Athletes training at higher than typical intensities without appropriate preparation and utilising inadequate recovery periods may become overtrained. This debilitating condition is characterised by persistent fatigue and an inability to maintain high-performance athletic outputs. Metabolites, lipid mediators and proteins harvested from body fluids are physiological indicators of the state of tissues, organs and general health of the individual analysed. These biomarkers could be used to monitor the state of stress and recovery from exercise when high intensity training has caused exercise-induced fatigue, stress or injury.
This discovery project will utilize quantitative protein profiling to search for novel low abundant proteins in samples sourced from a study of highly trained athletes, pre- and post-high-intensity exercise [1]. These same samples will also be analysed for metabolites and lipid mediators to develop an in-depth view of athlete health status after being excessively trained without a recovery period. The resulting –omics based data will be integrated and analysed through a data analysis pipeline to generate a more informative view of the underlying physiology. Results generated will be compared to a control cohort that was normally trained under the same conditions.
A differential abundance of biological markers may be detectable between excessively trained and normally trained athlete cohorts. This changed biomolecule profile will be indicative of a altered physiological state based upon effected biological pathways post-overtraining and better elucidate the mechanisms that underpin the processes of post-exercise muscle fatigue.
In addition, the identification of biomarkers indicating the onset of overtraining syndrome will allow for improved monitoring of athletic training, and determine key points of intervention to prevent long-term and career threatening performance decrements.
[1] Le Meur, Y., et al, "A multidisciplinary approach to overreaching detection in endurance trained athletes," Journal of Applied Physiology (2013). 114(3): 411-420.