Table_4_IL36G is associated with cutaneous antiviral competence in psoriasis.xlsx

BackgroundPsoriasis 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.
MethodsThe expression profiles of genes from psoriatic lesion samples and skin samples from healthy controls were integrated via 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 via 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.
ResultsWe 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.
ConclusionIL36G 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.

背景 银屑病是一种常见的炎症性皮肤病，对患者的身心健康均产生显著影响。然而，银屑病的病因及潜在分子机制目前仍未完全阐明。
方法 本研究通过sva软件包整合银屑病皮损样本与健康对照皮肤样本的基因表达谱，借助limma包筛选银屑病与健康皮肤间的差异表达基因（differentially expressed genes, DEGs）。进一步利用Clusterprofiler包对DEGs开展基因本体（Gene Ontology, GO）及京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路富集分析。随后构建DEGs的蛋白-蛋白相互作用（protein-protein interaction, PPI）网络以识别核心基因（hub genes）。通过irGSEA工具对单细胞RNA测序数据集开展单细胞基因集富集分析（single-cell Gene Set Enrichment Analysis, scGESA）。为筛选与核心基因表达相关的细胞因子，本研究采用单细胞加权基因共表达网络分析（single-cell weighted gene co-expression network analysis, scWGCNA）构建基因共表达网络。此外，将在基底层上层角质形成细胞中发现的银屑病特征基因与核心基因取交集，随后在整合数据集中分析交集基因与细胞因子的表达水平。之后利用其他数据集探究交集基因在生物制剂治疗过程中的表达变化，并探讨交集基因与银屑病面积与严重性指数（Psoriasis Area and Severity Index, PASI）评分的相关性。
结果 本研究共筛选得到148个银屑病与健康样本间的差异表达基因。GO与KEGG通路富集分析结果显示，DEGs主要参与对其他生物的防御反应。PPI网络分析表明，11种抗病毒蛋白（antiviral proteins, AVPs）为核心基因。单细胞转录组数据集的scGESA分析显示，上述核心基因在角质形成细胞中高表达，尤其在基底层上层角质形成细胞中富集。ISG15、MX1、IFI44L及IFI27为基底层上层角质形成细胞中的银屑病特征基因。scWGCNA分析显示，IL36G、MIF及IL17RA三种细胞因子在turquoise模块中存在共表达。在整合数据集中，仅白细胞介素-36γ（interleukin-36 gamma, IL36G）与抗病毒蛋白呈正相关。IL36G与抗病毒蛋白在大量基底层上层角质形成细胞中存在共表达。进一步分析发现，IL36G及上述4种抗病毒蛋白的表达水平与银屑病患者的PASI评分呈正相关，且在生物制剂治疗过程中其表达水平显著下调，但甲氨蝶呤治疗未产生此类变化。
结论 IL36G与抗病毒蛋白可能与银屑病的发病机制密切相关，或可作为反映银屑病发生及严重程度的新型候选分子标志物。