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The Autoimmune Tautology: An In Silico Approach
Author(s) -
Ricardo Cifuentes,
Daniel Restrepo-Montoya,
JuanManuel Anaya
Publication year - 2012
Publication title -
autoimmune diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.681
H-Index - 32
eISSN - 2090-0422
pISSN - 2090-0430
DOI - 10.1155/2012/792106
Subject(s) - tautology (logic) , rheumatoid arthritis , gene , computational biology , in silico , medicine , autoimmune disease , disease , encode , bioinformatics , immunology , genetics , biology , computer science , autoepistemic logic , multimodal logic , description logic , programming language
There is genetic evidence of similarities and differences among autoimmune diseases (AIDs) that warrants looking at a general panorama of what has been published. Thus, our aim was to determine the main shared genes and to what extent they contribute to building clusters of AIDs. We combined a text-mining approach to build clusters of genetic concept profiles (GCPs) from the literature in MedLine with knowledge of protein-protein interactions to confirm if genes in GCP encode proteins that truly interact. We found three clusters in which the genes with the highest contribution encoded proteins that showed strong and specific interactions. After projecting the AIDs on a plane, two clusters could be discerned: Sjögren's syndrome—systemic lupus erythematosus, and autoimmune thyroid disease—type1 diabetes—rheumatoid arthritis. Our results support the common origin of AIDs and the role of genes involved in apoptosis such as CTLA4 , FASLG, and IL10 .

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