Abstract
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.
Highlights
Within recent years, there has been an increased interest in the ability to provide personalised—or at least more personalised—information to athletes, their coaches and support staff in order to enhance the athletic preparation process [1,2,3,4]
Perhaps the most promising are miRNAs, which have the potential to serve as markers of responsiveness to a training programme prior to that programme being undertaken [88], allowing for the coach to match the athlete to the required exercise type. miRNAs hold potential value as a real-time marker of exercise adaptation [94], allowing for a change of stimulus to be applied at the most optimal time point, and as a marker of fatigue status [77], allowing for daily changes in training load and volume
Alongside an understanding of the microbiome, genome and epigenome, along with the utility of other markers such as Cell-Free DNA (cfDNA) to act as novel markers of exercise adaptation and readiness, there are a variety of other “omes”, including the transcriptome, proteome and metabalome, which may enhance the personalised medicine approach to elite athlete preparation
Summary
There has been an increased interest in the ability to provide personalised—or at least more personalised—information to athletes, their coaches and support staff in order to enhance the athletic preparation process [1,2,3,4] The sources of this information are potentially varied, but include genetic [1,2], epigenetic [1,2], workload-based [5] and wellness-based [6] information. This review aims to explore novel methods which, when used alongside existing technologies, will hopefully help coaches gain answers to the above questions These methods should assist in the decision-making process, allowing for the targeted use of emerging technology to guide such decisions and contributing to an enhanced understanding of the way in which each individual responds to—both in terms of adaptation and fatigue—exercise training. We examine the practical implementation of these technologies, some of which are highly invasive and potentially expensive, allowing interested practitioners to analyse the cost: benefit ratio of each technology
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