Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics

Autoimmune diseases (ADs) are a broad range of diseases in which the immune response to self-antigens causes damage or disorder of tissues, and the genetic susceptibility is regarded as the key etiology of ADs. Accumulating evidence has suggested that there are certain commonalities among different...

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Autores principales:	Yanjun Ding, Mintian Cui, Jun Qian, Chao Wang, Qi Shen, Hongbiao Ren, Liangshuang Li, Fengmin Zhang, Ruijie Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	ADs genetic susceptibility network similarity functional similarity semantic similarity autoimmune tautology Genetics QH426-470
Acceso en línea:	https://doaj.org/article/1849509947b1413fbf48f440dcfa4f95
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spelling	oai:doaj.org-article:1849509947b1413fbf48f440dcfa4f952021-11-11T09:48:08ZCalculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics1664-802110.3389/fgene.2021.758041https://doaj.org/article/1849509947b1413fbf48f440dcfa4f952021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fgene.2021.758041/fullhttps://doaj.org/toc/1664-8021Autoimmune diseases (ADs) are a broad range of diseases in which the immune response to self-antigens causes damage or disorder of tissues, and the genetic susceptibility is regarded as the key etiology of ADs. Accumulating evidence has suggested that there are certain commonalities among different ADs. However, the theoretical research about similarity between ADs is still limited. In this work, we first computed the genetic similarity between 26 ADs based on three measurements: network similarity (NetSim), functional similarity (FunSim), and semantic similarity (SemSim), and systematically identified three significant pairs of similar ADs: rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), myasthenia gravis (MG) and autoimmune thyroiditis (AIT), and autoimmune polyendocrinopathies (AP) and uveomeningoencephalitic syndrome (Vogt-Koyanagi-Harada syndrome, VKH). Then we investigated the gene ontology terms and pathways enriched by the three significant AD pairs through functional analysis. By the cluster analysis on the similarity matrix of 26 ADs, we embedded the three significant AD pairs in three different disease clusters respectively, and the ADs of each disease cluster might have high genetic similarity. We also detected the risk genes in common among the ADs which belonged to the same disease cluster. Overall, our findings will provide significant insight in the commonalities of different ADs in genetics, and contribute to the discovery of novel biomarkers and the development of new therapeutic methods for ADs.Yanjun DingYanjun DingMintian CuiJun QianChao WangQi ShenHongbiao RenLiangshuang LiFengmin ZhangRuijie ZhangFrontiers Media S.A.articleADsgenetic susceptibilitynetwork similarityfunctional similaritysemantic similarityautoimmune tautologyGeneticsQH426-470ENFrontiers in Genetics, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ADs genetic susceptibility network similarity functional similarity semantic similarity autoimmune tautology Genetics QH426-470
spellingShingle	ADs genetic susceptibility network similarity functional similarity semantic similarity autoimmune tautology Genetics QH426-470 Yanjun Ding Yanjun Ding Mintian Cui Jun Qian Chao Wang Qi Shen Hongbiao Ren Liangshuang Li Fengmin Zhang Ruijie Zhang Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics
description	Autoimmune diseases (ADs) are a broad range of diseases in which the immune response to self-antigens causes damage or disorder of tissues, and the genetic susceptibility is regarded as the key etiology of ADs. Accumulating evidence has suggested that there are certain commonalities among different ADs. However, the theoretical research about similarity between ADs is still limited. In this work, we first computed the genetic similarity between 26 ADs based on three measurements: network similarity (NetSim), functional similarity (FunSim), and semantic similarity (SemSim), and systematically identified three significant pairs of similar ADs: rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), myasthenia gravis (MG) and autoimmune thyroiditis (AIT), and autoimmune polyendocrinopathies (AP) and uveomeningoencephalitic syndrome (Vogt-Koyanagi-Harada syndrome, VKH). Then we investigated the gene ontology terms and pathways enriched by the three significant AD pairs through functional analysis. By the cluster analysis on the similarity matrix of 26 ADs, we embedded the three significant AD pairs in three different disease clusters respectively, and the ADs of each disease cluster might have high genetic similarity. We also detected the risk genes in common among the ADs which belonged to the same disease cluster. Overall, our findings will provide significant insight in the commonalities of different ADs in genetics, and contribute to the discovery of novel biomarkers and the development of new therapeutic methods for ADs.
format	article
author	Yanjun Ding Yanjun Ding Mintian Cui Jun Qian Chao Wang Qi Shen Hongbiao Ren Liangshuang Li Fengmin Zhang Ruijie Zhang
author_facet	Yanjun Ding Yanjun Ding Mintian Cui Jun Qian Chao Wang Qi Shen Hongbiao Ren Liangshuang Li Fengmin Zhang Ruijie Zhang
author_sort	Yanjun Ding
title	Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics
title_short	Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics
title_full	Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics
title_fullStr	Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics
title_full_unstemmed	Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics
title_sort	calculation of similarity between 26 autoimmune diseases based on three measurements including network, function, and semantics
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/1849509947b1413fbf48f440dcfa4f95
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Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics

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