DNA metilation profile of mother-concept binomy in the context of Maternal Obesity and fetal and neonatal adiposity

Abstract

Obesity is a worldwide public health problem. It is known that the intrauterine environment can program the fetus to develop Obesity later in life. A recognized epigenetic mechanism by which the adverse effects of the intrauterine environment are transferred to the offspring is DNA methylation. However, the relationship between intrauterine exposures and changes in epigenetics, especially regarding fetal and newborn adiposity, is not clear in the literature. Objective: to evaluate the relationship between Maternal Obesity and maternal DNA methylation profile of the maternal and cord blood, and placenta tissues with fetal and neonatal adiposity. Methodology: a population of 12 pregnant women with previous Obesity, 12 with eutrophy and 12 eutrophic pregnant women with excess weight gain during pregnancy, according to recommendation of the Institute of Medicine (2009) and their respective concepts will be involved in this study. The population was selected from the cohort entitled "Relation between Obesity maternal and adiposity of the concept in the fetal, neonatal and first year of life: prospective population-based study". Maternal blood samples will be collected from the women in the third trimester of pregnancy and umbilical cord blood will be collected for analysis of the methylation by ARRAY with the Infinium MethylationEPIC BeadChip850 (HM850) (Illumina, CA, USA). Candidate genes will be selected for the validation of hypo- and hypermethylated regions by quantitative PCR (qPCR) in maternal and cord blood and placenta tissues (decidua and villus). Fetal adiposity will be measured in the second and third trimesters by ultrasonography using the Philips HD11XE ultrasound scanner (Philips, USA) and neonatal adiposity will be measured 12-72h after delivery by plethysmography with PEOD POD (Cosmed®, USA). Maternal nutrition will be evaluated by two 24-hour recall by the Software Nutrition Data System for Research (NDSR, Minnesota, USA). For statistics we will use the unpaired T-tests and two-way ANOVA. Multiple linear regression models will be used to study associations between the variables of interest controlling by confounding factors. Linear models of repeated measures will be used to detect differences in baseline and follow-up data. The significance level will be a pd 0.05. (AU)