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- W4313373280 abstract "Abstract 50 Million people in the United States are estimated to suffer from an autoimmune disease, and this number is predicted to continue growing. Up to 70% of cases could be due to environmental factors. Therefore, an understanding of how diet, likely a major component of the environmental factors described, impacts the immune system merits exploration. We sought to develop a system of comparison between human epitopes implicated in seventy autoimmune diseases and the overlap between them and epitopes found in various commonly consumed animals and plants. The aim of the comparison was to construct a comprehensive database of overlap to provide an index, the Gershteyn-Ferreira index, of potential auto-immunogenicity of various diet-derived proteins. The construction of the database utilized the automation of querying and recording the epitopes with the IEDB (Immune Database and Analysis Resource) system. We created a comprehensive index for twenty-four organisms. Of note, our system personalizes the epitope overlap of the organisms per individual by integrating the human leukocyte antigen (HLA) alleles of the subject and re-running the overlapping epitopes to filter for in silico HLA binding. In addition, we mapped the tissue expression pattern of each epitope to gauge the risk of being exposed to it in the diet. With this new system, Immunodietica, we can determine exact diet-derived epitopes that could be responsible for the pathogenesis or symptom severity of autoimmunity, as well as generate a personalized ‘heat-map’ of potential triggers, the Gershteyn-Ferreira sensitivity passport, for use by autoimmune disease patients." @default.
- W4313373280 created "2023-01-06" @default.
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- W4313373280 date "2020-05-01" @default.
- W4313373280 modified "2023-09-27" @default.
- W4313373280 title "Immunodietica: towards a data-driven approach to dissect interactions between diet and autoimmune disease" @default.
- W4313373280 doi "https://doi.org/10.4049/jimmunol.204.supp.224.35" @default.
- W4313373280 hasPublicationYear "2020" @default.
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