Department of Dermatology, Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
Eur Rev Med Pharmacol Sci. 2021 Feb;25(3):1436-1446. doi: 10.26355/eurrev_202102_24851.
Atopic eczema (AE) is a chronic relapsing inflammatory skin disease. This study aims to identify key genes related to the development of AE.
The GSE6012 dataset was obtained from the Gene Expression Omnibus (GEO) database. The limma package was used to analyze differentially expressed genes (DEGs). Then, the weighted gene co-expression network analysis (WGCNA) package was utilized to generate weighted correlation networks of up-and downregulated genes. Additionally, the WGCNA package was used for enrichment analyses to explore the underlying functions of DEGs in modules (weighted correlation sub-networks) significantly associated with AE.
A total of 515 DEGs were identified between lesional and non-lesional skin samples. For the upregulated genes, the blue module was found to have a significant positive correlation with AE. Importantly, small proline-rich protein 2C (SPRR2C) and defensin, beta 4A (DEFB4A) exhibited higher |log fold change (FC) values and were the key nodes of the network. Moreover, KEGG pathway analysis revealed that the upregulated genes in the blue module were primarily involved in cytokine-cytokine receptor interaction. Additionally, for the downregulated genes, the brown module was found to have a significant positive correlation with AE. Further, WNT inhibitory factor 1 (WIF1), cryptochrome 2 (CRY2), and keratin 19 (KRT19) had higher |log FC| values and were key nodes of the network.
SPRR2C, DEFB4A, WIF1, CRY2, KRT19 and cytokine-cytokine receptor interaction might be correlated with the development of AE.
特应性皮炎(AE)是一种慢性复发性炎症性皮肤病。本研究旨在鉴定与 AE 发展相关的关键基因。
从基因表达综合数据库(GEO)中获取 GSE6012 数据集。使用 limma 包分析差异表达基因(DEGs)。然后,使用加权基因共表达网络分析(WGCNA)包生成上调和下调基因的加权相关网络。此外,使用 WGCNA 包进行富集分析,以探讨与 AE 显著相关的模块(加权相关子网络)中 DEGs 的潜在功能。
在病变和非病变皮肤样本之间共鉴定出 515 个 DEGs。对于上调基因,发现蓝色模块与 AE 呈显著正相关。重要的是,富含脯氨酸的小蛋白 2C(SPRR2C)和防御素β 4A(DEFB4A)表现出更高的 |log 倍变化(FC)值,并且是网络的关键节点。此外,KEGG 途径分析表明,蓝色模块中上调的基因主要参与细胞因子-细胞因子受体相互作用。此外,对于下调基因,发现棕色模块与 AE 呈显著正相关。此外,WNT 抑制因子 1(WIF1)、隐色素 2(CRY2)和角蛋白 19(KRT19)具有更高的 |log FC| 值,并且是网络的关键节点。
SPRR2C、DEFB4A、WIF1、CRY2、KRT19 和细胞因子-细胞因子受体相互作用可能与 AE 的发展相关。