STAT3 and SPI1, may lead to the immune system dysregulation and heterotopic ossification in ankylosing spondylitis

Liang, Tuo; Chen, Jiarui; Xu, Guoyong; Zhang, Zide; Xue, Jiang; Zeng, Huilan; Jiang, Jie; Chen, Tianyou; Qin, Zhaojie; Li, Hao; Ye, Zhen; Nie, Yunfeng; Zhan, Xinli; Liu, Chong

doi:10.1186/s12865-022-00476-6

Cited by 11 publications

(5 citation statements)

References 45 publications

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“…In addition, activation of the IL-10/ STAT3 signaling pathway promotes macrophage polarization to the M2 type [78]. STAT3 and SPI1 are overexpressed in patients with ankylosing spondylitis and are closely associated with immune system disorders [79]. Similarly, we found that STAT3 and SPI1 were overexpressed in patients with both AMI and UC, thus suggesting that SPI1/STAT3 may be an important pathway leading to AMI and UC; however, further experimental verification is warranted.…”

Section: Discussionmentioning

confidence: 61%

Uncovering the Genetic Link between Acute Myocardial Infarction and Ulcerative Colitis Co-Morbidity through a Systems Biology Approach

Cui¹,

Cai²,

Wu³

et al. 2023

CVIA

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Background: Cardiovascular diseases, particularly acute myocardial infarction, are the leading cause of disability and death. Atherosclerosis, the pathological basis of AMI, can be accelerated by chronic inflammation. Ulcerative colitis (UC), a chronic inflammatory disease associated with immunity, contributes to the risk of AMI development. However, controversy continues to surround the relationship between these two diseases. The present study unravels the pathogenesis of AMI and UC, to provide a new perspective on the clinical management of patients with these comorbidities. Methods: Microarray datasets GSE66360 and GSE87473 were downloaded from the Gene Expression Omnibus database. Common differentially expressed genes (co-DEGs) between AMI and UC were identified, and the following analyses were performed: enrichment analysis, protein-protein interaction network construction, hub gene identification and co-expression analysis. Results: A total of 267 co-DEGs (233 upregulated and 34 downregulated) were screened for further analysis. GO enrichment analysis suggested important roles of chemokines and cytokines in AMI and UC. In addition, the lipopolysaccharide-mediated signaling pathway was found to be closely associated with both diseases. KEGG enrichment analysis revealed that lipid and atherosclerosis, NF-κB, TNF and IL-17 signaling pathways are the core mechanisms involved in the progression of both diseases. Finally, 11 hub genes were identified with cytoHubba: TNF, IL1B, TLR2, CXCL8, STAT3, MMP9, ITGAX, CCL4, CSF1R, ICAM1 and CXCL1. Conclusion: This study reveals a co-pathogenesis mechanism of AMI and UC regulated by specific hub genes, thus providing ideas for further mechanistic studies, and new perspectives on the clinical management of patients with these comorbidities.

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Section: Discussionmentioning

confidence: 61%

Uncovering the Genetic Link between Acute Myocardial Infarction and Ulcerative Colitis Co-Morbidity through a Systems Biology Approach

Cui¹,

Cai²,

Wu³

et al. 2023

CVIA

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“…For example, PU.1 can facilitate the progression of rheumatoid arthritis by broblast-like synoviocytes and inhibiting macrophages [42] and promotes the expression of pro-in ammatory cytokines by inhibiting miR-150 in autoimmune encephalitis macrophages [43]. Over and above the previously mentioned important role of SPI1 in osteoblast differentiation and function reported by Liang et al [35], It has been reported that SPI1 can regulate the differentiation of dental pulp stem cells by inhibiting the expression of noggin [44]. This may explain the occurrence of ectopic ossi cation of AS, which in turn leads to spinal fusion.…”

Section: Discussionmentioning

confidence: 84%

“…[6,34]. Recently, Liang et al [35] found that Osteoblast differentiation and bone formation in AS may be regulated by STAT3 and SPI1 through MAPK signaling pathway, JAK/STAT and Wnt receptors, and interestingly, GSEA results showed that DYSF is highly enriched in MAPK signaling pathway, and the strong correlation between STAT3 and DYSF suggests that DYSF in AS in ammatory response may likewise play an important role. The SPI1 gene encoding PU.1 has been shown to affect the differentiation and function of multiple myeloid cells [36][37][38][39], It plays a key role in the human immune system and has been shown to be involved in the pathogenesis of many immune-related tumor diseases [40,41].…”

Section: Discussionmentioning

confidence: 99%

Identification immune-related biomarkers of ankylosing spondylitis based on bioinformatics analysis

