Related Experiment Video
Updated: Jan 25, 2026

A Real-World High-Intensity Interval Training Protocol for Cardiorespiratory Fitness Improvement
Published on: February 22, 2022
Influence of Immune and Nutritional Biomarkers on Illness Risk During Interval Training
Abstract:
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 (V˙O2peak) 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 V˙O2peak 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.
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