通过生物信息学分析鉴定特应性皮炎的关键基因和 microRNAs 并进行相互作用分析。

Identification and interaction analysis of key genes and microRNAs in atopic dermatitis by bioinformatics analysis.

机构信息

Department of Dermatology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China.

Beijing ZhiYuanZhongHe Technology Co. Ltd., Beijing, China.

出版信息

Clin Exp Dermatol. 2019 Apr;44(3):257-264. doi: 10.1111/ced.13691. Epub 2018 Jul 3.

DOI:10.1111/ced.13691

PMID:29974487

Abstract

BACKGROUND

Atopic dermatitis (AD) is a skin disease that carries a major health burden, but the exact mechanism of the disease is not yet known.

AIM

To identify the key genes and micro (mi)RNAs in AD, and to explore their potential molecular mechanisms.

METHODS

From the Gene Expression Omnibus (GEO) database, we downloaded microarray data for GSE32924 (mRNA profile) and GSE31408 (miRNA profile), which were analysed using GEO2R. Functional and pathway enrichment analyses were performed using the DAVID database, and the protein-protein interaction network was constructed with Cytoscape software. In addition, targets of differentially expressed miRNAs (DEMs) were predicted by the online resource miRDB.

RESULTS

In total, 328 differentially expressed genes (DEGs) were identified, including 121 upregulated and 207 downregulated genes. Gene Ontology analyses showed that upregulated genes were significantly enriched in immune responses, while downregulated genes were mainly involved in epidermis development. In addition, we identified three DEMs, all of which were downregulated. Hsa-let-7a-5p may target CCR7, and hsa-miR-26a-5p probably targets HAS3.

CONCLUSIONS

We identified lists of DEGs and DEMs in AD. Bioinformatics and interaction analysis may provide new clues for further studies of AD.

摘要

背景

特应性皮炎（AD）是一种严重影响健康的皮肤病，但该病的确切发病机制尚不清楚。

目的

鉴定 AD 中的关键基因和微小 RNA（miRNA），并探讨其潜在的分子机制。

方法

从基因表达综合数据库（GEO）中下载 GSE32924（mRNA 谱）和 GSE31408（miRNA 谱）的微阵列数据集，使用 GEO2R 进行分析。使用 DAVID 数据库进行功能和通路富集分析，使用 Cytoscape 软件构建蛋白质-蛋白质相互作用网络。此外，通过在线资源 miRDB 预测差异表达 miRNA（DEM）的靶基因。

结果

共鉴定出 328 个差异表达基因（DEG），包括 121 个上调基因和 207 个下调基因。基因本体论分析表明，上调基因在免疫反应中显著富集，而下调基因主要参与表皮发育。此外，我们鉴定出 3 个下调的 DEM，均下调。Hsa-let-7a-5p 可能靶向 CCR7，而 hsa-miR-26a-5p 可能靶向 HAS3。