both sexes. Acta Physiol Scand. 1977;100(4):385–92.

    CAS  PubMed  Google Scholar 

  15. Simoneau JA, Bouchard C. Genetic determinism of fiber type proportion in human skeletal muscle. FASEB J. 1995;9(11):1091–5.

    CAS  PubMed  Google Scholar 

  16. Zempo H, Miyamoto-Mikami E, Kikuchi N, Fuku N, Miyachi M, Murakami H. Heritability estimates of muscle strength-related phenotypes: a systematic review and meta-analysis. Scand J Med Sci Sports. 2016; https://doi.org/10.1111/sms.12804.

  17. Silventoinen K, Sammalisto S, Perola M, Boomsma DI, Cornes BK, Davis C, Dunkel L, De Lange M, Harris JR, Hjelmborg JV, Luciano M. Heritability of adult body height: a comparative study of twin cohorts in eight countries. Twin Res. 2003;6(5):399–408.

    Article  PubMed  Google Scholar 

  18. Petito A, Altamura M, Iuso S, Padalino FA, Sessa F, D'Andrea G, Margaglione M, Bellomo A. The relationship between personality traits, the 5HTT polymorphisms, and the occurrence of anxiety and depressive symptoms in elite athletes. PLoS One. 2016;11(6):e0156601.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Sanhueza JA, Zambrano T, Bahamondes-Avila C, Salazar LA. Association of anxiety-related polymorphisms with sports performance in Chilean long distance triathletes: a pilot study. J Sci Med Sport. 2016;15(4):554.

    Google Scholar 

  20. Schutte NM, Nederend I, Hudziak JJ, Bartels M, de Geus EJ. Heritability of the affective response to exercise and its correlation to exercise behavior. Psychol Sport Exerc. 2017;31:139–48.

    Article  PubMed  Google Scholar 

  21. De Moor MH, Spector TD, Cherkas LF, Falchi M, Hottenga JJ, Boomsma DI, De Geus EJ. Genome-wide linkage scan for athlete status in 700 British female DZ twin pairs. Twin Res Hum Genet. 2007;10(6):812–20.

    Article  PubMed  Google Scholar 

  22. Yang N, MacArthur DG, Gulbin JP, Hahn AG, Beggs AH, Easteal S, North K. ACTN3 genotype is associated with human elite athletic performance. Am J Hum Genet. 2003;73(3):627–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Scott RA, Irving R, Irwin L, Morrison E, Charlton V, Austin K, Tladi D, Deason M, Headley SA, Kolkhorst FW, Yang N. ACTN3 and ACE genotypes in elite Jamaican and US sprinters. Med Sci Sports Exerc. 2010;42(1):107–12.

    Article  CAS  PubMed  Google Scholar 

  24. Lucia A, Oliván J, Gómez-Gallego F, Santiago C, Montil M, Foster C. Citius and longius (faster and longer) with no α-actinin-3 in skeletal muscles? Br J Sports Med. 2007;41(9):616–7.

    Article  PubMed  PubMed Central  Google Scholar 

  25. North KN, Yang N, Wattanasirichaigoon D, Mills M, Easteal S, Beggs AH. A common nonsense mutation results in α-actinin-3 deficiency in the general population. Nat Genet. 1999;21(4):353–4.

    Article  CAS  PubMed  Google Scholar 

  26. Ruiz JR, Gómez-Gallego F, Santiago C, González-Freire M, Verde Z, Foster C, Lucia A. Is there an optimum endurance polygenic profile? J Appl Physiol. 2009;587(7):1527–34.

    CAS  Google Scholar 

  27. Ruiz JR, Arteta D, Buxens A, Artieda M, Gómez-Gallego F, Santiago C, Yvert T, Morán M, Lucia A. Can we identify a power-oriented polygenic profile? J Appl Physiol. 2010;108(3):561–6.

    Article  PubMed  Google Scholar 

  28. Santiago C, Ruiz JR, Muniesa CA, González-Freire M, Gómez-Gallego F, Lucia A. Does the polygenic profile determine the potential for becoming a world-class athlete? Insights from the sport of rowing. Scan J Med Sci Sports. 2010;20(1):e188–94.

    Article  CAS  Google Scholar 

  29. Webborn N, Williams A, McNamee M, Bouchard C, Pitsiladis Y, Ahmetov I, Ashley E, Byrne N, Camporesi S, Collins M, Dijkstra P. Direct-to-consumer genetic testing for predicting sports performance and talent identification: consensus statement. Br J Sports Med. 2015;49(23):1486–91.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Vlahovich N, Fricker PA, Brown MA, Hughes D. Ethics of genetic testing and research in sport: a position statement from the Australian Institute of Sport. Br J Sports Med. 2017;51(1):5–11.

