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Integrating Computational and Experimental Models to Predict Toxicity of the Pancreas

整合计算和实验模型来预测胰腺的毒性

基本信息

批准号：
10576042
负责人：
Uduak Zenas George
金额：
$ 18.24万
依托单位：
SAN DIEGO STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-02-15 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10576042
关键词：
Biological Chemical Structure Chemicals Childhood diabetes Complex Computer Analysis Computer Models Cross-Sectional Studies Data Set Development Diabetes Mellitus Diet Disease Embryo Environmental Pollutants Environmental Science Etiology Experimental Models Exposure to Gene Expression Gene Targeting Goals Habits Health Heterogeneity Impairment Incidence Individual Insulin-Dependent Diabetes Mellitus Life Cycle Stages Life Style Mathematics Metabolic Diseases Methodology Methods Modeling Molecular Morphology Non-Insulin-Dependent Diabetes Mellitus Organ Organogenesis Outcome PPAR alpha Pancreas Pathogenesis Pathologic Pathway interactions Peroxisome Proliferator-Activated Receptors Prevalence Process Quantitative Structure-Activity Relationship Receptor Signaling Research Resolution SEARCH for Diabetes in Youth Science Signal Transduction Structure Techniques Testing Tissues Toxic effect Toxicology Translations Uncertainty Unhealthy Diet United States Youth Zebrafish adverse outcome antagonist biological systems chemical property computational toxicology cytotoxicity developmental disease developmental toxicity developmental toxicology diabetic diet and exercise dietary high dimensionality multi-scale modeling network models novel pancreas development pharmacologic physical science predictive modeling response small molecule spatiotemporal transcriptomics translational impact

项目摘要

PROJECT SUMMARY The CDC SEARCH for Diabetes in Youth study found that Type I Diabetes (T1D) incidence increased by 1.8% each year between 2002-2012, and Type II Diabetes (T2D) increased by 4.8%. The Environmental Determinants of Diabetes in the Young (TEDDY) study has attributed a substantial burden of T1D and T2D to environmental contaminants. Due to the increasing prevalence of diabetes and metabolic diseases (especially among youth), computational models for developmental pancreatic toxicity are needed. Understanding how multiple factors such as chemical structure, gene expression and target tissue cytotoxicity integrate and impact pancreatic health is vital. However, an integrated analysis of multiple factors at multiple scales poses great challenges due to the inherent complexity, high-dimensionality, uncertainty, and heterogeneity. Multilayer networks have emerged as a novel methodology in network science that combines multiple networks, called “layers”, into one mathematical object. Multilayer networks are able to represent multiple factors across multi- scales for a rigorous computational analysis of their interactions. Thereby, uncovering novel relations between key factors on a multi-scale. The overarching goal of this research is to create multilayer network models by which we can predict the magnitude and mechanisms of pancreatic developmental toxicity based on chemical structure in a zebrafish (Danio rerio) model. Aim 1 will build a Quantitative Structure-Activity Relationship (QSAR) model to predict mechanisms of toxicity resulting from pharmacological and toxicological exposures in the developing pancreas. The goal of Aim 1 is to utilize a multilayer network and topological clustering model to predict the relationship between exposures and pancreatic developmental toxicity based on chemical structure. Aim 2 will utilize multi-scale modeling to create an Adverse Outcome Pathway (AOP) using molecular, structural, and pathological criteria for pancreatic developmental toxicity. The goal of Aim 2 is to characterize the processes by which exposures may disrupt pancreas development and early diabetic pathogenesis. We will develop a rigorous predictive model that can be used to better inform a priori testing and expected outcomes of small molecules in the context of pancreatic developmental diseases, and we will construct a framework to connect peroxisome proliferator-activated receptor (PPAR) modulation (pharmacological & toxicological) with aberrant pancreatic development and early function.

项目总结