Bioinformatics analysis to reveal the potential comorbidity mechanism in psoriasis and nonalcoholic steatohepatitis

Chronic urticaria (CU) is characterized by persistent skin hives, redness, and itching, enhanced by immune dysregulation and inflammation. Our main objective is identifying key genes and molecular mechanisms of chronic urticaria based on bioinformatics. We used the Gene Expression Omnibus (GEO) database and retrieved two GEO datasets, GSE57178 and GSE72540. The raw data were extracted, pre‐processed, and analyzed using the GEO2R tool to identify the differentially expressed genes (DEGs). The samples were divided into two groups: healthy samples and CU samples. We defined cut‐off values of log2 fold change ≥1 and p < .05. Analyses were performed in the Kyoto Encyclopaedia of Genes and Genomes (KEGG), the Database for Annotation, Visualization and Integrated Discovery (DAVID), Metascape, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and CIBERSOFT databases. We obtained 1613 differentially expressed genes. There were 114 overlapping genes in both datasets, out of which 102 genes were up‐regulated while 12 were down‐regulated. The biological processes included activation of myeloid leukocytes, response to inflammations, and response to organic substances. Moreover, the KEGG pathways of CU were enriched in the Nuclear Factor‐Kappa B (NF‐kB) signaling pathway, Tumor Necrosis Factor (TNF) signaling pathway, and Janus kinase/signal transducers and activators of transcription (JAK‐STAT) signaling pathway. We identified 27 hub genes that were implicated in the pathogenesis of CU, such as interleukin‐6 (IL‐6), Prostaglandin‐endoperoxide synthase 2 (PTGS2), and intercellular adhesion molecule‐1 (ICAM1). The complex interplay between immune responses, inflammatory pathways, cytokine networks, and specific genes enhances CU. Understanding these mechanisms paves the way for potential interventions to mitigate symptoms and improve the quality of life of CU patients.

Section: Discussionmentioning

confidence: 74%

Identification of key genes and molecular mechanisms of chronic urticaria based on bioinformatics

Guo,

et al. 2024

“…It is worth mentioning that the study by Xian et al. demonstrated that IFIT1 and IRF9 are important genes linking psoriasis and nonalcoholic steatohepatitis, 22 and obesity has been proven to be a risk factor for nonalcoholic steatohepatitis 23 . Therefore, PI3 may also be an important link between obesity and nonalcoholic steatohepatitis.…”

Section: Discussionmentioning

confidence: 98%

Exploring the comorbidity mechanisms between psoriasis and obesity based on bioinformatics

Gao,

2024

BackgroundPsoriasis is a chronic, recurrent, immune‐mediated inflammatory skin disease characterized by erythematous scaly lesions. Obesity is currently a major global health concern, increasing the risk of diseases such as cardiovascular diseases and diabetes. Since the correlation between psoriasis and obesity, as well as hypertension, diabetes, and cardiovascular diseases, has been clinically evidenced, it is of certain clinical significance to explore the mechanisms underlying the comorbidity of psoriasis with these conditions.Materials and methodsGene targets for both diseases were obtained from the Gene Expression Omnibus (GEO) comprehensive gene expression database. Differential gene analysis, intersection gene analysis, construction and visualization of protein‐protein interaction networks (PPI) using R software, Cytoscape 3.8.2 software, online tools such as String, and enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed, with relevant graphics generated.ResultsAnalysis identified 29 intersecting genes between the two diseases, with 10 key targets such as S100A7 and SERPINB4. Enrichment analysis indicated their involvement in regulating biological processes such as leukocyte chemotaxis, migration, and chronic inflammatory responses through cellular structures such as intracellular vesicles and extracellular matrix. Molecular functions, including RAGE receptor binding, Toll‐like receptor binding, and fatty acid binding, were found to simultaneously regulate psoriasis and obesity.ConclusionPsoriasis and obesity may mutually influence each other through multiple targets and pathways, emphasizing the importance of considering comorbidity treatment and daily care in clinical practice.

“…As a systemic disease, psoriasis is also related with many diseases and numerous studies have already established the relationship between psoriasis and other diseases like depression, nonalcoholic steatohepatitis, and IBD 36–41 . Our previous work focused on the comorbidity mechanism between psoriasis and nonalcoholic steatohepatitis, and identified several key genes as potential therapeutic targets using bioinformatics methods 42 . This discovery not only aids in understanding the comorbidity mechanisms of these two diseases but also emphasizes the broader applicability of bioinformatics in revealing complex disease relationships.…”

Section: Discussionmentioning

confidence: 99%

“…[36][37][38][39][40][41] Our previous work focused on the comorbidity mechanism between psoriasis and nonalcoholic steatohepatitis, and identified several key genes as potential therapeutic targets using bioinformatics methods. 42 This discovery not only aids in understanding the comorbidity mechanisms of these two diseases but also emphasizes the broader applicability of bioinformatics in revealing complex disease relationships. Ding et al suggested that FOS may play a critical role in both IBD and psoriasis, contributing to a growing body of evidence supporting the genetic commonality between these diseases.…”

Section: Shokrollah Et Al Have Shed Light On Potential Novel Biomarke...mentioning

confidence: 93%

Identification of potential crucial genes shared in psoriasis and ulcerative colitis by machine learning and integrated bioinformatics

Zhang,

Feng,

Chen

et al. 2024

Self Cite

BackgroundMounting evidence suggest that there are an association between psoriasis and ulcerative colitis (UC), although the common pathogeneses are not fully understood. Our study aimed to find potential crucial genes in psoriasis and UC through machine learning and integrated bioinformatics.MethodsThe overlapping differentially expressed genes (DEGs) of the datasets GSE13355 and GSE87466 were identified. Then the functional enrichment analysis was performed. The overlapping genes in LASSO, SVM‐RFE and key module in WGCNA were considered as potential crucial genes. The receiver operator characteristic (ROC) curve was used to estimate their diagnostic confidence. The CIBERSORT was conducted to evaluate immune cell infiltration. Finally, the datasets GSE30999 and GSE107499 were retrieved to validate.Results112 overlapping DEGs were identified in psoriasis and UC and the functional enrichment analysis revealed they were closely related to the inflammatory and immune response. Eight genes, including S100A9, PI3, KYNU, WNT5A, SERPINB3, CHI3L2, ARNTL2, and SLAMF7, were ultimately identified as potential crucial genes. ROC curves showed they all had high confidence in the test and validation datasets. CIBERSORT analysis indicated there was a correlation between infiltrating immune cells and potential crucial genes.ConclusionIn our study, we focused on the comprehensive understanding of pathogeneses in psoriasis and UC. The identification of eight potential crucial genes may contribute to not only understanding the common mechanism, but also identifying occult UC in psoriasis patients, even serving as therapeutic targets in the future.