Type 2 diabetes (T2D) risk, insulin resistance (IR) and glucose homeostasis (GH) traits are influ- enced by genes, physiology and lifestyle factors. Genetic association studies are used to under- stand the genetic architecture of complex traits ? but only implicate regions of the genome. Ge- netic sequence does not cause disease ? genetic changes influence disease risk through many processes: gene regulation; gene transcription and expression; protein levels and function; and the resulting cellular processes and metabolic output. Many of these processes are also influ- enced by environmental exposures and lifestyle factors through epigenetic mechanisms. Further insight to causal relationships between genes and environment can be gained from integrating these resources, allowing us to identify tissue-specific non-coding functional elements, predict function consequences of genetic variants in these element, and design association tests of com- mon and rare alleles within these elements on T2D, IR and GH. My long-term goal is to under- stand the genetic and epigenomic architecture of insulin resistance and T2D risk and develop strategies for translating these epidemiological findings to clinical care. In my K01 project, Inte- grating diabetes pathophysiology from genotype to phenotype in whole genome sequence asso- ciation studies of glycemic traits, I am increasing the statistical power of whole genome associa- tion studies (WGAS) by: (a) prioritizing regions of the genome that are functionally linked to genes involved in GH, and (b) refining GH phenotypes for association and risk prediction models.
The aims of this R03 proposal are to (1) implement workflows for summarization and sharing of ge- nomic, epigenomics and multi-omic discoveries from the K01 project; and (2) build predictive models for T2D risk, IR and GH that integrate gene expression, epigenome, chromatin confor- mation and metabolome data. Using the full spectrum of allele frequency variation available in TOPMed (common and rare variants) we will construct polygenic risk models and explore linking genetics to the many molecular and cellular processes that influence T2D risk, IR and GH. The expected outcomes of this proposal and the ongoing K01 project are WGAS of T2D and glycemic traits that fully integrate diabetes-specific functional data, and necessary preliminary data and a platform for a future R01 proposal that responds to the translational goals of the NIDDK for T2D research: adapting genomic and molecular epidemiological discoveries to ?point of care? in the clinic.
Type 2 diabetes (T2D) risk, insulin resistance (IR) and glucose homeostasis (GH) traits are influenced by genes, physiology and lifestyle factors and whole genome association studies (WGAS) of T2D, IR and GH traits have been performed. The objectives of this proposal are to build the infrastructure for disseminating integrative WGAS discoveries and investigate ?next generation? causal inference techniques that use ?multi-omic? data. The expected outcomes of this proposal are WGAS of T2D and glycemic traits that fully integrate diabetes-specific functional data, and necessary preliminary data and a platform for a future R01 proposal that responds to the translational goals of the NIDDK for T2D research: adapting genomic and molecular epidemiological discoveries to ?point of care? in the clinic. !
