ABSTRACT
Our proposal aims to uncover the intricate relationships between environmental, genetic, and 'omic factors in
Type 2 Diabetes (T2D) development. Given the limitations of environmental and genetic studies in fully
elucidating T2D risk, we intend to identify their combined effects in diverse populations and their role in insulin
resistance and beta-cell dysfunction. Central to our research is the exposome, representing environmental and
behavioral factors, and the genome, representing polygenic risk, and its influence on insulin resistance, beta-
cell function. Are there different genetic and exposomic pathways to insulin resistance and beta-cell
dysfunction? Circulating blood 'omic assays, such as the metabolome and proteome, will be instrumental in
deducing exposomic and genomic phenotype pathways related to insulin secretion and resistance that, in turn,
ultimately lead to T2D. Aim 1. Perform and create software for exposome-wide by genome-wide polygenic
predictors study (E by PRS) against insulin resistance, B-cell function and incident T2D. We hypothesize that it
is possible to identify differences of the effect of the exposome and the genome across the diabetes physiome,
including measures of insulin resistance (e.g, HOMA-IR), beta-cell function (HOMA-B, insulin levels), elevated
glycemic traits (e.g., HA1C%) in CDC NHANES with linked Medicare, Framingham Heart Study (FHS), Multi-
ethnic Study on Atherosclerosis (MESA), Coronary Artery Risk Development in Young Adults Study (CARDIA),
and Mass General Brigham Biobank (MGBB). We will deliver software and data to identify the architecture of
the longitudinal exposome and polygenic predictors in T2D and glycemic traits.
Aim 2. Catalog circulating biomarkers associated with the exposome and the genome and relate these
biomarkers to incident diabetes across biobanks. We hypothesize that circulating `omics will capture
endogenous responses to the exposome and genome, called Exposure Biomarkers (ExBs), and Genome
Biomarkers (GeBs), respectively. Biological responses will be associated with incident T2D, and output a
database of predictions between the genome, exposome and circulating `omics (the “genome-exposome
atlas”), deriving new biomarkers of exposure. We will use genetic approaches, including Mendelian
randomization to infer causal effects between the ExB biomarkers and T2D. We expect this application to
develop a new systems genetics/physiology approach for discovering elusive exposome, and exposome by
PRS interactions, in T2D. Our open data and analytic products and pipelines will increase the value of existing
federal resources, making exposome and genome research accessible to diabetes researchers.
