Integrated bioinformatics to identify potential key biomarkers for COVID-19-related chronic urticaria

Abstract

BackgroundA lot of studies have revealed that chronic urticaria (CU) is closely linked with COVID-19. However, there is a lack of further study at the gene level. This research is aimed to investigate the molecular mechanism of COVID-19-related CU via bioinformatic ways.MethodsThe RNA expression profile datasets of CU (GSE72540) and COVID-19 (GSE164805) were used for the training data and GSE57178 for the verification data. After recognizing the shared differently expressed genes (DEGs) of COVID-19 and CU, genes enrichment, WGCNA, PPI network, and immune infiltration analyses were performed. In addition, machine learning LASSO regression was employed to identify key genes from hub genes. Finally, the networks, gene-TF-miRNA-lncRNA, and drug-gene, of key genes were constructed, and RNA expression analysis was utilized for verification.ResultsWe recognized 322 shared DEGs, and the functional analyses displayed that they mainly participated in immunomodulation of COVID-19-related CU. 9 hub genes (CD86, FCGR3A, AIF1, CD163, CCL4, TNF, CYBB, MMP9, and CCL3) were explored through the WGCNA and PPI network. Moreover, FCGR3A, TNF, and CCL3 were further identified as key genes via LASSO regression analysis, and the ROC curves confirmed the dependability of their diagnostic value. Furthermore, our results showed that the key genes were significantly associated with the primary infiltration cells of CU and COVID-19, such as mast cells and macrophages M0. In addition, the key gene-TF-miRNA-lncRNA network was constructed, which contained 46 regulation axes. And most lncRNAs of the network were proved to be a significant expression in CU. Finally, the key gene-drug interaction network, including 84 possible therapeutical medicines, was developed, and their protein-protein docking might make this prediction more feasible.ConclusionsTo sum up, FCGR3A, TNF, and CCL3 might be potential biomarkers for COVID-19-related CU, and the common pathways and related molecules we explored in this study might provide new ideas for further mechanistic research.

Evaluation of the Genes and Molecular Pathways Involved in Skin Lesions in Patients with COVID-19: Systems Biology and Bioinformatics Analysis Approach

“…The current study showed that CXCL1, CCL2, CCL3, CXCL6, CCL4, and CXCL2 chemokines play important roles in the occurrence of skin manifestation. In the study by Zhang et al, it was found that increased production of CCL3 and CCL4 in COVID-19 patients caused chronic urticarial (45). Moreover, in the study of Rybkina et al, CCL3 and CCL4 produced by cytokine storms cause the progression of skin lesions (46).…”

Involvement of CCL2 and CH25H Genes and TNF signaling pathways in mast cell activation and pathogenesis of chronic spontaneous urticaria

“…PCA and boxplot analyses demonstrated the effectiveness of the merged dataset in subsequent analyses. GSE57178 and GSE72540 were individually utilized in previous studies ( 25 , 26 ). However, our dataset merging approach increased the sample size and enhanced reproducibility and data integration.…”

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

“…Chronic urticaria (CU) is a dermatological condition that manifests as an angioedema or wheal for more than 42 days. 1 It is a chronic pruritus condition with a global prevalence of about 1.8%, steadily rising during the coronavirus 2019 (COVID‐19) pandemic period. 2 , 3 CU affects the quality of life of individuals and leads to financial burdens on families seeking medical care and treatment.…”