|Support type:||Scholarships in Brazil - Post-Doctorate|
|Effective date (Start):||April 01, 2019|
|Effective date (End):||March 31, 2021|
|Field of knowledge:||Health Sciences - Nutrition - Nutritional Analysis of Population|
|Principal Investigator:||Sandra Roberta Gouvea Ferreira Vivolo|
|Grantee:||Renata Germano Borges de Oliveira Nascimento Freitas|
|Home Institution:||Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil|
There is evidence that gestational and early post-natal conditions like lactation can induces metabolic programming that would predispose to chronic diseases later in life. Among those, obesity, diabetes and hypertension have been associated with birth weight, type of delivery and lactation. The latter events have impacted on the composition of gut microbiota, a mediator of systemic metabolic effects, which may predispose to those diseases. It is questionable whether gestational exposures and early-life events could influence further energy expenditure. Studies in this field are rare but necessary to deep knowledge on the pathways and biomarkers involved. Our hypothesis is that pre- and post-natal conditions could induce programming toward effects on energy metabolism, expressed in adult life by distinct metabolic phenotypes. This project aims to examine whether the gut microbiota composition and metabolic profile of young women intestinal, participants of the NutriHS, varies according to conditions during gestation and lactation. This is a cross-sectional analysis of a convenience sample of 120 women (18-45 years), distributed into 2 groups, normal and weight excess (Body mass index e 25 kg/m²), subdivided by the presence of disturbed cardiometabolic profile. Assessments will be: exposures during gestational period, lactation type, current lifestyle, DXA-measured body composition, indirect calorimetry-measured metabolic flexibility, biomarkers of energy balance (visfatin, myostatin and obestatin), gut microbiota and cardiometabolic profile. Indirect calorimetry will be combined to a standardized meal test in which glucose, insulin and short chain fatty acids will be determined. DAG will be employed to define covariables to be included in multiple regression models to test associations with metabolic outcomes.