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The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data
OBJECTIVE: This study aimed to explore the shared mechanism and candidate drugs of multiple sclerosis (MS) and Sjögren’s syndrome (SS). METHODS: MS- and SS-related susceptibility genes and differentially expressed genes (DEGs) were identified by bioinformatics analysis based on genome-wide associati...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959321/ https://www.ncbi.nlm.nih.gov/pubmed/35356004 http://dx.doi.org/10.3389/fimmu.2022.857014 |
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author | Hong, Xiangxiang Wang, Xin Rang, Xinming Yin, Xinyue Zhang, Xuemei Wang, Rui Wang, Duo Zhao, Tingting Fu, Jin |
author_facet | Hong, Xiangxiang Wang, Xin Rang, Xinming Yin, Xinyue Zhang, Xuemei Wang, Rui Wang, Duo Zhao, Tingting Fu, Jin |
author_sort | Hong, Xiangxiang |
collection | PubMed |
description | OBJECTIVE: This study aimed to explore the shared mechanism and candidate drugs of multiple sclerosis (MS) and Sjögren’s syndrome (SS). METHODS: MS- and SS-related susceptibility genes and differentially expressed genes (DEGs) were identified by bioinformatics analysis based on genome-wide association studies (GWAS) and transcriptome data from GWAS catalog and Gene Expression Omnibus (GEO) database. Pathway enrichment, Gene Ontology (GO) analysis, and protein–protein interaction analysis for susceptibility genes and DEGs were performed. The drugs targeting common pathways/genes were obtained through Comparative Toxicogenomics Database (CTD), DrugBank database, and Drug–Gene Interaction (DGI) Database. The target genes of approved/investigational drugs for MS and SS were obtained through DrugBank and compared with the common susceptibility genes. RESULTS: Based on GWAS data, we found 14 hub common susceptibility genes (HLA-DRB1, HLA-DRA, STAT3, JAK1, HLA-B, HLA-DQA1, HLA-DQA2, HLA-DQB1, HLA-DRB5, HLA-DPA1, HLA-DPB1, TYK2, IL2RA, and MAPK1), with 8 drugs targeting two or more than two genes, and 28 common susceptibility pathways, with 15 drugs targeting three or more than three pathways. Based on transcriptome data, we found 3 hub common DEGs (STAT1, GATA3, PIK3CA) with 3 drugs and 10 common risk pathways with 435 drugs. “JAK-STAT signaling pathway” was included in common susceptibility pathways and common risk pathways at the same time. There were 133 overlaps including JAK-STAT inhibitors between agents from GWAS and transcriptome data. Besides, we found that IL2RA and HLA-DRB1, identified as hub common susceptibility genes, were the targets of daclizumab and glatiramer that were used for MS, indicating that daclizumab and glatiramer may be therapeutic for SS. CONCLUSION: We observed the shared mechanism of MS and SS, in which JAK-STAT signaling pathway played a vital role, which may be the genetic and molecular bases of comorbidity of MS with SS. Moreover, JAK-STAT inhibitors were potential therapies for MS and SS, especially for their comorbidity. |
format | Online Article Text |
id | pubmed-8959321 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89593212022-03-29 The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data Hong, Xiangxiang Wang, Xin Rang, Xinming Yin, Xinyue Zhang, Xuemei Wang, Rui Wang, Duo Zhao, Tingting Fu, Jin Front Immunol Immunology OBJECTIVE: This study aimed to explore the shared mechanism and candidate drugs of multiple sclerosis (MS) and Sjögren’s syndrome (SS). METHODS: MS- and SS-related susceptibility genes and differentially expressed genes (DEGs) were identified by bioinformatics analysis based on genome-wide association studies (GWAS) and transcriptome data from GWAS catalog and Gene Expression Omnibus (GEO) database. Pathway enrichment, Gene Ontology (GO) analysis, and protein–protein interaction analysis for susceptibility genes and DEGs were performed. The drugs targeting common pathways/genes were obtained through Comparative Toxicogenomics Database (CTD), DrugBank database, and Drug–Gene Interaction (DGI) Database. The target genes of approved/investigational drugs for MS and SS were obtained through DrugBank and compared with the common susceptibility genes. RESULTS: Based on GWAS data, we found 14 hub common susceptibility genes (HLA-DRB1, HLA-DRA, STAT3, JAK1, HLA-B, HLA-DQA1, HLA-DQA2, HLA-DQB1, HLA-DRB5, HLA-DPA1, HLA-DPB1, TYK2, IL2RA, and MAPK1), with 8 drugs targeting two or more than two genes, and 28 common susceptibility pathways, with 15 drugs targeting three or more than three pathways. Based on transcriptome data, we found 3 hub common DEGs (STAT1, GATA3, PIK3CA) with 3 drugs and 10 common risk pathways with 435 drugs. “JAK-STAT signaling pathway” was included in common susceptibility pathways and common risk pathways at the same time. There were 133 overlaps including JAK-STAT inhibitors between agents from GWAS and transcriptome data. Besides, we found that IL2RA and HLA-DRB1, identified as hub common susceptibility genes, were the targets of daclizumab and glatiramer that were used for MS, indicating that daclizumab and glatiramer may be therapeutic for SS. CONCLUSION: We observed the shared mechanism of MS and SS, in which JAK-STAT signaling pathway played a vital role, which may be the genetic and molecular bases of comorbidity of MS with SS. Moreover, JAK-STAT inhibitors were potential therapies for MS and SS, especially for their comorbidity. Frontiers Media S.A. 2022-03-09 /pmc/articles/PMC8959321/ /pubmed/35356004 http://dx.doi.org/10.3389/fimmu.2022.857014 Text en Copyright © 2022 Hong, Wang, Rang, Yin, Zhang, Wang, Wang, Zhao and Fu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Hong, Xiangxiang Wang, Xin Rang, Xinming Yin, Xinyue Zhang, Xuemei Wang, Rui Wang, Duo Zhao, Tingting Fu, Jin The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data |
title | The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data |
title_full | The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data |
title_fullStr | The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data |
title_full_unstemmed | The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data |
title_short | The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren’s Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data |
title_sort | shared mechanism and candidate drugs of multiple sclerosis and sjögren’s syndrome analyzed by bioinformatics based on gwas and transcriptome data |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959321/ https://www.ncbi.nlm.nih.gov/pubmed/35356004 http://dx.doi.org/10.3389/fimmu.2022.857014 |
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