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Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season

PURPOSE: To evaluate relationships of proteomics data, athlete-reported illness, athlete training distress (TDS), and coaches’ ratings of distress and performance over the course of the competitive season. METHODS: Thirty-five NCAA Division II swimmers were recruited to the study (male n = 19, femal...

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Autores principales: Knab, Amy M., Nieman, David C., Zingaretti, Laura M., Groen, Arnoud J., Pugachev, Artyom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261863/
https://www.ncbi.nlm.nih.gov/pubmed/32523539
http://dx.doi.org/10.3389/fphys.2020.00373
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author Knab, Amy M.
Nieman, David C.
Zingaretti, Laura M.
Groen, Arnoud J.
Pugachev, Artyom
author_facet Knab, Amy M.
Nieman, David C.
Zingaretti, Laura M.
Groen, Arnoud J.
Pugachev, Artyom
author_sort Knab, Amy M.
collection PubMed
description PURPOSE: To evaluate relationships of proteomics data, athlete-reported illness, athlete training distress (TDS), and coaches’ ratings of distress and performance over the course of the competitive season. METHODS: Thirty-five NCAA Division II swimmers were recruited to the study (male n = 19, female n = 16; age 19.1 ± 1.6 years). Athletes provided fingerprick dried blood spot (DBS) samples, illness symptoms, and TDS every Monday for 19 of 25 weeks in their season. Coaches monitored performance and rated visual signs of distress. DBS samples were analyzed for a targeted panel of 12 immune-related proteins using liquid chromatography/mass spectrometry (LC/MS). RESULTS: Thirty-two swimmers completed the protocol. The data were grouped in 2–3 weeks segments to facilitate interpretation and analysis of the data. TDS scores varied between athletes, and were highest during the early fall conditioning ramp up period (8.9 ± 1.6 at baseline to a peak of 22.6 ± 2.0). The percent of athletes reporting illness was high throughout the season (50–78%). Analysis of TDS using Principle Component Analysis (PCA) revealed that 40.5% of the variance (PC1) could be attributed to illness prevalence, and TDS scores for the athletes reporting illness and no illness were different across the season (P < 0.001). The coaches’ ratings of swim performance and swimmer’s distress, sex, and racing distance (sprinters, middle distance, long distance) were not correlated with PC1. Linear Discriminant Analysis (LDA) analysis of the data showed a separation of the baseline weeks from exam weeks with or without competitions, and with competitions alone (p < 0.001). Seven of the 12 proteins monitored over the course of training were upregulated, and the addition of the protein data to LDA analysis enhanced the separation between these groups of weeks. CONCLUSION: TDS and illness were related in this group of 32 collegiate swimmers throughout the competitive season, and expression of immune proteins improved the statistical separation of baseline weeks from the most stressful weeks. TDS data provided by the swimmers did not match their coaches’ ratings of distress and swim performance. The importance of the immune system in the reaction to internal and external stress in athletes should be an area of further research.
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spelling pubmed-72618632020-06-09 Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season Knab, Amy M. Nieman, David C. Zingaretti, Laura M. Groen, Arnoud J. Pugachev, Artyom Front Physiol Physiology PURPOSE: To evaluate relationships of proteomics data, athlete-reported illness, athlete training distress (TDS), and coaches’ ratings of distress and performance over the course of the competitive season. METHODS: Thirty-five NCAA Division II swimmers were recruited to the study (male n = 19, female n = 16; age 19.1 ± 1.6 years). Athletes provided fingerprick dried blood spot (DBS) samples, illness symptoms, and TDS every Monday for 19 of 25 weeks in their season. Coaches monitored performance and rated visual signs of distress. DBS samples were analyzed for a targeted panel of 12 immune-related proteins using liquid chromatography/mass spectrometry (LC/MS). RESULTS: Thirty-two swimmers completed the protocol. The data were grouped in 2–3 weeks segments to facilitate interpretation and analysis of the data. TDS scores varied between athletes, and were highest during the early fall conditioning ramp up period (8.9 ± 1.6 at baseline to a peak of 22.6 ± 2.0). The percent of athletes reporting illness was high throughout the season (50–78%). Analysis of TDS using Principle Component Analysis (PCA) revealed that 40.5% of the variance (PC1) could be attributed to illness prevalence, and TDS scores for the athletes reporting illness and no illness were different across the season (P < 0.001). The coaches’ ratings of swim performance and swimmer’s distress, sex, and racing distance (sprinters, middle distance, long distance) were not correlated with PC1. Linear Discriminant Analysis (LDA) analysis of the data showed a separation of the baseline weeks from exam weeks with or without competitions, and with competitions alone (p < 0.001). Seven of the 12 proteins monitored over the course of training were upregulated, and the addition of the protein data to LDA analysis enhanced the separation between these groups of weeks. CONCLUSION: TDS and illness were related in this group of 32 collegiate swimmers throughout the competitive season, and expression of immune proteins improved the statistical separation of baseline weeks from the most stressful weeks. TDS data provided by the swimmers did not match their coaches’ ratings of distress and swim performance. The importance of the immune system in the reaction to internal and external stress in athletes should be an area of further research. Frontiers Media S.A. 2020-05-25 /pmc/articles/PMC7261863/ /pubmed/32523539 http://dx.doi.org/10.3389/fphys.2020.00373 Text en Copyright © 2020 Knab, Nieman, Zingaretti, Groen and Pugachev. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Knab, Amy M.
Nieman, David C.
Zingaretti, Laura M.
Groen, Arnoud J.
Pugachev, Artyom
Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season
title Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season
title_full Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season
title_fullStr Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season
title_full_unstemmed Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season
title_short Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season
title_sort proteomic profiling and monitoring of training distress and illness in university swimmers during a 25-week competitive season
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261863/
https://www.ncbi.nlm.nih.gov/pubmed/32523539
http://dx.doi.org/10.3389/fphys.2020.00373
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