Identifying key inflammatory genes in psoriasis via weighted gene co-expression network analysis: Potential targets for therapy

Authors

  • Huidan Li Clinical Laboratory Medicine Center, Shanghai General Hospital, Shanghai, China
  • Xiaorui Wang Clinical Laboratory Medicine Center, Shanghai General Hospital, Shanghai, China
  • Jing Zhu Clinical Laboratory Medicine Center, Jiading Branch of Shanghai General Hospital, Shanghai, China
  • Bingzhe Yang School of Medicine, Shanghai Jiao Tong University, Shanghai, China
  • Jiatao Lou Clinical Laboratory Medicine Center, Shanghai General Hospital, Shanghai, China

DOI:

https://doi.org/10.17305/bb.2024.10327

Keywords:

Psoriasis, hub gene, inflammation-related genes, chemokine, immunohistochemistry, weighted gene co-expression network analysis (WGCNA)

Abstract

Psoriasis is a globally prevalent chronic inflammatory skin disease. This study aimed to scrutinize the hub genes related to inflammation and potential molecular mechanisms in psoriasis. Utilizing mRNA expression profiles from public datasets GSE13355, GSE78097, and GSE14905, we set up a comprehensive analysis. Initially, we selected differentially expressed genes (DEGs) from psoriasis and control samples in GSE13355, followed by calculating inflammatory indices using genomic set variation analysis (GSVA). Weighted gene co-expression network analysis (WGCNA) was then applied to link significant modules with the inflammatory index. This process helped us identify differentially expressed inflammation-related genes (DE-IRGs). A protein-protein interaction (PPI) network was established, with the molecular complex detection (MCODE) plug-in pinpointing six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as central hub genes. These genes demonstrated pronounced immunohistochemical staining in psoriatic tissues compared to normal skin. Notably, the CCR7 gene exhibited the highest potential for m6A modification sites. Furthermore, we constructed transcription factor-microRNA-mRNA networks, identifying 139 microRNAs and 52 transcription factors associated with the hub genes. For the LASSO logistic regression model, the area under the curve (AUC) in the training set was 1, and in the two validation cohorts GSE78097 and GSE14905 were 1 and 0.872, respectively. In conclusion, our study highlights six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as potential biomarkers in psoriasis, providing insights into the immune and inflammatory responses as pivotal instances in disease pathogenesis. These findings pave the way for exploring new therapeutic targets, particularly focusing on chemokine-associated pathways in psoriasis treatment.

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Additional Files

Published

05-04-2024

Data Availability Statement

The original contributions presented in the study are publicly available. This data can be found here: GSE13355, GSE14905, and GSE78097. Any additional queries should be directed to the corresponding author for further elucidation.

Issue

Section

Immunology

Categories

How to Cite

1.
Identifying key inflammatory genes in psoriasis via weighted gene co-expression network analysis: Potential targets for therapy. Biomol Biomed [Internet]. 2024 Apr. 5 [cited 2024 May 27];. Available from: https://www.bjbms.org/ojs/index.php/bjbms/article/view/10327

Funding data