Doctor Class of 2021, Jiangxi University of Chinese Medicine, Nanchang 330000, Jiangxi, China.
Department of Dermatology, Shanghai Hudong Hospital, Shanghai 200000, China.
J Healthc Eng. 2022 Jan 4;2022:8745722. doi: 10.1155/2022/8745722. eCollection 2022.
Allergic dermatitis (AD) is a common and burdensome inflammatory skin disease, and diagnosis is challenging. This study was conducted to identify candidate genes for AD diagnosis and underlying molecular mechanisms. Gene expression profiles were obtained from datasets GSE121212, GSE130588, and GSE157194. Use differential analysis to identify differentially expressed genes (DEGs) between AD and control. Use enrichment analysis to identify potential molecular dysregulation mechanisms. Comprehensive least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operator characteristic (ROC) curve, and logistic regression analysis are used to identify candidate genes. In addition, ssGSEA and ImmPort database were used to identify AD-related immune response abnormalities. In this study, a total of 60 common genes were identified. Enrichment analysis found that these genes are mainly involved in Th17 cell immune and complement and coagulation cascades. LASSO regression analysis identified 18 feature genes, and screened genes with AUC >0.75 were selected as candidate genes. Finally, PLA2G4D, IFI6, AGR3, IGFL1, SPRR3, ATP13A5, SERPINB13, KRT16, HAS3, and CH25H were recognized as candidate genes and may be able to diagnose AD. PLA2G4D, CH25H, and IFI6 may be risk factors for AD based on logistic analysis. Furthermore, we identified the abnormalities of immune response activation in AD patients. Interestingly, PLA2G4D, CH25H, and IFI6 had positive correlations with immune cells and signaling pathways. PLA2G4D, CH25H, and IFI6 may be candidate diagnostic genes for AD. This may be related to their promotion of abnormal immune activation, especially Th17 cell immune.
变应性皮炎（AD）是一种常见且负担沉重的炎症性皮肤病，其诊断具有挑战性。本研究旨在鉴定 AD 诊断的候选基因和潜在的分子机制。从数据集 GSE121212、GSE130588 和 GSE157194 中获取基因表达谱。使用差异分析鉴定 AD 与对照之间的差异表达基因（DEG）。使用富集分析鉴定潜在的分子失调机制。综合最小绝对收缩和选择算子（LASSO）逻辑回归、接收者操作特征（ROC）曲线和逻辑回归分析用于鉴定候选基因。此外，还使用 ssGSEA 和 ImmPort 数据库来鉴定 AD 相关的免疫反应异常。在这项研究中，共鉴定出 60 个共同基因。富集分析发现，这些基因主要参与 Th17 细胞免疫和补体与凝血级联反应。LASSO 回归分析鉴定出 18 个特征基因，筛选出 AUC＞0.75 的基因作为候选基因。最后，鉴定出 PLA2G4D、IFI6、AGR3、IGFL1、SPRR3、ATP13A5、SERPINB13、KRT16、HAS3 和 CH25H 作为候选基因，它们可能能够诊断 AD。基于逻辑分析，PLA2G4D、CH25H 和 IFI6 可能是 AD 的风险因素。此外，我们还鉴定出 AD 患者免疫反应激活的异常。有趣的是，PLA2G4D、CH25H 和 IFI6 与免疫细胞和信号通路呈正相关。PLA2G4D、CH25H 和 IFI6 可能是 AD 的候选诊断基因。这可能与其促进异常免疫激活有关，尤其是 Th17 细胞免疫。