    Article  PubMed  Google Scholar 

  31. Abbott A, Collins D. A theoretical and empirical analysis of a ‘state of the art’ talent identification model. High Ability Studies. 2002;13(2):157–78.

    Article  Google Scholar 

  32. Bouchard C, Rankinen T. Individual differences in response to regular physical activity. Med Sci Sports Exerc. 2001;33(6 Suppl):S446–51.

    Article  CAS  PubMed  Google Scholar 

  33. Bouchard C, Sarzynski MA, Rice TK, Kraus WE, Church TS, Sung YJ, Rao DC, Rankinen T. Genomic predictors of the maximal O2 uptake response to standardized exercise training programs. J Appl Physiol. 2011;110(5):1160–70.

    Article  CAS  PubMed  Google Scholar 

  34. Delmonico MJ, Kostek MC, Doldo NA, Hand BD, Walsh S, Conway JM, Carignan CR, Roth SM, Hurley BF. Alpha-actinin-3 (ACTN3) R577X polymorphism influences knee extensor peak power response to strength training in older men and women. J Gerontol A Biol Sci Medic Sci. 2007;62(2):206–12.

    Article  Google Scholar 

  35. Pereira A, Costa AM, Izquierdo M, Silva AJ, Bastos E, Marques MC. ACE I/D and ACTN3 R/X polymorphisms as potential factors in modulating exercise-related phenotypes in older women in response to a muscle power training stimuli. Age. 2013;35(5):1949–59.

    Article  CAS  PubMed  Google Scholar 

  36. Abbott A, Button C, Pepping GJ, Collins D. Unnatural selection: talent identification and development in sport. Nonlinear Dynamics Psychol Life Sci. 2005;9(1):61–88.

    PubMed  Google Scholar 

  37. Lloyd RS, Cronin JB, Faigenbaum AD, Haff GG, Howard R, Kraemer WJ, Micheli LJ, Myer GD, Oliver JL. National Strength and Conditioning Association position statement on long-term athletic development. J Strength Cond Res. 2016;30(6):1491–509.

    Article  PubMed  Google Scholar 

  38. O’Brien TD, Reeves ND, Baltzopoulos V, Jones DA, Maganaris CN. Muscle–tendon structure and dimensions in adults and children. J Anat. 2010;216(5):631–42.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Waugh CM, Korff T, Fath F, Blazevich AJ. Rapid force production in children and adults: mechanical and neural contributions. Med Sci Sports Exerc. 2013;45(4):762–71.

    Article  PubMed  Google Scholar 

  40. Van Praagh E, Doré E. Short-term muscle power during growth and maturation. Sports Med. 2002;32(11):701–28.

    Article  PubMed  Google Scholar 

  41. Ratel S, Duché P, Williams CA. Muscle fatigue during high-intensity exercise in children. Sports Med. 2006;36(12):1031–65.

    Article  PubMed  Google Scholar 

  42. Pearson DT, Naughton GA, Torode M. Predictability of physiological testing and the role of maturation in talent identification for adolescent team sports. J Sci Med Sport. 2006;9(4):277–87.

    Article  CAS  PubMed  Google Scholar 

  43. Radnor JM, Lloyd RS, Oliver JL. Individual response to different forms of resistance training in school-aged boys. J Strength Cond Res. 2017;31(3):787–97.

    Article  PubMed  Google Scholar 

  44. Jones N, Kiely J, Suraci B, Collins DJ, De Lorenzo D, Pickering C, Grimaldi KA. A genetic-based algorithm for personalized resistance training. Biol Sport. 2016;33(2):117.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Timmons JA. Variability in training-induced skeletal muscle adaptation. J Appl Physiol. 2011;110(3):846–53.

    Article  PubMed  Google Scholar 

  46. Ross R, de Lannoy L, Stotz PJ. Separate effects of intensity and amount of exercise on interindividual cardiorespiratory fitness response. Mayo Clin Proc. 2015;90(11):1506–14.

  47. Montero D, Lundby C. Refuting the myth of non-response to exercise training: ‘non-responders’ do respond to higher dose of training. J Physiol. 2017;595(11):3377–87.

    Article  CAS  PubMed  Google Scholar 

  48. Skinner JS, Jaskólski A, Jaskólska A, Krasnoff J, Gagnon J, Leon AS, Rao DC, Wilmore JH, Bouchard C. Age, sex, race, initial fitness, and response to training: the HERITAGE Family Study. J Appl Physiol. 2001;90(5):1770–6.

