Influence of immune and nutritional biomarkers on illness risk during interval training

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 2019 NEXS 370

PY - 2020

Y1 - 2020

N2 - Intensive training periods may negatively influence immune function, but the immunological consequences of specific high-intensity-training (HIT) prescriptions are not well defined. Purpose: To explore whether 3 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 randomized to 3 HIT groups and completed 12 HIT sessions over 4 wk. Peak oxygen consumption (VO ․ 2peak) 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% confidence interval 0.83–0.97). Lower preintervention cortisol and higher EA predicted a 4% increase in URI duration. Participants with higher VO ․ 2peak reported higher total symptom scores (incidence rate ratio = 1.07, 90% confidence interval 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 in 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 regimens, and include athletes with suspected or known nutritional deficiencies.

AB - Intensive training periods may negatively influence immune function, but the immunological consequences of specific high-intensity-training (HIT) prescriptions are not well defined. Purpose: To explore whether 3 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 randomized to 3 HIT groups and completed 12 HIT sessions over 4 wk. Peak oxygen consumption (VO ․ 2peak) 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% confidence interval 0.83–0.97). Lower preintervention cortisol and higher EA predicted a 4% increase in URI duration. Participants with higher VO ․ 2peak reported higher total symptom scores (incidence rate ratio = 1.07, 90% confidence interval 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 in 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 regimens, 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

SN - 1555-0265

JO - International Journal of Sports Physiology and Performance

JF - International Journal of Sports Physiology and Performance

ER -