Location: Children's Nutrition Research Center
2024 Annual Report
Objectives
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.
Progress Report
This project seeks to understand epigenetics, i.e. the fundamental molecular mechanisms that enable our different cell types (each of which contains the same DNA) to develop and stably maintain very different structures and functions. In particular, this project focuses on DNA methylation, which is the most stable epigenetic mark and likely relevant to our over-arching goal of understanding how nutrition before conception and during embryonic, fetal, and early postnatal development has persistent influences on the risk of disease throughout life (an area called ‘developmental programming’). Objective 1 focuses on mouse models of epigenetic development in the hypothalamus of the brain, to understand developmental programming of obesity. We used a classic model of developmental programming of energy balance (the postnatal small litter model), coupled with an innovative approach, to test the hypothesis that early postnatal overnutrition induces epigenetic changes within specific subclasses of neurons in the hypothalamus. We conducted the small litter experiments in transgenic mice in which one type of hypothalamic neuron (Agrp neurons) are fluorescently tagged. This allowed us to isolate specifically Agrp neurons from mice who were overnourished postnatally and compare to mice that were fed normally. Unfortunately, likely due to the very small quantities of DNA recovered, we have been unable to reliably perform library preparation for whole-genome bisulfite sequencing, so were unable to generate the profiling data on DNA methylation as intended.
Research under Objective 2 focuses on identifying human metastable epialleles and assessing their associations with obesity. (Metastable epialleles are regions of the genome that show random (i.e. not-genetically directed) epigenetic variation among individuals but not between different tissues of the same individual.) Rather than focus on identifying canonical metastable epialleles (at which individual variation in DNA methylation is largely independent of genetic variation), our studies have shown that systemic interindividual epigenetic variants in humans can have a stochastic (probabilistic) component, a genetic component, and moreover be influenced by periconceptional nutrition. Rather than limiting our focus to metastable epialleles, in 2019 we introduced a new term: Correlated Regions of Systemic Interindividual Variation in DNA methylation (CoRSIVs). This year, we made progress on Sub-objective 2C, performing target-capture bisulfite-seq at baseline on 100 weight stable and 100 ‘gainer’ adults from Starr County, Texas. We designed a panel of custom ‘baits’ to allow us to target and capture human genomic regions corresponding to the nearly 10,000 CoRSIVs we discovered. Last year, we performed target-capture on the 200 Starr County samples (100 weight stable and 100 'gainers'), and this year we have been analyzing these data. We detected unacceptably high levels of read duplication in our target-capture data. This means that the complexity of the 'libraries' we prepared from the captured DNA is low, indicating that the full panel of CoRSIVs was not well represented. We experienced delays due to manufacturing issues of a scientific instrument company. We are now evaluating a newly-synthesized capture panel following our version 2.0 design (which was the last version that worked according to expectations). Given these difficulties, we sought other manufacturers for items specifically tailored to custom-capture bisulfite sequencing. We have designed a CoRSIV-capture panel, and pilot experiments are underway to evaluate the performance of their panel and compare it with other manufacturers. We have performed a text-mining meta analysis of 2,700 published epigenome-wide association studies using the methylation platform (the current standard in the field) and found that probes overlapping CoRSIVs are hugely over-represented in the literature. This allowed us to estimate that, compared to studies using the platform, target-capture bisulfite sequencing of all known CoRSIVs will provide power advantages of ~100 to 600-fold, depending on the class of disease. These results represent major progress toward our goal of positioning CoRSIVs as the new standard for human methylome profiling for population association studies. Research under Objective 3 is focused on asking whether cancer-causing epigenetic modifications, particularly aberrant DNA methylation, can be influenced by dietary intake. Overall, we have achieved the primary goal of our project. We have successfully characterized a mouse model based on two common genetic and epigenetic events observed in human colorectal cancers: Apc mutation and p16 epimutation. This year, we conducted detailed histological analyses to compare the effects of dietary supplementation. We performed single-cell RNA sequencing to reveal previously uncharacterized tumor microenvironment. We have demonstrated a direct pathogenic role of p16 epimutation in colon cancer development and revealed how dietary folate enhances colon cancer risk in animal models. Our findings highlight the need for monitoring the long-term safety of folate fortification and resulting cancer-promoting effects.
In Objective 4, to address the demand for efficient access to large volumes of multi-omic data across labs, we created an integrative database framework. We developed a working version of the database, providing streamlined access to multi-omic nutritional data. It integrates various datasets to navigate and utilize the data and has significantly advanced the ability to conduct multi-omic analyses, facilitating more robust research outcomes. Our methodologies, findings, and the implications of our database will provide the scientific community with a guide to utilize its potential to transform nutritional research. Our work fosters greater collaboration and accelerates research by overcoming data barriers for researchers and offers a valuable resource for exploring critical biological questions and improving dietary recommendations, ultimately benefiting researchers, farmers, and consumers.
