Has Athletic Performance Reached its Peak?
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ABSTRACT:
SUBMITTER: Berthelot G
PROVIDER: S-EPMC4536275 | biostudies-literature | 2015 Sep
REPOSITORIES: biostudies-literature
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Project description:Background Despite advances in pediatric health care over recent decades, it is not clear whether survival in children with congenital heart disease (CHD) is still increasing. Methods and Results We identified all patients with CHD using nationwide Swedish health registries for 1980 to 2017. We examined the survival trends in children with CHD; we investigated the mortality risk in patients with CHD compared with matched controls without CHD from the general population using Cox proportional regression models and Kaplan-Meier survival analysis. Among 64 396 patients with CHD and 639 012 matched controls without CHD, 3845 (6.0%) and 2235 (0.3%) died, respectively. The mean study follow-up (SD) was 11.4 (6.3) years in patients with CHD. The mortality risk was 17.7 (95% CI, 16.8-18.6) times higher in children with CHD compared with controls. The highest mortality risk was found during the first 4 years of life in patients with CHD (hazard ratio [HR], 19.6; 95% CI, 18.5-20.7). When stratified by lesion group, patients with non-conotruncal defects had the highest risk (HR, 97.2; 95% CI, 80.4-117.4). Survival increased substantially according to birth decades, but with no improvement after the turn of the century where survivorship reached 97% in children with CHD born in 2010 to 2017. Conclusions Survival in children with CHD has increased substantially since the 1980s; however, no significant improvement has been observed this century. Currently, >97% of children with CHD can be expected to reach adulthood highlighting the need of life-time management.
| S-EPMC7763707 | biostudies-literature
Project description:Phenotypes of athletic performance and exercise capacity are complex traits influenced by both genetic and environmental factors. This update on the panel of genetic markers (DNA polymorphisms) associated with athlete status summarises recent advances in sports genomics research, including findings from candidate gene and genome-wide association (GWAS) studies, meta-analyses, and findings involving larger-scale initiatives such as the UK Biobank. As of the end of May 2023, a total of 251 DNA polymorphisms have been associated with athlete status, of which 128 genetic markers were positively associated with athlete status in at least two studies (41 endurance-related, 45 power-related, and 42 strength-related). The most promising genetic markers include the AMPD1 rs17602729 C, CDKN1A rs236448 A, HFE rs1799945 G, MYBPC3 rs1052373 G, NFIA-AS2 rs1572312 C, PPARA rs4253778 G, and PPARGC1A rs8192678 G alleles for endurance; ACTN3 rs1815739 C, AMPD1 rs17602729 C, CDKN1A rs236448 C, CPNE5 rs3213537 G, GALNTL6 rs558129 T, IGF2 rs680 G, IGSF3 rs699785 A, NOS3 rs2070744 T, and TRHR rs7832552 T alleles for power; and ACTN3 rs1815739 C, AR ≥21 CAG repeats, LRPPRC rs10186876 A, MMS22L rs9320823 T, PHACTR1 rs6905419 C, and PPARG rs1801282 G alleles for strength. It should be appreciated, however, that elite performance still cannot be predicted well using only genetic testing.
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Project description:An individual's dietary and supplement strategies can influence markedly their physical performance. Personalized nutrition in athletic populations aims to optimize health, body composition, and exercise performance by targeting dietary recommendations to an individual's genetic profile. Sport dietitians and nutritionists have long been adept at placing additional scrutiny on the one-size-fits-all general population dietary guidelines to accommodate various sporting populations. However, generic "one-size-fits-all" recommendations still remain. Genetic differences are known to impact absorption, metabolism, uptake, utilization and excretion of nutrients and food bioactives, which ultimately affects a number of metabolic pathways. Nutrigenomics and nutrigenetics are experimental approaches that use genomic information and genetic testing technologies to examine the role of individual genetic differences in modifying an athlete's response to nutrients and other food components. Although there have been few randomized, controlled trials examining the effects of genetic variation on performance in response to an ergogenic aid, there is a growing foundation of research linking gene-diet interactions on biomarkers of nutritional status, which impact exercise and sport performance. This foundation forms the basis from which the field of sport nutrigenomics continues to develop. We review the science of genetic modifiers of various dietary factors that impact an athlete's nutritional status, body composition and, ultimately athletic performance.
