Song Jian-Kun, Zhang Ying, Fei Xiao-Ya, Chen Yi-Ran, Luo Ying, Jiang Jing-Si, Ru Yi, Xiang Yan-Wei, Li Bin, Luo Yue, Kuai Le
Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Front Genet. 2022 Aug 30;13:850108. doi: 10.3389/fgene.2022.850108. eCollection 2022.
Psoriasis is a chronic and immune-mediated skin disorder that currently has no cure. Pyroptosis has been proved to be involved in the pathogenesis and progression of psoriasis. However, the role pyroptosis plays in psoriasis remains elusive. RNA-sequencing data of psoriasis patients were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed pyroptosis-related genes (PRGs) between psoriasis patients and normal individuals were obtained. A principal component analysis (PCA) was conducted to determine whether PRGs could be used to distinguish the samples. PRG and immune cell correlation was also investigated. Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. Consensus clustering analysis was used to investigate whether there was a difference in biological functions within PRG-based subtypes. Finally, the expression of the kernel PRGs were validated by qRT-PCR We identified a total of 39 PRGs, which could distinguish psoriasis samples from normal samples. The process of T cell CD4 memory activated and mast cells resting were correlated with PRGs. Ten PRGs, IL-1β, AIM2, CASP5, DHX9, CASP4, CYCS, CASP1, GZMB, CHMP2B, and CASP8, were subsequently screened using a random forest diagnostic model. ROC analysis revealed that our model has good diagnostic performance in both internal validation (area under the curve [AUC] = 0.930 [95% CI 0.877-0.984]) and external validation (mean AUC = 0.852). PRG subtypes indicated differences in metabolic processes and the MAPK signaling pathway. Finally, the qRT-PCR results demonstrated the apparent dysregulation of PRGs in psoriasis, especially AIM2 and GZMB. Pyroptosis may play a crucial role in psoriasis and could provide new insights into the diagnosis and underlying mechanisms of psoriasis.
银屑病是一种慢性免疫介导的皮肤疾病，目前无法治愈。已证明细胞焦亡参与银屑病的发病机制和进展。然而，细胞焦亡在银屑病中所起的作用仍不清楚。从基因表达综合数据库（GEO）中获取银屑病患者的RNA测序数据，得到银屑病患者与正常个体之间差异表达的细胞焦亡相关基因（PRG）。进行主成分分析（PCA）以确定PRG是否可用于区分样本。还研究了PRG与免疫细胞的相关性。随后，使用随机森林算法（ntree = 400）构建了一种包含用于银屑病的PRG的新型诊断模型。采用受试者工作特征（ROC）分析通过内部和外部验证来评估分类性能。共识聚类分析用于研究基于PRG的亚型在生物学功能上是否存在差异。最后，通过qRT-PCR验证核心PRG的表达。我们共鉴定出39个PRG，它们可以区分银屑病样本和正常样本。T细胞CD4记忆激活和肥大细胞静止过程与PRG相关。随后使用随机森林诊断模型筛选出10个PRG，即白细胞介素-1β（IL-1β）、黑素瘤缺乏因子2（AIM2）、半胱天冬酶5（CASP5）、解旋酶9（DHX9）、半胱天冬酶4（CASP4）、细胞色素c（CYCS）、半胱天冬酶1（CASP1）、颗粒酶B（GZMB）、染色质修饰蛋白2B（CHMP2B）和半胱天冬酶8（CASP8）。ROC分析表明，我们的模型在内部验证（曲线下面积[AUC] = 0.930 [95%可信区间0.877 - 0.984]）和外部验证（平均AUC = 0.852）中均具有良好的诊断性能。PRG亚型在代谢过程和丝裂原活化蛋白激酶（MAPK）信号通路方面存在差异。最后，qRT-PCR结果表明PRG在银屑病中明显失调，尤其是AIM2和GZMB。细胞焦亡可能在银屑病中起关键作用，并可为银屑病的诊断和潜在机制提供新的见解。