In Sub-objective 5A, we aim to decode the regulatory network of alternative splicing and epigenetic changes in disordered eating. We established analytical pipelines to infer splicing and epigenetic patterns. We aimed to identify the causal molecular changes in disordered eating. We realized that most publicly available datasets suffer from batch effects, where the signal is biased based on the research center or group generating the data. Such biases hinder the biological interpretability of the true signal. To address this, we developed a new splicing software capable of effectively handling batch effects and inferring splicing patterns and their respective molecular phenotypes. We then analyzed datasets related to disordered eating, focusing on alternative splicing and epigenetic changes. Results were summarized, providing new insights into the molecular mechanisms underlying disordered eating. This has advanced our understanding of the regulatory networks involved in disordered eating, and our software enhances the reliability of splicing analysis in the presence of batch effects. This supports a deeper and meaningful interpretation of complex biological data, benefiting ongoing and future research in disordered eating and subsequent metabolic disorders.
For Sub-objective 5B, we aim to decode the regularity interaction of alternative polyadenylation and epigenetic changes in disordered eating. We developed PolyAMiner-Bulk, an advanced computational tool that accurately infers alternative polyadenylation (APA) patterns from existing bulk RNA-seq datasets. By integrating these findings with epigenetic data (e.g., DNA methylation), we constructed APA-centric epigenetic regulatory networks. This allows us to identify causal differentially methylated regions and their impact on APA patterns in disordered eating conditions. Our results were summarized and visualized as APA centric epigenetic regulatory networks with causal differentially methylated regions and effected APA patterns. This will aid our understanding or decode novel regularity aspects in disordered eating and contribute to a deeper understanding of the molecular underpinnings of obesity-related disorders, paving the way for nutritional interventions.
In Objective 6, our focus is understanding the genetic and epigenetic basis of disordered eating using machine learning models. We collected a large amount of genetic, epigenetic, and transcriptomic data from public resources and from ongoing studies and this data underwent rigorous preprocessing to ensure quality and consistency. We applied advanced machine learning models, including deep learning algorithms, to this high-dimensional data. These models are designed to identify complex patterns in DNA methylation and gene expression. We focused on analyzing methylation profiles due to their significant role as epigenetic markers. By integrating our transcriptomic and epigenetic findings, we gained a complete view of the molecular changes associated with disordered eating, leading to a better understanding of the broader biological pathways and clinical outcomes. Throughout the project life, advancements were made towards the objectives. The creation and deployment of the multi-omic nutritional data portal have streamlined data access and integration, facilitating more comprehensive and robust analyses. Development of new tools and methods to infer alternative polyadenylation, alternative splicing patterns, and their regulatory relation whip with epigenetic factors has improved our ability to handle complex data and uncover critical insights into the molecular mechanisms of disordered eating and metabolic disorders. Our work provides a foundation for future research and personalized nutritional interventions.
Accomplishments
1. Dietary folate enhances colon cancer risk in animal models. There is an unresolved debate about the extent to which the environment contributes to cancer risk. Although epidemiological studies suggest that environmental factors such as diet can certainly contribute to this risk, especially for colon cancer, how dietary factors could tip the scale in favor of cancer is not known. Researchers at the Children's Nutrition Research Center in Houston, Texas, developed the first mouse model of engineered p16 promoter hypermethylation, leading to accelerated p16 epimutation in somatic tissues during aging. This work investigates the link between age-related p16 epimutation which is regulated by folate and intestinal tumorigenesis, identifying potential targets for colorectal cancer treatment. It also sheds light on the connection between diet and epigenetic regulation in cancer development. Importantly, these findings highlight the need to monitor the long-term safety of folate fortification in high-risk individuals.
2. Discovering novel splicing changes with new software. Novel splicing events in genes, called cryptic splicing events, are often missed by traditional tools but are crucial for understanding the biological phenomenon. To address this gap, specialized computational tools are necessary to accurately identify cryptic splicing. Researchers at the Children's Nutrition Research Center in Houston, Texas, developed a new software that finds these hidden changes and shows how diet affects them, offering new ways to manage metabolic diseases like diabetes. Researchers have used this tool to uncover genetic changes in heart failure and mental health disorders, leading to new diagnostic markers and treatments influenced by diet. This work broadens our understanding of gene regulation and its nutritional impacts, benefiting public health. By identifying diet-related splicing changes, the software opens avenues for personalized nutrition plans to prevent and treat metabolic conditions including obesity and diabetes.
3. The effect of cold on body fat and health. Brown fat helps keep us warm by burning energy, and cold temperatures make it more active. Researchers at the Children's Nutrition Research Center in Houston, Texas, studied the effect of temperature on body fat and health by housing mice at different temperatures, from comfortable to very cold and profiling their molecular changes. We saw a decrease in DNA methylation and increases in certain protein modifications, which together aid in regulating how brown fat genes turn on or off to produce heat in response to cold. This discovery suggests new ways to treat obesity and diabetes by understanding body heat and energy use and could lead to treatments that mimic cold effects on brown fat. This research impacts how we manage body fat and energy and highlights the potential for environmental and lifestyle changes to play a significant role in combating metabolic diseases.