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Navigating diabetes-related immune epitope data: resources and tools provided by the Immune Epitope Database (IEDB)

BACKGROUND: The Immune Epitope Database (IEDB), originally focused on infectious diseases, was recently expanded to allergy, transplantation and autoimmunity diseases. Here we focus on diabetes, chosen as a prototype autoimmune disease. We utilize a combined tutorial and meta-analysis format, which...

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Detalles Bibliográficos
Autores principales: Vaughan, Kerrie, Peters, Bjoern, Mallone, Roberto, von Herrath, Matthias, Roep, Bart O., Sette, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4134942/
https://www.ncbi.nlm.nih.gov/pubmed/25140192
http://dx.doi.org/10.4172/1745-7580.1000063
Descripción
Sumario:BACKGROUND: The Immune Epitope Database (IEDB), originally focused on infectious diseases, was recently expanded to allergy, transplantation and autoimmunity diseases. Here we focus on diabetes, chosen as a prototype autoimmune disease. We utilize a combined tutorial and meta-analysis format, which demonstrates how common questions, related to diabetes epitopes can be answered. RESULTS: A total of 409 references are captured in the IEDB describing >2,500 epitopes from diabetes associated antigens. The vast majority of data were derived from GAD, insulin, IA-2/PTPRN, IGRP, ZnT8, HSP, and ICA-1, and the experiments related to T cell epitopes and MHC binding far outnumbers B cell assays. We illustrate how to search by specific antigens, epitopes or host. Other examples include searching for tetramers or epitopes restricted by specific alleles or assays of interest, or searching based on the clinical status of the host. CONCLUSIONS: The inventory of all published diabetes epitope data facilitates its access for the scientific community. While the global collection of primary data from the literature reflects potential investigational biases present in the literature, the flexible search approach allows users to perform queries tailored to their preferences, including or excluding data as appropriate. Moreover, the analysis highlights knowledge gaps and identifies areas for future investigation.