Type 1 Diabetes: Investigating the Gut Microbiome, Urinary Proteome and Metabolome
Type 1 diabetes mellitus (T1D) is characterized by autoimmune destruction of the insulin producing - cells of pancreatic islets. It is believed that T1D results from complex interactions between multiple genes, environmental factors and the immune system, and the autoimmune aspects may begin many years before the clinical manifestation of T1D. The role of environmental factors such as commensal intestinal microbiota, and microbial infections and their immunological consequences in genetically susceptible individuals are not yet properly understood. Current gold standards for determination of the at-risk population for T1D (HLA typing, auto-antibodies) and early diagnosis of diabetes (blood glucose and insulin levels) are inadequate. Comprehensive studies of changes in the resident intestinal microbiota, host metabolism and immune system reactivity in T1D patients and cohorts at risk of T1D, as well as the correlation with clinical data, anti-islet antigen antibodies and HLA genotypes will enable identification of novel biomarkers and biosignatures, and insights into the pathophysiology of the onset of T1D.
We propose to apply high-throughput genomics, proteomics and metabolomics techniques to samples that have been collected from different cohorts of T1D patients to identify distinct molecular signatures. By deconvolution of high-resolution molecular data, we expect to identify viral-microbial specific correlated patterns of proteins and metabolites. The discriminatory biomarkers and biosignatures derived, comparing T1D patients and controls, will be potentially useful for the early diagnosis of T1D onset and the prediction of T1D onset during the pre-symptomatic disease phase. To our knowledge, the proposed study will be the first of its kind that combines the diversity of 'omics' analyses. Our ultimate goal is to identify and advance biomarkers or a panel of biomarkers into the clinic, e.g. to generate a specific diagnostic test and to develop rationales for therapeutic intervention based on metabolic and immune system reactivity networks.