Effects of obesity, metabolic parameters and genetic variants on the acceleration of biological age in patients with Systemic Lupus Erythematosus.

• Grant number: 24/15583-6
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: May 01, 2025
• End date: June 30, 2026
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal Investigator: Carolina Nicoletti Ferreira Fino
• Grantee: Amanda Alves Ribeiro
• Host Institution: Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Introduction: Systemic lupus erythematosus (SLE) is a complex condition associated with immunedysregulation, with pathophysiology resulting from the interaction between genetic, epigenetic, andenvironmental factors, including diet. Obesity emerges as a significant contributor to the exacerbation of symptoms and pathogenesis in SLE, contributing to a chronic inflammatory state. This increased adiposity not only worsens inflammation associated with lupus but also accelerates the epigenetic clock by altering epigenetic marks and speeding up cellular aging. Objective: This study aims to investigatewhether obesity associated with SLE promotes accelerated biological aging measured by epigenetic clock models and whether metabolic, inflammatory parameters and genetic variants are related to this process. Materials and Methods: 100 selected patients will be divided into two groups based on nutritional status classified by body mass index (BMI): 1. The EUT group will consist of SLE patients with normal weight (BMI between 18.5 and 24.9 kg/m²), and 2. The EP group will consist of SLE patients with excess weight (BMI > 25 kg/m²). Adipose tissue and blood samples will be collected for DNA methylation analysis, biological age estimation, and biochemical assessments including metabolic and inflammatory parameters, as well as genetic variant analyses. All participants will be genotyped for polymorphisms in the SIRT1 (rs12778366 and rs7895833) and FOXO3 (rs2802292 and rs10457180)genes using real-time PCR. Genotypic frequencies will be calculated using additive and allelicinheritance models. DNA methylation analysis will be performed using the Infinium MethylationBeadChip assay. Biological age will be estimated using epigenetic clocks based on aging biomarkers:DNAm Hannum, Horvath, PhenoAge, and Grim Age.Keywords: Epigenetic clock. DNA methylation. Adipose tissue. Systemic lupus erythematous. Obesity.Polymorphism.