    CAS  PubMed  Google Scholar 

  49. Hautala AJ, Kiviniemi AM, Mäkikallio TH, Kinnunen H, Nissilä S, Huikuri HV, Tulppo MP. Individual differences in the responses to endurance and resistance training. Eur J Appl Physiol. 2006;96(5):535–42.

    Article  PubMed  Google Scholar 

  50. Hubal MJ, Gordish-Dressman HE, Thompson PD, Price TB, Hoffman EP, Angelopoulos TJ, Gordon PM, Moyna NM, Pescatello LS, Visich PS, Zoeller RF. Variability in muscle size and strength gain after unilateral resistance training. Med Sci Sports Exerc. 2005;37(6):964–72.

    PubMed  Google Scholar 

  51. Karavirta L, Häkkinen K, Kauhanen A, Arija-Blazquez A, Sillanpää E, Rinkinen N, Häkkinen A. Individual responses to combined endurance and strength training in older adults. Med Sci Sports Exerc. 2011;43(3):484–90.

    Article  PubMed  Google Scholar 

  52. Mägi A, Unt E, Prans E, Raus L, Eha J, Veraksitš A, Kingo K, Kõks S. The association analysis between ACE and ACTN3 genes polymorphisms and endurance capacity in young cross-country skiers: longitudinal study. J Sports Sci Med. 2016;15(2):287.

    PubMed  PubMed Central  Google Scholar 

  53. Pickering C, Kiely J. Are the current guidelines on caffeine use in sport optimal for everyone? Inter-individual variation in caffeine ergogenicity, and a move towards personalised sports nutrition. Sports Med. 2017; In Press

  54. Beaven CM, Cook CJ, Gill ND. Significant strength gains observed in rugby players after specific resistance exercise protocols based on individual salivary testosterone responses. J Strength Cond Res. 2008;22(2):419–25.

    Article  PubMed  Google Scholar 

  55. Zarebska A, Jastrzebski Z, Moska W, Leonska-Duniec A, Kaczmarczyk M, Sawczuk M, Maciejewska-Skrendo A, Żmijewski P, Ficek K, Grzegorz T, Lulinska-Kuklik E, Semenova E, Ahmetov I, Cieszczyk P. The AGT gene M235T polymorphism and response of power-related variables to aerobic training. J Sports Sci Med. 2016;15(4):616.

    Google Scholar 

  56. Timmons JA, Knudsen S, Rankinen T, Koch LG, Sarzynski M, Jensen T, Keller P, Scheele C, Vollaard NB, Nielsen S, Åkerström T. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. J Appl Physiol. 2010;108(6):1487–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Camporesi S, McNamee MJ. Ethics, genetic testing, and athletic talent: children’s best interests, and the right to an open (athletic) future. Physiol Genomics. 2016;48(3):191–5.

    Article  CAS  PubMed  Google Scholar 

  58. Gould D, Dieffenbach K, Moffett A. The development of psychological talent in US Olympic champions. Final grant report. Colorado Springs: United States Olympic Committee; 2001.

    Google Scholar 

  59. Penke L, Denissen JJ, Miller GF. The evolutionary genetics of personality. Eur J Pers. 2007;21(5):549–87.

    Article  Google Scholar 

  60. Krueger RF, South S, Johnson W, Iacono W. The heritability of personality is not always 50%: gene-environment interactions and correlations between personality and parenting. J Pers. 2008;76(6):1485–522.

    Article  PubMed  PubMed Central  Google Scholar 

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  1. Institute of Coaching and Performance, School of Sport and Wellbeing, University of Central Lancashire, Preston, UK

    Craig Pickering & John Kiely

  2. Exercise and Nutritional Genomics Research Centre, DNAFit Ltd, London, UK

    Craig Pickering

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CP conceived the idea underpinning this manuscript and prepared the first draft. JK provided critical feedback as to the manuscript’s content and structure and contributed to the writing of the later drafts and final submitted version of the manuscript. Both authors have read and approved the final manuscript.

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CP is an employee of DNAFit Ltd., a genetic testing company, and is undertaking a Professional Doctorate in Elite Performance at the University of Central Lancashire (UK). His research interest is understanding the potential utility of genetic information in elite sport. JK is a Senior Lecture in Elite Performance at the Institute of Coaching & Performance at the University of Central Lancashire.

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Craig Pickering is an employee of DNAFit Ltd. He received no financial incentive for the production of this manuscript which was produced as part of his Professional Doctorate studies. John Kiely has no interests to declare.

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Pickering, C., Kiely, J. Can the ability to adapt to exercise be considered a talent—and if so, can we test for it?. Sports Med - Open 3, 43 (2017). https://doi.org/10.1186/s40798-017-0110-3

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