Influence of immune and nutritional biomarkers on illness risk during interval training
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Influence of immune and nutritional biomarkers on illness risk during interval training. / Hanstock, Helen G; Govus, Andrew D; Stenqvist, Thomas B; Melin, Anna Katarina; Sylta, Øystein; Torstveit, Monica Klungland.
In: International Journal of Sports Physiology and Performance, Vol. 15, No. 1, 2020, p. 60-67.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Influence of immune and nutritional biomarkers on illness risk during interval training
AU - Hanstock, Helen G
AU - Govus, Andrew D
AU - Stenqvist, Thomas B
AU - Melin, Anna Katarina
AU - Sylta, Øystein
AU - Torstveit, Monica Klungland
N1 - CURIS 2020 NEXS 017
PY - 2020
Y1 - 2020
N2 - Purpose: This study explored whether three different HIT prescriptions influence multiple health-related biomarkers and whether biomarker responses to HIT were associated with upper respiratory illness (URI) risk.Methods: Twenty-five male cyclists and triathletes were randomised to three HIT groups and completed twelve HIT sessions over four weeks. Peak oxygen consumption (V̇O2peak) was determined using an incremental cycling protocol, while resting serum biomarkers (cortisol, testosterone, 25[OH]D and ferritin), salivary immunoglobulin-A (s-IgA) and energy availability (EA) were assessed before and after the training intervention. Participants self-reported upper respiratory symptoms during the intervention and episodes of URI were identified retrospectively.Results: Fourteen athletes reported URIs, but there were no differences in incidence, duration or severity between groups. Increased risk of URI was associated with higher s-IgA secretion rates (odds ratio=0.90, 90% CI:0.83-0.97). Lower pre-intervention cortisol and higher EA predicted a 4% increase in URI duration. Participants with higher V̇O2peak reported higher total symptom scores (incidence rate ratio=1.07, 90% CI:1.01-1.13).Conclusions: Although multiple biomarkers were weakly associated with risk of URI, the direction of associations between s-IgA, cortisol, EA and URI risk were inverse to previous observations and physiological rationale. There was a cluster of URIs within the first week of the training intervention, but no samples were collected at this time-point. Future studies should incorporate more frequent sample time-points, especially around the onset of new training regimes, and include athletes with suspected or known nutritional deficiencies.
AB - Purpose: This study explored whether three different HIT prescriptions influence multiple health-related biomarkers and whether biomarker responses to HIT were associated with upper respiratory illness (URI) risk.Methods: Twenty-five male cyclists and triathletes were randomised to three HIT groups and completed twelve HIT sessions over four weeks. Peak oxygen consumption (V̇O2peak) was determined using an incremental cycling protocol, while resting serum biomarkers (cortisol, testosterone, 25[OH]D and ferritin), salivary immunoglobulin-A (s-IgA) and energy availability (EA) were assessed before and after the training intervention. Participants self-reported upper respiratory symptoms during the intervention and episodes of URI were identified retrospectively.Results: Fourteen athletes reported URIs, but there were no differences in incidence, duration or severity between groups. Increased risk of URI was associated with higher s-IgA secretion rates (odds ratio=0.90, 90% CI:0.83-0.97). Lower pre-intervention cortisol and higher EA predicted a 4% increase in URI duration. Participants with higher V̇O2peak reported higher total symptom scores (incidence rate ratio=1.07, 90% CI:1.01-1.13).Conclusions: Although multiple biomarkers were weakly associated with risk of URI, the direction of associations between s-IgA, cortisol, EA and URI risk were inverse to previous observations and physiological rationale. There was a cluster of URIs within the first week of the training intervention, but no samples were collected at this time-point. Future studies should incorporate more frequent sample time-points, especially around the onset of new training regimes, and include athletes with suspected or known nutritional deficiencies.
KW - Faculty of Science
KW - Endurance athletes
KW - HIT
KW - Immunity
KW - Training load
KW - URT1
U2 - 10.1123/ijspp.2018-0527
DO - 10.1123/ijspp.2018-0527
M3 - Journal article
C2 - 31034260
VL - 15
SP - 60
EP - 67
JO - International Journal of Sports Physiology and Performance
JF - International Journal of Sports Physiology and Performance
SN - 1555-0265
IS - 1
ER -
ID: 217552178