Department of Dermatology and Venereology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Hubei Provincial Key Laboratory of Occurrence and Intervention of Kidney Diseases, Medical College, Hubei Polytechnic University, Huangshi, China.
Front Immunol. 2022 Sep 12;13:971071. doi: 10.3389/fimmu.2022.971071. eCollection 2022.
Psoriasis is a common inflammatory skin disease that has a great impact on patients' physical and mental health. However, the causes and underlying molecular mechanisms of psoriasis are still largely unknown.
The expression profiles of genes from psoriatic lesion samples and skin samples from healthy controls were integrated the sva software package, and differentially expressed genes (DEGs) between psoriasis and healthy skin were screened by the limma package. Furthermore, GO and KEGG pathway enrichments for the DEGs were performed using the Clusterprofiler package. Protein-protein interaction (PPI) networks for the DEGs were then constructed to identify hub genes. scGESA analysis was performed on a single-cell RNA sequencing dataset irGSEA. In order to find the cytokines correlated with the hub genes expression, single cell weighted gene co-expression network analyses (scWGCNA) were utilized to build a gene co-expression network. Furthermore, the featured genes of psoriasis found in suprabasal keratinocytes were intersected with hub genes. We then analyzed the expression of the intersection genes and cytokines in the integrated dataset. After that, we used other datasets to reveal the changes in the intersection genes' expression levels during biological therapy. The relationship between intersection genes and PASI scores was also explored.
We identified 148 DEGs between psoriatic and healthy samples. GO and KEGG pathway enrichment analysis suggested that DEGs are mainly involved in the defense response to other organisms. The PPI network showed that 11 antiviral proteins (AVPs) were hub genes. scGSEA analysis in the single-cell transcriptome dataset showed that those hub genes are highly expressed in keratinocytes, especially in suprabasal keratinocytes. ISG15, MX1, IFI44L, and IFI27 were the characteristic genes of psoriasis in suprabasal keratinocytes. scWGCNA showed that three cytokines-IL36G, MIF, and IL17RA-were co-expressed in the turquoise module. Only interleukin-36 gamma (IL36G) was positively correlated with AVPs in the integrated dataset. IL36G and AVPs were found co-expressed in a substantial number of suprabasal keratinocytes. Furthermore, we found that the expression levels of IL36G and the 4 AVPs showed positive correlation with PASI score in patients with psoriasis, and that these levels decreased significantly during treatment with biological therapies, but not with methotrexate.
IL36G and antiviral proteins may be closely related with the pathogenesis of psoriasis, and they may represent new candidate molecular markers for the occurrence and severity of psoriasis.
银屑病是一种常见的炎症性皮肤病，对患者的身心健康有很大影响。然而，银屑病的病因和潜在的分子机制在很大程度上仍不清楚。
整合银屑病病变样本和健康对照皮肤样本的基因表达谱，使用 sva 软件包筛选银屑病和健康皮肤之间的差异表达基因（DEGs）。然后，使用 Clusterprofiler 包对 DEGs 进行 GO 和 KEGG 通路富集分析。构建 DEGs 的蛋白质-蛋白质相互作用（PPI）网络以识别关键基因。在 irGSEA 的单细胞 RNA 测序数据集上进行 scGESA 分析。为了找到与关键基因表达相关的细胞因子，我们利用单细胞加权基因共表达网络分析（scWGCNA）构建基因共表达网络。此外，将在表皮上层角质形成细胞中发现的银屑病特征基因与关键基因进行交集。然后，我们分析了整合数据集中文献中交叉基因和细胞因子的表达。之后，我们使用其他数据集揭示了生物治疗过程中交叉基因表达水平的变化。还探讨了交叉基因与 PASI 评分之间的关系。
我们在银屑病和健康样本之间鉴定出 148 个 DEGs。GO 和 KEGG 通路富集分析表明，DEGs 主要参与对其他生物体的防御反应。PPI 网络显示，11 种抗病毒蛋白（AVPs）是关键基因。单细胞转录组数据集的 scGSEA 分析表明，这些关键基因在角质形成细胞中高度表达，尤其是在表皮上层角质形成细胞中。ISG15、MX1、IFI44L 和 IFI27 是表皮上层角质形成细胞中银屑病的特征基因。scWGCNA 显示，在绿松石模块中，三种细胞因子-IL36G、MIF 和 IL17RA-共表达。只有白细胞介素 36 伽马（IL36G）在整合数据集中与 AVPs 呈正相关。IL36G 和 AVPs 在大量表皮上层角质形成细胞中共表达。此外，我们发现，在银屑病患者中，IL36G 和 4 种 AVPs 的表达水平与 PASI 评分呈正相关，并且在接受生物治疗时，这些水平显著降低，但在接受甲氨蝶呤治疗时没有降低。
IL36G 和抗病毒蛋白可能与银屑病的发病机制密切相关，它们可能代表银屑病发生和严重程度的新的候选分子标志物。
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