Obesity prevention by different exercise protocols (HIIT or MICT) involves beige adipocyte recruitment and improved mitochondrial dynamics in high-fat-fed mice

Abstract

Aim: This study evaluated the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on UCP1-dependent and UCP1-independent thermogenic and mitochondrial dynamics markers in the inguinal sWAT of high-fat-fed mice.

Methods: Sixty male C57BL/6 mice (3 months old) were divided into six experimental groups: control diet (C), C + HIIT (C-HIIT), C + MICT (C-MICT), high-fat diet (HF), HF + HIIT (HF-HIIT) and HF + MICT (HF-MICT). The diet and exercise protocols started simultaneously and lasted ten weeks.

Results: HIIT and MICT prevented body mass gain and fat pad expansion, improved insulin sensitivity, and induced browning in C-fed and HF-fed animals. Chronic intake of a HF diet caused adipocyte hypertrophy with a proinflammatory adipokine profile and impaired the expression of thermogenic and mitochondrial dynamics markers. However, both exercise intensities increased anti-inflammatory adipokine concentrations and improved gene markers of mitochondrial dynamics, resulting in sustained UCP1-dependent and UCP1-independent thermogenic markers and maintenance of the beige phenotype in inguinal sWAT. The principal component analysis placed all trained groups opposite the HF group and near the C group, ensuring the effectiveness of HIIT and MICT to prevent metabolic alterations.

Conclusions: This study provides reliable evidence that, regardless of intensity, exercise is a strategy to prevent obesity by reducing body fat accumulation and inducing browning. The anti-inflammatory adipokine profile and the increased expression of UCP1-dependent and UCP1-independent thermogenic markers sustained active beige adipocytes and mitochondrial enhancement to halt metabolic disturbances due to HF-feeding in exercised mice.

Keywords: Beige adipocyte; Browning; Exercise; HIIT; High-fat diet; Mitochondrial dynamics; Principal component analysis.