4.7 Article

Skeletal Muscle Proteomic Profile Revealed Gender-Related Metabolic Responses in a Diet-Induced Obesity Animal Model

Journal

Publisher

MDPI
DOI: 10.3390/ijms22094680

Keywords

insulin resistance; obesity; proteomics; sarcopenia; skeletal muscle

Funding

  1. Italian Ministry of University and Research (MUR) [201742SBXA]
  2. AMANDA: Abnormal metabolic states, cellular stressors and neurodegenerative processes-Regione Lombardia
  3. National Research Council (CNR)
  4. Italian Ministry of University and Research (MUR), Department of Excellence project PREcision MedIcine Approach: bringing biomarker research to the clinic (PREMIA)

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The study revealed gender-specific responses to obesity in mice, with males showing various metabolic alterations while females exhibited activation of compensatory mechanisms. Bioinformatics analysis identified upstream molecules regulating pathways differently in males and females.
Obesity is a chronic, complex pathology associated with a risk of developing secondary pathologies, including cardiovascular diseases, cancer, type 2 diabetes (T2DM) and musculoskeletal disorders. Since skeletal muscle accounts for more than 70% of total glucose disposal, metabolic alterations are strictly associated with the onset of insulin resistance and T2DM. The present study relies on the proteomic analysis of gastrocnemius muscle from 15 male and 15 female C56BL/J mice fed for 14 weeks with standard, 45% or 60% high-fat diets (HFD) adopting a label-free LC-MS/MS approach followed by bioinformatic pathway analysis. Results indicate changes in males due to HFD, with increased muscular stiffness (Col1a1, Col1a2, Actb), fiber-type switch from slow/oxidative to fast/glycolytic (decreased Myh7, Myl2, Myl3 and increased Myh2, Mylpf, Mybpc2, Myl1), increased oxidative stress and mitochondrial dysfunction (decreased respiratory chain complex I and V and increased complex III subunits). At variance, females show few alterations and activation of compensatory mechanisms to counteract the increase of fatty acids. Bioinformatics analysis allows identifying upstream molecules involved in regulating pathways identified at variance in our analysis (Ppargc1a, Pparg, Cpt1b, Clpp, Tp53, Kdm5a, Hif1a). These findings underline the presence of a gender-specific response to be considered when approaching obesity and related comorbidities.

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