Abstract
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.
Highlights
Autoimmune diseases (ADs) are characterized by causing abnormal immune response which can damage human tissues as a result of the loss of immune tolerance to self-antigens (Margo and Harman, 2016)
All of AD pairs were sorted in descending according to their scores of network similarity (NetSim), functional similarity (FunSim), and semantic similarity (SemSim)
To enhance the reliability of the study, we selected ten AD pairs from intersection of top 50 AD pairs with the highest NetSim score, top 50 AD pairs with the highest FunSim score, and top 50 AD pairs with the highest SemSim score for further analysis (Figure 2 and Supplementary Tables S2–4), which were considered as potential pairs of similar ADs
Summary
Autoimmune diseases (ADs) are characterized by causing abnormal immune response which can damage human tissues as a result of the loss of immune tolerance to self-antigens (Margo and Harman, 2016). ADs share several clinical signs and symptoms, physiopathological mechanisms, and environmental and genetic factors, and this fact indicates that they have a common origin, which has been called the autoimmune tautology. A growing body of evidence has indicated the existence of the autoimmune tautology among various ADs: 1) Different ADs exhibit the same phenotypic characteristics (Anaya, 2017). These diseases, whether organ-specific or systematic, show tissue and organ damage and inflammatory pathological features (Place and Kanneganti, 2020). The studies on the genetic similarity of ADs can help us to dissect AD pathogenesis, and contribute to the discovery of novel biomarkers and the development of new therapeutic methods for ADs, which is extremely important in clinical research
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