Impact of Paternal Weight on the Cardiometabolic Profile of Offspring of Mothers with Gestational Diabetes Mellitus: A Transgenerational Study

• Grant number: 24/21946-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2025
• End date: February 28, 2026
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal Investigator: Bianca de Almeida Pititto
• Grantee: Marina Meirelles Paredes Muradian
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil

Abstract

Childhood obesity and its long-term consequences, such as an increased risk of cardiometabolic diseases, represent a significant public health challenge. This issue becomes even more relevant given the rising prevalence of obesity in both children and adults over the years. In this context, the mother's role in influencing a child's risk of developing obesity is widely recognized, with this influence being environmental, genetic, and epigenetic. However, the paternal influence remains underexplored, particularly in the Brazilian context. Evidence suggests that the father's nutritional status during the pre-conception period can affect the health of offspring through both genetic and epigenetic mechanisms.This study, part of the larger project titled "Association between early life events and glycemic profile and pancreatic reserve in children exposed to gestational diabetes mellitus," aims to evaluate the paternal contribution to the risk of obesity and cardiometabolic alterations in the offspring of mothers with gestational diabetes mellitus (GDM). The present research is a retrospective cohort study conducted as part of the larger project at the Diabetes and Pregnancy Outpatient Clinic of UNIFESP. A total of 222 gestation-offspring pairs, recruited between 2007 and 2021, were included, with data collected on the anthropometric, metabolic, and socioeconomic characteristics of mothers, fathers, and children. Variables such as body mass index (BMI), abdominal circumference, blood pressure, glycemia, and lipid profiles were analyzed. A comprehensive analysis of this database will then be performed.