Letter to the editor: A genetic-based algorithm for personalized resistance training

Monnerat, Gustavo; Paulucio, Dailson; Neto, RS Moura; Silva, R; Pompeu, Fernando; Budowle, Bruce; Santos, Caleb Guedes Miranda dos

doi:10.5114/biolsport.2017.63384

Cited by 4 publications

(4 citation statements)

References 30 publications

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“…After testing for replicability, our results corroborated the previous minor cohort of 25 participants [1]. Although ancestry studies based on genome-wide arrays have shown an important similarity between south-eastern Brazilian and European, African, and Native American populations, the panel of 10 specific performance-related SNPs used in this study revealed very low F ST values between U20_BFDSC and BFDSC, European, and American populations (Table 2).…”

Section: Resultssupporting

confidence: 88%

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Replicative Study in Performance-Related Genes of Brazilian Elite Soccer Players Highlights Genetic Differences from African Ancestry and Similarities between Professional and U20 Youth Athletes

Kanope

Santos

Marinho³

et al. 2023

Genes

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Classically, genetic association studies have attempted to assess genetic polymorphisms related to human physiology and physical performance. However, the heterogeneity of some findings drives the research to replicate, validate, and confirmation as essential aspects for ensuring their applicability in sports sciences. Genetic distance matrix and molecular variance analyses may offer an alternative approach to comparing athletes’ genomes with those from public databases. Thus, we performed a complete sequencing of 44 genomes from male Brazilian first-division soccer players under 20 years of age (U20_BFDSC). The performance-related SNP genotypes were obtained from players and from the “1000 Genomes” database (European, African, American, East Asian, and South Asian). Surprisingly, U20_BFDSC performance-related genotypes had significantly larger FST levels (p < 0.00001) than African populations, although studies using ancestry markers have shown an important similarity between Brazilian and African populations (12–24%). U20_BFDSC were genetically similar to professional athletes, showing the intense genetic selection pressure likely to occur before this maturation stage. Our study highlighted that performance-related genes might undergo selective pressure due to physical performance and environmental, cognitive, and sociocultural factors. This replicative study suggests that molecular variance and Wright’s statistics can yield novel conclusions in exercise science.

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Section: Resultssupporting

confidence: 88%

“…Physical performance is a multifactorial trait to which genetic data can potentially be applied for precision medicine approaches [1]. Classically, genetic association studies (GASs) are used to better understand the effects of genetic variability.…”

Section: Introductionmentioning

confidence: 99%

Replicative Study in Performance-Related Genes of Brazilian Elite Soccer Players Highlights Genetic Differences from African Ancestry and Similarities between Professional and U20 Youth Athletes

Kanope

Santos

Marinho³

et al. 2023

Genes

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show abstract

“…The cost of these tests has dropped in recent years, increasing accessibility [208]. This gives rise to the potential use of genetic tests to inform training programme design, which may have predictive ability [183,209,210]. Whilst single gene models might give some insight into exercise response [62,211], adaptation to exercise is not determined by a single gene.…”

Section: Harnessing This Knowledge To Improve Performancementioning

confidence: 99%

Understanding Personalized Training Responses: Can Genetic Assessment Help?

Pickering¹,

Kiely²

2017

TOSSJ

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Background:Traditional exercise prescription is based on the assumption that exercise adaptation is predictable and standardised across individuals. However, evidence has emerged in the past two decades demonstrating that large inter-individual variation exists regarding the magnitude and direction of adaption following exercise.Objective:The aim of this paper was to discuss the key factors influencing this personalized response to exercise in a narrative review format.Findings:Genetic variation contributes significantly to the personalized training response, with specific polymorphisms associated with differences in exercise adaptation. These polymorphisms exist in a number of pathways controlling exercise adaptation. Environmental factors such as nutrition, psycho-emotional response, individual history and training programme design also modify the inter-individual adaptation following training. Within the emerging field of epigenetics, DNA methylation, histone modifications and non-coding RNA allow environmental and lifestyle factors to impact genetic expression. These epigenetic mechanisms are themselves modified by genetic and non-genetic factors, illustrating the complex interplay between variables in determining the adaptive response. Given that genetic factors are such a fundamental modulator of the inter-individual response to exercise, genetic testing may provide a useful and affordable addition to those looking to maximise exercise adaption, including elite athletes. However, there are ethical issues regarding the use of genetic tests, and further work is needed to provide evidence based guidelines for their use.Conclusion:There is considerable inter-individual variation in the adaptive response to exercise. Genetic assessments may provide an additional layer of information allowing personalization of training programmes to an individual’s unique biology.

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“…The results of this study suggested, for the first time, that genetic information could be used to enhance training adaptations. These findings were somewhat polarizing within the scientific community, receiving both criticism [ 68 ]—which was rebutted [ 69 ]—and praise [ 70 ].…”

Section: The Use Of Genetic Information Within the Personalised Trmentioning

confidence: 99%

The Development of a Personalised Training Framework: Implementation of Emerging Technologies for Performance

Pickering

Kiely

2019

JFMK

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Over the last decade, there has been considerable interest in the individualisation of athlete training, including the use of genetic information, alongside more advanced data capture and analysis techniques. Here, we explore the evidence for, and practical use of, a number of these emerging technologies, including the measurement and quantification of epigenetic changes, microbiome analysis and the use of cell-free DNA, along with data mining and machine learning. In doing so, we develop a theoretical model for the use of these technologies in an elite sport setting, allowing the coach to better answer six key questions: (1) To what training will my athlete best respond? (2) How well is my athlete adapting to training? (3) When should I change the training stimulus (i.e., has the athlete reached their adaptive ceiling for this training modality)? (4) How long will it take for a certain adaptation to occur? (5) How well is my athlete tolerating the current training load? (6) What load can my athlete handle today? Special consideration is given to whether such an individualised training framework will outperform current methods as well as the challenges in implementing this approach.

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Letter to the editor: A genetic-based algorithm for personalized resistance training

Cited by 4 publications

References 30 publications

Replicative Study in Performance-Related Genes of Brazilian Elite Soccer Players Highlights Genetic Differences from African Ancestry and Similarities between Professional and U20 Youth Athletes

Replicative Study in Performance-Related Genes of Brazilian Elite Soccer Players Highlights Genetic Differences from African Ancestry and Similarities between Professional and U20 Youth Athletes

Understanding Personalized Training Responses: Can Genetic Assessment Help?

The Development of a Personalised Training Framework: Implementation of Emerging Technologies for Performance

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