Epigenetic and genetic regulation of arsenic methylation and arsenic-relatedcardiovascular disease risk

SUMMARY In the United States, Native American communities face the greatest burden of chronic diseases among all ethnic groups and high rates of cardiovascular disease (CVD) incidence and mortality. Elevated disease risk may be in part attributed to arsenic in drinking water, which is a key environmental risk factor among rural households that rely on private wells. Arsenic-related CVD risk may be modified by the biomethylation of arsenic, a pathway that decreases arsenic toxicity and increases urinary excretion. Arsenic methylation efficiency varies between individuals and populations and is influenced by genetic variation. However, the role of pre- and post- transcriptional gene regulatory factors, including DNA methylation (DNAm) and microRNAs, on arsenic methylation efficiency and arsenic-induced CVD is not fully understood. This study will leverage data and biospecimens representing multiple omics layers from the Strong Heart Study (SHS) and Strong Heart Family Study (SHFS), large, prospective, well characterized cohorts of Native American adults with longitudinal data on CVD outcomes and risk biomarkers. The aims of this project are to (K00, Aim 1) determine the relationship between DNAm, arsenic methylation efficiency, and CVD to identify epigenetic biomarkers of arsenic toxicity and arsenic-related disease risk; (K99, Aim 2) determine the effect of genetic variation on DNAm associated with arsenic methylation efficiency to distinguish molecular mechanisms underlying arsenic methylation phenotypes; and (R00, Aim 3) investigate the role of microRNAs in mediating the association between arsenic exposure and methylation efficiency and CVD risk biomarkers to elucidate molecular processes underlying arsenic-related CVD. To accomplish these aims, Dr. Bozack will be receive mentorship from experts in environmental, molecular, and genetic epidemiology. In the K99 phase, Dr. Bozack will also receive training in bioinformatics and machine learning, including approaches for developing DNAm biomarkers and investigating gene-epigene interactions. In the R00 phase, she will generate circulating microRNA expression data and will further apply her training in clustering and network analyses to identify microRNA signatures linking arsenic exposure and methylation efficiency to CVD risk. The proposed training and research will enable Dr. Bozack to establish an independent research path focusing on biomarker development and applying multiple omics approaches to environmental molecular epidemiology. Furthermore, mentorship and career development activities will facilitate her transition to an independent researcher. Overall, this study will advance the understanding of gene regulatory factors involved in arsenic-related CVD risk through a multiple omics perspective, which is necessary to unravel the relationship between environmental and biological factors involved in the etiology of complex diseases. Findings will contribute the development of noninvasive biomarkers of arsenic-related CVD risk and may aid in targeting arsenic mitigation and public health interventions.