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Project description:Purposein the last two decades, several evidences have been provided to support the relationship between single nucleotide polymorphisms and the susceptibility to develop injuries participating in sport and performance related to sports activity. We report up-to-date review of the genetics factors involved in tendon injuries and athletic performance.Methodswe searched PubMed using the terms "sports injuries", "athletic performance" and "genetics" over the period 1990 to the present day. We also included non-English journals.Resultsmost of the currently established or putative tendinopathy susceptibility loci have been analyzed by candidate gene studies. The genes currently associated with tendon injuries include gene encoding for collagen, matrix metallopeptidase, tenascin and growth factors. Several genes have been related to the physical performance phenotypes affecting endurance capacity and muscle performance. The most studied include ACE and ACTN3 genes.Conclusionsgenetics determines the response of an individual to the surrounding environment. Recently, some of the individual genetic variations contributing to the athletic performance and the onset of musculoskeletal injuries, particularly in tendon and ligament tissues, have been identified. However, the identification of the genetic background related to susceptibility to injuries and physical performance of the athletes is challenging yet and further studies must be performed to establish the specific role of each gene and the potential effect of the interaction of these.
| S-EPMC3838326 | biostudies-literature
Project description:BACKGROUND: The World Anti-Doping Agency (WADA) publishes the Prohibited List, a manually compiled international standard of substances and methods prohibited in-competition, out-of-competition and in particular sports. It would be ideal to be able to identify all substances that have one or more performance-enhancing pharmacological actions in an automated, fast and cost effective way. Here, we use experimental data derived from the ChEMBL database (~7,000,000 activity records for 1,300,000 compounds) to build a database model that takes into account both structure and experimental information, and use this database to predict both on-target and off-target interactions between these molecules and targets relevant to doping in sport. RESULTS: The ChEMBL database was screened and eight well populated categories of activities (Ki, Kd, EC50, ED50, activity, potency, inhibition and IC50) were used for a rule-based filtering process to define the labels "active" or "inactive". The "active" compounds for each of the ChEMBL families were thereby defined and these populated our bioactivity-based filtered families. A structure-based clustering step was subsequently performed in order to split families with more than one distinct chemical scaffold. This produced refined families, whose members share both a common chemical scaffold and bioactivity against a common target in ChEMBL. CONCLUSIONS: We have used the Parzen-Rosenblatt machine learning approach to test whether compounds in ChEMBL can be correctly predicted to belong to their appropriate refined families. Validation tests using the refined families gave a significant increase in predictivity compared with the filtered or with the original families. Out of 61,660 queries in our Monte Carlo cross-validation, belonging to 19,639 refined families, 41,300 (66.98%) had the parent family as the top prediction and 53,797 (87.25%) had the parent family in the top four hits. Having thus validated our approach, we used it to identify the protein targets associated with the WADA prohibited classes. For compounds where we do not have experimental data, we use their computed patterns of interaction with protein targets to make predictions of bioactivity. We hope that other groups will test these predictions experimentally in the future.
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Project description:There is increasing evidence for strong genetic influences on athletic performance and for an evolutionary "trade-off" between performance traits for speed and endurance activities. We have recently demonstrated that the skeletal-muscle actin-binding protein alpha-actinin-3 is absent in 18% of healthy white individuals because of homozygosity for a common stop-codon polymorphism in the ACTN3 gene, R577X. alpha-Actinin-3 is specifically expressed in fast-twitch myofibers responsible for generating force at high velocity. The absence of a disease phenotype secondary to alpha-actinin-3 deficiency is likely due to compensation by the homologous protein, alpha-actinin-2. However, the high degree of evolutionary conservation of ACTN3 suggests function(s) independent of ACTN2. Here, we demonstrate highly significant associations between ACTN3 genotype and athletic performance. Both male and female elite sprint athletes have significantly higher frequencies of the 577R allele than do controls. This suggests that the presence of alpha-actinin-3 has a beneficial effect on the function of skeletal muscle in generating forceful contractions at high velocity, and provides an evolutionary advantage because of increased sprint performance. There is also a genotype effect in female sprint and endurance athletes, with higher than expected numbers of 577RX heterozygotes among sprint athletes and lower than expected numbers among endurance athletes. The lack of a similar effect in males suggests that the ACTN3 genotype affects athletic performance differently in males and females. The differential effects in sprint and endurance athletes suggests that the R577X polymorphism may have been maintained in the human population by balancing natural selection.
