Characterizing metabolic variability during pregnancy to understand pathways of in-utero overnutrition: an integrative analysis of metabolomics and lifestyle data

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PROJECT SUMMARY/ABSTRACT Maternal-fetal resource allocation is governed by complex maternal physiological adaptations; however, conditions such as obesity and Gestational Diabetes Mellitus (GDM) are associated with a suboptimal adaptive response to pregnancy resulting in under- or overnutrition in utero. In utero overnutrition (i.e., fetal over- nourishment by excess exposure to maternal fuels) is a concern given the earlier onset of obesity and cardiometabolic disease in youth. Moreover, higher glycemia and adiposity, even below thresholds of clinical GDM and obesity, have detrimental effects on offspring health. Such metabolic heterogeneity is noteworthy as it influences target tissues involved in fetal development, such as the placenta. Characterizing metabolic variability in pregnant women and assessing associations with offspring metabolic health will reveal nuances in maternal phenotypes that contribute to metabolic disease risk in offspring. However, the associations of maternal metabolic heterogeneity with maternal fuels (e.g., glucose, insulin, lipids) and modifiable behaviors are unclear. Moreover, it is unknown if placental signaling, which is implicated in fetal programming, reflects metabolic heterogeneity assessed via circulating biomarkers during pregnancy. Dr. Ellen Francis’ proposal addresses these knowledge gaps by integrating low- and high-dimensional observational data and applying advanced statistical techniques to test the hypothesis that distinct maternal metabolic subgroups correspond to differences in placental signaling pathways, and that the maternal subgroups and placental pathways are involved in programming of offspring metabolic risk. This proposal will use existing samples of fasting maternal blood during pregnancy (N=1410), placental villus tissue, and collect new metabolomics in offspring at 4-8 years of age. Through didactic instruction and mentored training, Dr. Francis will obtain training in the analysis of ‘omics data within a lifecourse epidemiological framework to characterize metabolic variability in pregnancy and generate metabolic subgroups related to adiposity and maternal fuels. She will advance her understanding of placental and developmental biology (fetal programing) by receiving extensive hands-on-training (inclusion in lab and bench training, and conference and seminar attendance) from mentors with expertise in placental and perinatal biology. In the independent phase, she will use training gained in the mentored phase to assess if maternal metabolic subgroups are reflected in placental nutrient sensing pathways, generate metabolomics data in offspring and create offspring metabolic profiles. She will then assess whether maternal metabolic subgroups are associated with offspring metabolic profiles in childhood, and the extent to which these associations are mediated by placental nutrient sensing pathways. Findings from these complementary studies will improve our understanding of metabolic pathways involved in fetal development, contribute to knowledge of how maternal metabolic variability influences metabolic risk in offspring, and could reveal key cellular and behavioral targets for prevention strategies, while assisting Dr. Francis’ to establish a career as an independent investigator.