Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and Semantics Article Swipe
Yanjun Ding
,
Mintian Cui
,
Jun Qian
,
Chao Wang
,
Shen Qi
,
Hongbiao Ren
,
Liangshuang Li
,
Fengmin Zhang
,
Ruijie Zhang
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3389/fgene.2021.758041
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3389/fgene.2021.758041
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.
Related Topics
Concepts
Semantic similarity
Similarity (geometry)
Disease
Gene ontology
Computational biology
Genetic similarity
Rheumatoid arthritis
Etiology
Autoimmune disease
Immunology
Bioinformatics
Biology
Medicine
Gene
Genetics
Computer science
Information retrieval
Artificial intelligence
Gene expression
Population
Internal medicine
Environmental health
Image (mathematics)
Genetic diversity
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fgene.2021.758041
- OA Status
- gold
- Cited By
- 3
- References
- 57
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3214412357
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3214412357Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fgene.2021.758041Digital Object Identifier
- Title
-
Calculation of Similarity Between 26 Autoimmune Diseases Based on Three Measurements Including Network, Function, and SemanticsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-11-11Full publication date if available
- Authors
-
Yanjun Ding, Mintian Cui, Jun Qian, Chao Wang, Shen Qi, Hongbiao Ren, Liangshuang Li, Fengmin Zhang, Ruijie ZhangList of authors in order
- Landing page
-
https://doi.org/10.3389/fgene.2021.758041Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.3389/fgene.2021.758041Direct OA link when available
- Concepts
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Semantic similarity, Similarity (geometry), Disease, Gene ontology, Computational biology, Genetic similarity, Rheumatoid arthritis, Etiology, Autoimmune disease, Immunology, Bioinformatics, Biology, Medicine, Gene, Genetics, Computer science, Information retrieval, Artificial intelligence, Gene expression, Population, Internal medicine, Environmental health, Image (mathematics), Genetic diversityTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2023: 1Per-year citation counts (last 5 years)
- References (count)
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57Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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