Analysis of Biomarkers in Response to High Intensity Functional Training (HIFT) and High Intensity Interval Training (HIIT): A Systematic Review Study

Aerobic training with an acyclic and intermittent character triggers high metabolic stress, responsible for generating alterations in several blood biomarkers. Thus, investigations that clarify understanding of metabolic behavior in response to exercise seem pertinent, when considering the dynamics of prescription of physical training and recovery. Objective: Demonstrate and discuss the behavior of blood biomarkers in response to High Intensity Interval Training (HIIT) and High Intensity Functional Training (HIFT). Methods: The PubMed/MEDLINE, Scielo, Lilacs, Bireme, Google Scholar, and Scopus databases were searched from the oldest records available until January 16, 2020. The search was carried out by combining descriptors related to the terms: “HIIT”, “HIFT”, and “blood biomarkers”. To be included, studies were required to: 1) have a clinical trial design; 2) evaluate the effects of an HIIT and/or HIFT protocol; and 3) measure blood biomarkers before and after the training protocol. No restrictions were applied to the characteristics of the participants regarding health condition, age, sex, and level of training. Results: In total, seven studies were included (n=221 participants, aged between 18 and 63 years) that analyzed different population profiles such as athletes, sedentary young people, patients with breast cancer, and diabetics. The biomarkers evaluated included analysis of muscle damage (C Reactive protein and CK); oxidative stress (antioxidant capacity); kidney injury (creatinine and urea); hormones (testosterone and cortisol); cytokines (TNF-α, IL-6, IL-1β, IL-10, IL-4, and IF-γ); and hemogram. In general, the results demonstrated specific patterns for the investigated markers. Thus, there were increases in muscle damage markers, while in the inflammatory markers, there was a reduction in pro-inflammatory cytokines and an increase in anti-inflammatory cytokines. Despite the reduced values of the general blood count, markers such as neutrophils and basophils did not demonstrate statistically significant alterations. Serum testosterone levels were higher and cortisol was lower in the post-exercise period when compared to pre-exercise. Conclusion: These data are of practical relevance when demonstrating patterns of physiological responses, which also characterize knowledge and understanding essential to determine adequate periodization.