Location: Children's Nutrition Research Center
Project Number: 3092-10700-070-030-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Apr 1, 2019
End Date: Mar 31, 2024
Objective:
Objective 1: Use transgenic mouse models, microdissection, nuclear sorting, next-generation sequencing and innovative computational approaches to alter DNA methylation in specific subpopulations of hypothalamic neurons and evaluate lifelong effects on energy metabolism, food intake, and physical activity; isolate specific neuronal (and potentially non-neuronal) hypothalamic cell types to evaluate cell type-specific alterations in DNA methylation in established models of nutritional programming.
Objective 2: Advance understanding of the causes of interindividual epigenetic variation and consequences for human energy balance by conducting target-capture bisulfite sequencing in multiple tissues from an existing cohort of molecularly-phenotyped individuals to determine associations between genetic variation, epigenetic variation, and gene expression at human metastable epialleles; identify human metastable epialleles that predict risk of obesity by exploiting existing longitudinal cohorts of metabolically-phenotyped individuals; assess how DNA methylation at obesity-associated metastable epialleles is affected by maternal periconceptional nutrition.
Objective 3: Determine the functional impact of folic acid supplementation and establish the functional role of age-related p16 epimutation in genetically and epigenetically engineered mouse models of colon cancer and in intestinal carcinogenesis.
New Project (HY):
Objective 1. Create multi-omic nutritional data share portal to resolve the unmet demand for an efficient access to the large volumes of heterogeneous multi-omic data across various research labs and centers.
Objective 2. Integrate heterogeneous multi-omic datasets such as genetic (SNPs), transcriptomic, epigenetic, proteomic, metabolomic and microbiome to infer molecular network structures illustrating eating disorder dynamics.
Objective 3. Decode genetic and epigenetic patterns of disordered eating using machine learning methods.
Approach:
Developmental programming occurs when nutrition and other environmental exposures affect prenatal or early postnatal development, causing structural or functional changes that persist to influence health throughout life. Researchers are working to understand epigenetic mechanisms of developmental programming. Epigenetic mechanisms regulate cell-type specific gene expression, are established during development, and persist for life. Importantly, nutrition during prenatal and early postnatal development can induce epigenetic changes that persist to adulthood. We focus on DNA methylation because this is the most stable epigenetic mechanism. The inherent cell-type specificity of epigenetic regulation motivates development of techniques to isolate and study specific cell types of relevance to obesity and digestive diseases. These projects integrate both detailed studies of animal models and characterization of epigenetic mechanisms in humans. We will use mouse models of developmental epigenetics in the hypothalamus to understand cell type-specific epigenetic mechanisms mediating developmental programming of body weight regulation. Mouse models will also be used to investigate how folic acid intake affects epigenetic mechanisms regulating intestinal epithelial stem cell (IESC) development and characterize the involvement of these mechanisms in metabolic programming related to obesity, inflammation, and gastrointestinal cancer. In human studies, we will identify human genomic loci at which interindividual variation in DNA methylation is both sensitive to maternal nutrition in early pregnancy and associated with risk of later weight gain. An improved understanding of how nutrition affects developmental epigenetics should eventually lead to the creation of early-life nutritional interventions to improve human health. And scientists will elucidate the molecular interplay of epigenome and transcriptome in aberrant eating behaviors using robust genome-wide computational analyses. They will conduct a multi-omic integrative study to systematically decipher the regulatory aspects of DNA methylation and histone modifications on alternative splicing and alternative polyadenylation in disordered eating. Novel machine learning approaches will be designed to address specific analytical challenges.