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Project description:We present a novel, quantitative view on the human athletic performance of individual runners. We obtain a predictor for running performance, a parsimonious model and a training state summary consisting of three numbers by application of modern validation techniques and recent advances in machine learning to the thepowerof10 database of British runners' performances (164,746 individuals, 1,417,432 performances). Our predictor achieves an average prediction error (out-of-sample) of e.g. 3.6 min on elite Marathon performances and 0.3 seconds on 100 metres performances, and a lower error than the state-of-the-art in performance prediction (30% improvement, RMSE) over a range of distances. We are also the first to report on a systematic comparison of predictors for running performance. Our model has three parameters per runner, and three components which are the same for all runners. The first component of the model corresponds to a power law with exponent dependent on the runner which achieves a better goodness-of-fit than known power laws in the study of running. Many documented phenomena in quantitative sports science, such as the form of scoring tables, the success of existing prediction methods including Riegel's formula, the Purdy points scheme, the power law for world records performances and the broken power law for world record speeds may be explained on the basis of our findings in a unified way. We provide strong evidence that the three parameters per runner are related to physiological and behavioural parameters, such as training state, event specialization and age, which allows us to derive novel physiological hypotheses relating to athletic performance. We conjecture on this basis that our findings will be vital in exercise physiology, race planning, the study of aging and training regime design.
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Project description:Master athletes maintain high physical activity levels and have better health than age-matched non-athletes. World records show accelerated declines after age 70 in swimming, long-distance running and sprint performance. However, less is known about age-related performance declines in the general master athlete population and whether decline rates differ between disciplines and genders. We interrogated a dataset including all track and field athletes of North Rhine from 2001 to 2014 to assess age-related changes in performance. 27,088 results of athletes between 11 and 89 years of age in 12 disciplines were analyzed by regression statistics. The analyses showed an accelerated decline beyond the age of 70 in sprint, middle- and long-distance running, while in throwing and jumping disciplines the performance continued a linear decline. Patterns of decline differed between men and women. The steepest declines were observed in javelin throw and 400 m (women), and in pole vault and 800 m (men). In conclusion, performance declines in aging depend more on the specific profile of requirements than previously assumed.
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Project description:In the past decades, much research has examined the negative effects of stressors on the performance of athletes. However, according to evolutionary biology, organisms may exhibit growth under stress, a phenomenon called antifragility. For both coaches and their athletes, a key question is how to design training conditions to help athletes develop the kinds of physical, physiological, and behavioral adaptations underlying antifragility. An answer to this important question requires a better understanding of how individual athletes respond to stress or loads in the context of relevant sports tasks. In order to contribute to such understanding, the present study leverages a theoretical and methodological approach to generate individualized load-response profiles in the context of a climbing task. Climbers (n = 37) were asked to complete different bouldering (climbing) routes with increasing loading (i.e. difficulty). We quantified the behavioral responses of each individual athlete by mathematically combining two measures obtained for each route: (a) maximal performance (i.e. the percentage of the route that was completed) and (b) number of attempts required to achieve maximal performance. We mapped this composite response variable as a function of route difficulty. This procedure resulted in load-response curves that captured each athlete's adaptability to stress, termed phenotypic plasticity (PP), specifically operationalized as the area under the generated curves. The results indicate individual load-response profiles (and by extension PP) for athletes who perform at similar maximum levels. We discuss how these profiles might be used by coaches to systematically select stress loads that may be ideally featured in performance training.
| S-EPMC7078366 | biostudies-literature
Project description:This study aimed to investigate the relationship between power-oriented genetic polymorphisms and weightlifting status, create a total genotype score (TGS), and validate the association between TGS models and power-oriented athletes. First, 192 weightlifters and 416 controls were studied, and 12 polymorphisms that have previously been associated with strength, power status, and phenotype were genotyped using the TaqMan SNP genotyping assay. We calculated the TGS for the 12 polymorphisms using a PWM (power-oriented whole model) and for 6 of them using a WRM (weightlifting-related model) based on a case-control study. Second, the TGS of the WRM was compared for 177 strength and power athletes and 416 controls. There was no significant difference in the PWM score between weightlifters and the controls. Weightlifters and elite weightlifters had higher WRM scores than the controls. However, the WRM score had no association with weightlifting performance. There was no significant difference in the WRM between power-oriented athletes and the controls. Our study was able to create a TGS model for weightlifters based on case-control results. However, the TGS model could not be applied to other power-oriented athletes.
| S-EPMC9690594 | biostudies-literature