Multi-Omic Analysis of Phthalate Exposure and Early Life Risk of Type 2 Diabetes.

University Of Michigan At Ann Arbor, Ann Arbor MI

Investigators

Abstract

Project Summary The rise of youth onset Type 2 Diabetes Mellitus (T2DM), one of the most common endocrine diseases, is an important public health concern. Current methods to identify risk of T2DM are neither specific, such as screening for elevated body mass index (BMI), nor sensitive. Most risk factors are thought to be related to lifestyle and do not account for environmental chemical exposures or individual variation in biological response to lifestyle and chemical exposures. Despite this, evidence has emerged that links endocrine disrupting chemicals such as phthalates to T2DM. Phthalates are a class of human-made compounds found in plastics and fragrances. However, analyses linking gestational phthalate exposure, an important window of susceptibility, to endocrine disruption and disease risk later in life are sparse and rely on non- specific anthropometric outcomes such as BMI. The use of multi-omics data in epidemiological research can help to identify biomarkers of disease and predict disease development, such as elevated fasting blood glucose, before clinical symptoms occur, and quantify inter-individual differences in disease risk. Epigenomics is the measurement of environmentally modifiable chemical marks on DNA and chromatin which regulate gene expression. Metabolomics, measurements of compounds circulating in the blood, provide a real-time view of metabolic activity. These analytes may elucidate early markers of disease development and potentially serve as biomarkers of disease. The central hypothesis of this work is that changes to the epigenome and metabolome are predictive of blood glucose dysregulation in adolescence, and that gestational exposure to phthalates increases this risk. We address this hypothesis in the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) longitudinal birth cohort study. Aim 1 focuses on understanding the effect of maternal phthalate exposure on the offspring epigenome and how maternal nutrition interacts with phthalates to alter the epigenome. Aim 2 applies novel computational techniques to epigenomic and metabolomic data to predict adolescents at elevated risk for elevated fasting blood glucose. Overall, this study will contribute to the scientific knowledge base about potentially preventable exposures that contribute to T2DM development and biomarkers to improve early screening efforts. Completion of this research along with the proposed training plan will equip me with a highly specialized skillset to leverage data science techniques and include omics, nutrition, and toxicant exposure in precision environmental health research.