Showing papers by "Alun G. Williams published in 2008"

Similarity of polygenic profiles limits the potential for elite human physical performance

Abstract: Human physical capability is influenced by many environmental and genetic factors, and it is generally accepted that physical capability phenotypes are highly polygenic. However, the ways in which relevant polymorphisms combine to influence the physical capability of individuals and populations are unknown. Initially, the literature was searched to identify associations between 23 genetic polymorphisms and human endurance phenotypes. Next, typical genotype frequencies of those polymorphisms in the general population were obtained from suitable literature. Using probability calculations, we found only a 0.0005% chance of a single individual in the world having the 'preferable' form of all 23 polymorphisms. As the number of DNA variants shown to be associated with human endurance phenotypes continues to increase, the probability of any single individual possessing the 'preferable' form of each polymorphism will become even lower. However, with population turnover, the chance of such genetically gifted individuals existing increases. To examine the polygenic endurance potential of a human population, a 'total genotype score' (for the 23 polymorphisms) was calculated for each individual within a hypothetical population of 1000 000. There was considerable homogeneity in terms of genetic predisposition to high endurance potential, with 99% of people differing by no more than seven genotypes from the typical profile. Consequently, with population turnover world and Olympic records should improve even without further enhancement of environmental factors, as more 'advantageous' polygenic profiles occasionally, though rarely, emerge. More broadly, human potential appears limited by the similarity of polygenic profiles at both the 'elite sport' and 'chronic disorder' ends of the performance continuum.

Allometric scaling of strength measurements to body size.

Abstract: For comparative purposes, normalisation of strength measures to body size using allometric scaling is recommended. A wide range of scaling exponents have been suggested, typically utilising body mass, although a comprehensive evaluation of different body size variables has not been documented. Differences between force (F) and torque (T) measurements of strength, and the velocity of measurement might also explain some of the variability in the scaling exponents proposed. Knee extensor strength of 86 young men was assessed with measurement of torque at four velocities (0-4.19 rad s(-1)) and force measured isometrically. Body size variables included body mass, height and fat-free mass. Scaling exponents for torque were consistently higher than for force, but the velocity of torque measurement had no influence. As the confounding effects of fat mass were restricted, scaling exponents and the strength of the power-function relationships progressively increased. Fat-free mass determined a surprisingly high proportion of the variance in measured strength (F, 31%; T, 52-58%). Absolute force and torque measurements, and even torque normalised for body mass, were significantly influenced by height, although strength measures normalised to fat-free mass were not. To normalise strength measurements to body mass, for relatively homogenous lean populations (body fat 20%) lower body mass exponents appear more suitable (F, 0.45; T, 0.68). Nevertheless, fat-free mass is the recommended index for scaling strength to body size, and higher exponents (F, 0.76; T, 1.12) are advocated in this case.

Reply from Alun G. Williams and Jonathan P. Folland

Abstract: The weight of evidence suggests, and indeed it is widely accepted, that physical performance phenotypes are highly polygenic (Rankinen et al. 2006; Spurway, 2006). Based on that suggestion and using clearly defined inclusion criteria, in our recent article (Williams & Folland, 2008) we showed that human genetic potential for endurance performance depends on polymorphisms of at least 23 loci and probably many more. We then developed the first genetic algorithm for endurance performance and used this to show that it is extremely unlikely that even a single individual in the world possesses what could be termed a ‘perfect’ polygenic profile for endurance. We concluded that world records should continue to advance, although probably at a steadily reducing rate, purely through an ever-increasing pool of participants that includes individuals with genetic profiles more advantageous for endurance performance. The current letter to the editor advances the notion that ‘mental’ factors make significant contributions to success in sport. For example, mental toughness, tactical astuteness, team coherence, anticipation and decision-making, and motivation to endure pain during training and competition were suggested as key psychological traits. We would agree unreservedly. The qualities that make a champion athlete are legion and, we believe, certainly include those psychological factors suggested. We are aware of the impact that psychological factors can play in sport (Gould et al. 2002) and can have upon endurance-related phenotypes specifically (Crews, 1992). Accordingly we would encourage efforts to explore genetic influences on the psychological traits that influence endurance. Although rather outside our particular fields of expertise, we believe the first steps in identifying genetic influences on psychological traits that influence endurance performance would be to collate evidence to demonstrate that certain psychological traits are unequivocally related to improved endurance performance. In other words, a body of evidence similar to that associating maximal rate of oxygen uptake, economy of movement, lactate/ventilatory threshold and oxygen uptake kinetics (Jones & Carter, 2000) with endurance performance. To the best of our knowledge this has not yet been achieved. Next, evidence from twin or family studies would be useful to confirm and quantify the extent of the genetic (versus environmental) influences on those psychological phenotypes. In other words, evidence similar to that for the maximal rate of oxygen uptake, where heritability estimates are typically around 50% both in sedentary individuals and in terms of their response to training (Klissouras, 1971; Bouchard et al. 1986, 1998, 1999; Fagard et al. 1991). If those steps are taken successfully, researchers could then use their understanding of the underlying neurophysiology to identify candidate genes and examine their association (in cross-sectional or longitudinal studies) with critical psychological phenotypes. The demonstration of such genotype–phenotype associations would justify inclusion of those genetic loci in an updated genetic algorithm for endurance performance. An alternative and more direct approach involves identifying candidate genes for exercise and competition behaviours and investigating their association with endurance performance, irrespective of whether psychological phenotypes are or can be measured. The fact is that if any particular genetic polymorphism is associated with endurance sufficiently, regardless of mechanism, then that polymorphism should be identifiable using a ‘case-control’ study design, comparing elite athletes with non-elite controls. Six of the 23 polymorphisms included in our algorithm fell into this category, i.e. the only evidence of association with an endurance phenotype was from a case-control study with no direct evidence of the mechanism (mental or physical). Therefore, it is possible that some of the identified polymorphisms have neurophysiological and behavioural mechanisms of action, although in most cases there are good reasons for thinking the mechanism is local to skeletal muscle or the cardiovascular system. A further development of research of this kind that, initially at least, completely disregards the likely underlying physiological mechanisms, would be to conduct a genome-wide case-control study that does not have a priori hypotheses regarding particular genes. While this approach is proving fruitful in the study of genotype associations with phenotypes that are overtly related to disease (Altshuler & Daly, 2007), no equivalent study has yet been conducted with phenotypes chosen specifically because they are associated with elite athletic performance. It is probably only a matter of time before this occurs. The information that results can be incorporated into updated versions of the novel genetic algorithm for human endurance that we published recently in this journal (Williams & Folland, 2008).