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pmid:33262784

Identification of Common Differentially Expressed Genes and Potential Therapeutic Targets in Ulcerative Colitis and Rheumatoid Arthritis.

Yueying Chen · Hanyang Li · Lijie Lai · Qi Feng · Jun Shen

Frontiers in genetics · 2020 doi:10.3389/fgene.2020.572194

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:33262784
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science-record
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2026-11-01T15:41:17Z
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2026-11-01T22:02:38Z
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paper object · 10 fields
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title
Identification of Common Differentially Expressed Genes and Potential Therapeutic Targets in Ulcerative Colitis and Rheumatoid Arthritis.
doi
10.3389/fgene.2020.572194
pmid
33262784
authors array · 5 items
[0]
Yueying Chen
[1]
Hanyang Li
[2]
Lijie Lai
[3]
Qi Feng
[4]
Jun Shen
journal
Frontiers in genetics
year
2020
abstract
Ulcerative colitis (UC) and rheumatoid arthritis (RA) are immune-mediated inflammatory diseases (IMIDs) with similar symptoms and common genomics. However, the relationship between UC and RA has not been investigated thoroughly. Therefore, this study aimed to establish the differentially expressed genes (DEGs) and potential therapeutic targets in UC and RA. Three microarray datasets (GSE38713, GSE1919, and GSE12251) were selected from the Gene Expression Omnibus (GEO) database for analysis. We used R software to identify the DEGs and performed enrichment analyses. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape software were used to construct the protein-protein interaction (PPI) network and identify the hub genes. A regulatory network based on the constructed PPI was generated using StarBase and PROMO databases. We identified a total of 1542 and 261 DEGs in UC and RA. There were 169 common DEGs identified in both UC and RA, including 63 upregulated genes (DEGs1) and nine downregulated genes (DEGs2). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs1 and DEGs2 in the PPI network revealed that the genes enriched were involved in immunity. A total of 45 hub genes were selected based on high scores of correlation; three hub genes (SRGN, PLEK, and FCGR3B) were found to be upregulated in UC and RA, and downregulated in UC patients with response to infliximab treatment. The identification of novel DEGs and hub genes in the current study contributes to a novel perception for latent functional mechanisms and presents potential prognostic indicators and therapeutic targets in UC and RA.
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
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A Predictive Response Signature to Infliximab Treatment in Ulcerative Colitis
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GSM948589
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570
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Expression data from intestinal mucosa of patients with UC
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The GO enrichment analysis of DEGs3 and DEGs4 (top 3 terms according to p.adjust).
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GO Enrichment Analyses of Independent DEGs in UC and RA
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The GO enrichment analysis of DEGs3 and DEGs4 (top 3 terms according to p.adjust).
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[1] array · 6 items
[0]
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138
[5]
3.44E-41
[2] array · 6 items
[0]
[1]
[2]
GO:0006959
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110
[5]
2.09E-37
[3] array · 6 items
[0]
[1]
[2]
GO:0050727
[3]
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[4]
120
[5]
1.06E-30
[4] array · 6 items
[0]
[1]
CC
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GO:0062023
[3]
Collagen-containing extracellular matrix
[4]
109
[5]
2.07E-32
[5] array · 6 items
[0]
[1]
[2]
GO:0009897
[3]
External side of plasma membrane
[4]
98
[5]
1.92E-26
[6] array · 6 items
[0]
[1]
[2]
GO:0019814
[3]
Immunoglobulin complex
[4]
53
[5]
3.78E-20
[7] array · 6 items
[0]
[1]
MF
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GO:0003823
[3]
Antigen binding
[4]
57
[5]
1.83E-21
[8] array · 6 items
[0]
[1]
[2]
GO:0005201
[3]
Extracellular matrix structural constituent
[4]
47
[5]
1.61E-13
[9] array · 6 items
[0]
[1]
[2]
GO:0034987
[3]
Immunoglobulin receptor binding
[4]
31
[5]
2.48E-13
[10] array · 6 items
[0]
DEGs4
[1]
BP
[2]
GO:0046677
[3]
Response to antibiotic
[4]
14
[5]
0.000109
[11] array · 6 items
[0]
[1]
[2]
GO:0051384
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[4]
10
[5]
0.000109
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[0]
[1]
[2]
GO:0031960
[3]
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[4]
10
[5]
0.000193
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[0]
[1]
CC
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GO:0009897
[3]
External side of plasma membrane
[4]
16
[5]
1.88E-06
[14] array · 6 items
[0]
[1]
[2]
GO:0044449
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Contractile fiber part
[4]
8
[5]
0.008248
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[0]
[1]
[2]
GO:0030665
[3]
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[5]
0.008248
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8
[5]
0.000361
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[5]
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tial therapeutic targets in UC and RA. Three microarray datasets (GSE38713, GSE1919, and GSE12251) w
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Complete file
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However, the relationship between UC and RA has not been investigated thoroughly. Therefore, this study aimed to establish the differentially expressed genes (DEGs) and potential therapeutic targets in UC and RA. Three microarray datasets (GSE38713, GSE1919, and GSE12251) were selected from the Gene Expression Omnibus (GEO) database for analysis. We used R software to identify the DEGs and performed enrichment analyses. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape software were used to construct the protein-protein interaction (PPI) network and identify the hub genes. A regulatory network based on the constructed PPI was generated using StarBase and PROMO databases. We identified a total of 1542 and 261 DEGs in UC and RA. There were 169 common DEGs identified in both UC and RA, including 63 upregulated genes (DEGs1) and nine downregulated genes (DEGs2). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs1 and DEGs2 in the PPI network revealed that the genes enriched were involved in immunity. A total of 45 hub genes were selected based on high scores of correlation; three hub genes (SRGN, PLEK, and FCGR3B) were found to be upregulated in UC and RA, and downregulated in UC patients with response to infliximab treatment. The identification of novel DEGs and hub genes in the current study contributes to a novel perception for latent functional mechanisms and presents potential prognostic indicators and therapeutic targets in UC and RA.", "claims": [{"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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