Cao

Dong

et al. 2023

Preprint

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Objective: The aim of this study is to search for key genes in ankylosing spondylitis through comprehensive bioinformatics analysis, thus providing some theoretical support for future diagnosis and treatment of AS and further research. Methods: The expression matrix of ankylosing spondylitis was downloaded and integrated through public libraries. A bioinformatic approach was used to screen differential genes and perform functional enrichment analysis to obtain biological functions and signaling pathways associated with the disease. Weighted correlation network analysis (WGCNA) was used to further obtain key genes. Immune infiltration analysis was performed using the CIBERSORT algorithm to obtain the correlation analysis of key genes with immune cells. The GWAS data of AS were analyzed to identify the pathogenic regions of key genes in AS. Finally, potential therapeutic agents for AS were predicted using these key genes. Results: A total of 7 potential biomarkers were identified: DYSF, BASP1, PYGL, SPI1, C5AR1, ANPEP and SORL1.ROC curves showed good prediction of each gene. T cell, CD4 naive, and neutrophil levels were significantly higher in the disease group compared to the paired normal group, and key gene expression was strongly correlated with immune cells.CMap results showed that the expression profiles of ibuprofen, forskolin, bongkrek-acid, and cimaterol showed the most significant negative correlation with the expression profiles of disease perturbations, suggesting that these drugs may play a role in AS play a good role in the treatment. Conclusion: The potential biomarkers of AS screened in this study are closely related to the level of immune cell infiltration and play an important role in the immune microenvironment. This may provide help for clinical diagnosis and treatment of AS and provide new ideas for further research.

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“…STAT3 is involved in the regulation of Th17 cell development and thus in activation of the IL-23/IL-17 axis and contributes to the development of several inflammatory diseases [ 38 , 39 ]. It has recently been reported that STAT3 and SPI1 may be involved in osteoblast differentiation and bone formation in AS patients through the MAPK signalling pathway, JAK/STAT and Wnt receptors [ 40 ]. The GSEA results showed that the DYSF gene was enriched in the MAPK signalling pathway, suggesting that DYSF may be involved in osteoblast differentiation and bone formation in AS.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential biomarkers for ankylosing spondylitis based on bioinformatics analysis

Cao

Dong

et al. 2023

BMC Musculoskelet Disord

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Objective The aim of this study was to search for key genes in ankylosing spondylitis (AS) through comprehensive bioinformatics analysis, thus providing some theoretical support for future diagnosis and treatment of AS and further research. Methods Gene expression profiles were collected from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) by searching for the term "ankylosing spondylitis". Ultimately, two microarray datasets (GSE73754 and GSE11886) were downloaded from the GEO database. A bioinformatic approach was used to screen differentially expressed genes and perform functional enrichment analysis to obtain biological functions and signalling pathways associated with the disease. Weighted correlation network analysis (WGCNA) was used to further obtain key genes. Immune infiltration analysis was performed using the CIBERSORT algorithm to conduct a correlation analysis of key genes with immune cells. The GWAS data of AS were analysed to identify the pathogenic regions of key genes in AS. Finally, potential therapeutic agents for AS were predicted using these key genes. Results A total of 7 potential biomarkers were identified: DYSF, BASP1, PYGL, SPI1, C5AR1, ANPEP and SORL1. ROC curves showed good prediction for each gene. T cell, CD4 naïve cell, and neutrophil levels were significantly higher in the disease group than in the paired normal group, and key gene expression was strongly correlated with immune cells. CMap results showed that the expression profiles of ibuprofen, forskolin, bongkrek-acid, and cimaterol showed the most significant negative correlation with the expression profiles of disease perturbations, suggesting that these drugs may play a role in AS treatment. Conclusion The potential biomarkers of AS screened in this study are closely related to the level of immune cell infiltration and play an important role in the immune microenvironment. This may provide help in the clinical diagnosis and treatment of AS and provide new ideas for further research.

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STAT3 and SPI1, may lead to the immune system dysregulation and heterotopic ossification in ankylosing spondylitis

Cited by 11 publications

References 45 publications

Uncovering the Genetic Link between Acute Myocardial Infarction and Ulcerative Colitis Co-Morbidity through a Systems Biology Approach

Uncovering the Genetic Link between Acute Myocardial Infarction and Ulcerative Colitis Co-Morbidity through a Systems Biology Approach

Identification immune-related biomarkers of ankylosing spondylitis based on bioinformatics analysis

Identification of potential biomarkers for ankylosing spondylitis based on bioinformatics analysis

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