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

In a recent paper entitled “A genetic-based algorithm for personalized resistance training”, Jones et al. [1] presented an algorithm of 15 performance-associated gene polymorphisms that they propose can determine an athlete’s training response by predicting power and endurance potential. However, fr...

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Detalles Bibliográficos
Autores principales: Karanikolou, A, Wang, G, Pitsiladis, Y
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Institute of Sport in Warsaw 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5377557/
https://www.ncbi.nlm.nih.gov/pubmed/28416894
http://dx.doi.org/10.5114/biolsport.2017.63385
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author Karanikolou, A
Wang, G
Pitsiladis, Y
author_facet Karanikolou, A
Wang, G
Pitsiladis, Y
author_sort Karanikolou, A
collection PubMed
description In a recent paper entitled “A genetic-based algorithm for personalized resistance training”, Jones et al. [1] presented an algorithm of 15 performance-associated gene polymorphisms that they propose can determine an athlete’s training response by predicting power and endurance potential. However, from the design of their studies and the data provided, there is no evidence to support these authors’ assertions. Progress towards such a significant development in the field of sport and exercise genomics will require a paradigm shift in line with recent recommendations for international collaborations such as the Athlome Project (see www.athlomeconsortium.org). Large-scale initiatives, involving numerous multi-centre and well-phenotyped exercise training and elite performance cohorts, will be necessary before attempting to derive and replicate training and/or performance algorithms.
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spelling pubmed-53775572017-04-17 Letter to the editor: A genetic-based algorithm for personalized resistance training Karanikolou, A Wang, G Pitsiladis, Y Biol Sport Letter to the Editor In a recent paper entitled “A genetic-based algorithm for personalized resistance training”, Jones et al. [1] presented an algorithm of 15 performance-associated gene polymorphisms that they propose can determine an athlete’s training response by predicting power and endurance potential. However, from the design of their studies and the data provided, there is no evidence to support these authors’ assertions. Progress towards such a significant development in the field of sport and exercise genomics will require a paradigm shift in line with recent recommendations for international collaborations such as the Athlome Project (see www.athlomeconsortium.org). Large-scale initiatives, involving numerous multi-centre and well-phenotyped exercise training and elite performance cohorts, will be necessary before attempting to derive and replicate training and/or performance algorithms. Institute of Sport in Warsaw 2016-11-11 2017-03 /pmc/articles/PMC5377557/ /pubmed/28416894 http://dx.doi.org/10.5114/biolsport.2017.63385 Text en Copyright © Biology of Sport 2017 http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Letter to the Editor
Karanikolou, A
Wang, G
Pitsiladis, Y
Letter to the editor: A genetic-based algorithm for personalized resistance training
title Letter to the editor: A genetic-based algorithm for personalized resistance training
title_full Letter to the editor: A genetic-based algorithm for personalized resistance training
title_fullStr Letter to the editor: A genetic-based algorithm for personalized resistance training
title_full_unstemmed Letter to the editor: A genetic-based algorithm for personalized resistance training
title_short Letter to the editor: A genetic-based algorithm for personalized resistance training
title_sort letter to the editor: a genetic-based algorithm for personalized resistance training
topic Letter to the Editor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5377557/
https://www.ncbi.nlm.nih.gov/pubmed/28416894
http://dx.doi.org/10.5114/biolsport.2017.63385
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