Proteomic changes/progression of human type 1 diabetes

  • She, Jin-Xiong (PI)
  • She, Jin Xiong (PI)

Project: Research project

Project Details


DESCRIPTION (provided by applicant): The progression from genetic predisposition to beta-cell autoimmunity and then Type 1 diabetes (T1D) is a critical but poorly understood process, resulting in a cascade of molecular and cellular changes. Identification of these changes will undoubtedly provide useful biomarkers for disease prediction and elucidation of disease mechanisms. Unfortunately, the changes associated with disease progression are difficult to document as they can occur at different times and different tissues or cells. The conventional approaches of analyzing a single gene/protein a time have had only limited success in uncovering the complex molecular pathways implicated in the autoimmune cascade. Therefore, we propose to use high throughput proteomic technologies to systematically identify proteomic changes associated with T1D progression in the serum and peripheral blood mononuclear ceils. The R21 application is designed to screen and validate putative biomarkers present in human serum samples and selected PBMC subsets using two complimentary proteomic technologies: surface-enhanced laser desorption/ionization (SELDI) and 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). The screening will be done using a large cross-sectional cohort of diabetic, pre-diabetic and control subjects, while and the validation of putative biomarkers will be accomplished using a large independent cross-sectional data set. These studies are expected to discover a number of proteins that are likely implicated in the pathogenesis of T1D and/or useful for risk assessment. In the R33 phase, we will further validate the biomarkers discovered in the R21 phase using a prospective cohort, essential for the development of predictive markers. The prospective data set should allow us to directly estimate the chance of transitions between T1D progression stages and to incorporate other risk factors such as HLA and islet autoantibody data into proteomic-based risk assessment models. We will also develop and validate highly reproducible and economic assays for the novel proteins of interest. The new assays will serve as independent confirmation of the proteomic changes identified by the discovery tools and more importantly can be used as suitable clinical tests.
StatusNot started


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