Xiang Hong, Yang Xiao-Hu, Ai Liang-Xia, Pan Yan-Ping, Hu Yong
Institute for Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Yi Chuan. 2020 Feb 20;42(2):172-182. doi: 10.16288/j.yczz.19-214.
The molecular mechanism of alopecia areata (AA) is still elusive and here we utilized bioinformatics methods to analyze AA-related differentially expressed genes. In this study, GSE45512 and GSE45513 were downloaded from the NCBI sub-database Gene Expression Omnibus (GEO). The gene expressions of AA and normal samples were analyzed using the R package limma, which showed significant differences between AA and normal samples in two species. These genes were subject to functional annotation and protein interaction networks. At the same time, gene set enrichment analysis was conducted for all differentially expressed genes. The study revealed that a total of 225 differentially expressed genes were screened from human AA samples, and a total of 337 differentially expressed genes were screened from spontaneous AA skin samples in C3H/HeJ mice. There are 23 differentially expressed genes in the two species. GO and protein interaction network analysis shown gene enrichment in immune-related functions, and these proteins interact with each other. Gene set enrichment analysis showed that differential genes from both species were significantly enriched to chemokine signaling pathways, cytokine-cytokine receptor interactions, staphylococcus aureus infection, and antigen processing and presentation. Moreover, the human down-regulated differential gene not only maps to the alopecia in human phenotype ontology, but also maps to the pathologically relevant phenotype of the skin appendage. In brief, 23 significant differentially expressed genes were screened out coexisting in AA human and mouse by bioinformatics methods. In addition, the result demonstrated that AA is closely related to the immune process and skin appendage lesions. These results provide new ideas for the diagnosis and treatment of AA.
斑秃（AA）的分子机制仍不清楚，在此我们利用生物信息学方法分析与AA相关的差异表达基因。在本研究中，从NCBI子数据库基因表达综合数据库（GEO）下载了GSE45512和GSE45513。使用R包limma分析AA和正常样本的基因表达，结果显示在两个物种中AA和正常样本之间存在显著差异。对这些基因进行功能注释和蛋白质相互作用网络分析。同时，对所有差异表达基因进行基因集富集分析。研究发现，从人类AA样本中筛选出总共225个差异表达基因，从C3H/HeJ小鼠的自发性AA皮肤样本中筛选出总共337个差异表达基因。两个物种中有23个差异表达基因。GO和蛋白质相互作用网络分析显示基因在免疫相关功能中富集，并且这些蛋白质相互作用。基因集富集分析表明，两个物种的差异基因均显著富集于趋化因子信号通路、细胞因子-细胞因子受体相互作用、金黄色葡萄球菌感染以及抗原加工和呈递。此外，人类下调的差异基因不仅映射到人类表型本体中的脱发，还映射到皮肤附属器的病理相关表型。简而言之，通过生物信息学方法筛选出23个在人类和小鼠AA中共存的显著差异表达基因。此外，结果表明AA与免疫过程和皮肤附属器病变密切相关。这些结果为AA的诊断和治疗提供了新思路。
