No reliable biomarkers exist to identify athletes in various training states including functional overreaching (FOR), non-functional overreaching (NFOR), and overtraining syndrome (OTS). Participants (N = 10, age 38.3 ± 3.4 years) served as their own controls and in random, counterbalanced order either ran/cycled 2.5 h (70.0 ± 3.7% VO2max) three days in a row (FOR) or sat in the lab (rest) (separated by three weeks; 7:00–9:30 am, overnight fasted state). Participants provided fingerprick samples for dried blood spot samples (DBS) pre- and post-exercise/rest, and then during two recovery days. DBS proteins were measured with nanoLC-MS in data-independent acquisition (DIA) mode, and 593 proteins were identified and quantified. Proteins were considered for the FOR cluster if they were elevated during one of the two recovery days but not more than one of the exercise days (compared to rest). The generalized estimating equation (GEE) was used to identify proteins linked to FOR. A total of 13 proteins was linked to FOR and most were associated with the acute phase response and innate immune system activation. This study used a system-wide proteomics approach to define a targeted panel of blood proteins related to FOR that could form the basis of future NFOR- and OTS-based studies.

Proteomics monitoring of an elite adventure athlete (age 33 years) was conducted over a 28-week period that culminated in the successful, solo, unassisted, and unsupported two month trek across the Antarctica (1500 km). Training distress was monitored weekly using a 19-item, validated training distress scale (TDS). Weekly dried blood spot (DBS) specimens were collected via fingerprick blood drops onto standard blood spot cards. DBS proteins were measured with nano-electrospray ionization liquid chromatography tandem mass spectrometry (nanoLC-MS/MS) in data-independent acquisition (DIA) mode, and 712 proteins were identified and quantified. The 28-week period was divided into time segments based on TDS scores, and a contrast analysis between weeks five and eight (low TDS) and between weeks 20 and 23 (high TDS, last month of Antarctica trek) showed that 31 proteins (n = 20 immune related) were upregulated and 35 (n = 17 immune related) were downregulated. Protein–protein interaction (PPI) networks supported a dichotomous immune response. Gene ontology (GO) biological process terms for the upregulated immune proteins showed an increase in regulation of the immune system process, especially inflammation, complement activation, and leukocyte mediated immunity. At the same time, GO terms for the downregulated immune-related proteins indicated a decrease in several aspects of the overall immune system process including neutrophil degranulation and the antimicrobial humoral response. These proteomics data support a dysfunctional immune response in an elite adventure athlete during a sustained period of mental and physical distress while trekking solo across the Antarctica.

In a previous study, proteomics procedures identified blood proteins as potential overreaching and overtraining biomarkers, and a targeted proteomics panel of 21 proteins was developed.PurposeTo measure targeted blood protein changes in an ultraendurance cyclist competing in RAAM.MethodsThe athlete underwent testing 4-week pre-RAAM and 4-day post-RAAM to determine body composition and aerobic capacity. During RAAM training distress score (TDS) and body mass were measured daily. Power output and heart rate (HR) were measured during cycling. Blood sampling for proteomic analysis occurred 4 weeks, 24, and 2 h before the start, twice per day of the race, and after 1 and 4 days recovery.ResultsThe athlete completed the 4941 km race in 10.1 days at a speed of 24.5 km/h with 20 total hours of sleep. TDS was very low, 1, pre-RAAM and increased to very high, 47, at the finish. Post-RAAM maximal aerobic capacity and HR were 6.3 and 5.7% lower (61.6 vs. 57.5 mL.kg–1.min–1 and 192 bpm vs. 181 bpm). Body composition did not change. The change in blood proteins was calculated using pre-race samples and samples collected on days 8, 9, and recovery day 1. The blood proteins with the largest increase were complement component C7 (359%), complement C4-B (231%), serum amyloid A-4 protein (210%), inter-alpha-trypsin inhibitor heavy chain H4 (191%), and alpha-1-antitrypsin (188%).ConclusionThe RAAM athlete exhibited non-functional overreaching symptoms including increased training distress and decreased work capacity. Proteomic analysis indicated large increases for immune-related proteins involved with complement activation and the acute phase response, which could be useful biomarkers for non-functional overreaching.

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.

Abstract:No reliable biomarkers exist to identify athletes in various training states including functional overreaching (FOR), non-functional overreaching (NFOR), and overtraining syndrome (OTS). Participants (N = 10, age 38.3 ± 3.4 years) served as their own controls and in random, counterbalanced order either ran/cycled 2.5 h (70.0 ± 3.7% VO 2max ) three days in a row (FOR) or sat in the lab (rest) (separated by three weeks; 7:00-9:30 am, overnight fasted state). Participants provided fingerprick samples for dried blood spot samples (DBS) pre-and post-exercise/rest, and then during two recovery days. DBS proteins were measured with nanoLC-MS in data-independent acquisition (DIA) mode, and 593 proteins were identified and quantified. Proteins were considered for the FOR cluster if they were elevated during one of the two recovery days but not more than one of the exercise days (compared to rest). The generalized estimating equation (GEE) was used to identify proteins linked to FOR. A total of 13 proteins was linked to FOR and most were associated with the acute phase response and innate immune system activation. This study used a system-wide proteomics approach to define a targeted panel of blood proteins related to FOR that could form the basis of future NFOR-and OTS-based studies.