Analysis of genetic parameters related to inflammation in metabolically healthy women with obesity VS women with metabolically unhealthy obesity: a cross-sectional study

• Grant number: 24/13009-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: January 01, 2025
• End date: December 31, 2025
• Field of knowledge: Health Sciences - Nutrition
• Principal Investigator: Ellen Cristini de Freitas
• Grantee: Gabriela Geraldo Benzoni
• Host Institution: Escola de Educação Física e Esporte de Ribeirão Preto (EEFERP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Obesity is defined as the excessive accumulation of adipose tissue in different parts of the body, stored predominantly in subcutaneous or visceral tissue. It is known that adipocyte hypertrophy or hyperplasia can influence the development of Metabolic Syndrome (MetS) due to chronic inflammation resulting from the increase in adipocyte volume and consequent reduction in tissue vascularization, leading to an increase in pro-inflammatory cytokines throughout the organism. There are people who develop the so-called Metabolically Healthy Obesity (WHO), in which excess adipose tissue does not lead to the development of MetS, they usually have greater tissue hyperplasia and a lower degree of inflammation. The objective of the present study is to evaluate the differences in pro-inflammatory cytokine genes (TNF-± and NF-kB) involved in the pathogenesis of MetS in two groups of women: with WHO and with Metabolically Unhealthy Obesity (MUO). 32 participants with age between 18 and 40 and a Body Mass Index (BMI) above 30kg/m² will be included. The data collection will be performed in a single session, including: blood samples for genetic and biochemical analysis, anthropometric assessments and body composition, physical tests and analysis of food intake. The data will be evaluated using the Student's t test or the Mann-Whiteney test for paired samples depending on the normality of the data, which will be tested using the Shapiro-Wilk test. To evaluate the correlation between variables, the Pearson correlation test will be used for parametric data and the Spearman correlation test for non-parametric data, the significance level adopted will be p<0.05 and all analyzes will be carried out using the SPSS 20.0 software.