Although T1D is sometimes referred to as juvenile diabetes, the majority of cases occur in adults. Recent decades have seen a rapid rise in the incidence rate of type 1 diabetes (T1D) in children and in adolescents. Presently, it is not known why T1D occurs later in life for some people nor if one can delay it. This project aims to investigate the genetic regulation of age of onset in T1D with the long term goal of dissecting the genetic architecture underlying T1D and to identify means than can delay or even prevent the onset. As a complex disease, the genetic basis for T1D has been extremely difficult to solve. The project proposes to develop an integrative genomics approach to prioritize candidate genes, following a multi-level disease biology, genomic and genetic data R disease pathway R regulatory network in disease pathway R prioritization of candidate disease genes R typing and confirmation methodology. By doing so, the investigators emphasize on close integration of disease biology to its genetic investigation. The specific objectives include: (1) Identification of key disease pathways that contribute to adult- and young-onset T1D in a differential way. First, disease pathogenesis will be investigated through quantitative analysis of the cellular interaction and signaling leading to immune destruction of 2 cells, utilizing a mathematical model, MINT1D, that the investigators have developed. This will allow the identification of the key pathways responsible for disease initiation in each age-at-onset (AAO) group. Then genomic data that the Type 1 Diabetes Genetics Consortium (T1DGC) have pooled (with ~1500 multiplex families) will be compile to determine linkage loci in each AAO group of <19y and >=19y, and the pathways that have significantly enhanced representation among the positional candidates in each group will be identified. The results from both approaches will be integrated and candidate disease pathways will be determined from their convergent predictions. (2) All genes that are located within a linkage region and which also belong to the candidate disease pathways will be compiled for each AAO group as prior candidates. Time course gene expression data from the investigators'own research that profiled key tissue types in human T1D and the corresponding animal model, as well as the same type of data in the public expression data repositories will be compiled. Transcription regulatory networks of the disease pathways will be investigated utilizing these data and the Dynamics Bayesian Network (DBYN) approach. Potential gene pair relationships inferred from PubMed co-citation, GO and MeSH semantic similarity, transcription factor binding database, and expression change synchronization will be utilized as prior knowledge. The initial candidates will be prioritized according to their importance in the regulatory network. (3) Validation of the candidate genes by typing them in the world's largest T1D cohort the investigators have collected from the population of Finland, with more than 2000 singleton and more 300 multiplex families in each onset age group. Both the case-control and family based analysis will be performed. The findings will be replicated with the sample collection by T1DGC.This project, when successfully accomplished, will lead to significant social and economic benefit. Understanding the genetic regulation of age-at-onset could lead to new intervention method that delays the onset (beyond one's normal life span, or even just beyond adolescence)., which is important, as there is still not a cure for diabetes or means to prevent its eventual and devastating complications. The management of T1D is difficult particularly in the young, and in recent decades incidence in the young is rising rapidly.
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