Department of Molecular and Cellular Engineering, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj (Allahabad), India.
ICMR-AIIMS Computational Genomics Centre (ISRM) Division- Indian Council of Medical Research, New Delhi, India.
Curr Pharm Des. 2020;26(29):3619-3630. doi: 10.2174/1381612826666200311130133.
Psoriasis is a chronic immune mediated skin disorder with global prevalence of 0.2- 11.4%. Despite rare mortality, the severity of the disease could be understood by the accompanying comorbidities, that has even led to psychological problems among several patients. The cause and the disease mechanism still remain elusive.
To identify potential therapeutic targets and affecting pathways for better insight of the disease pathogenesis.
The gene expression profile GSE13355 and GSE14905 were retrieved from NCBI, Gene Expression Omnibus database. The GEO profiles were integrated and the DEGs of lesional and non-lesional psoriasis skin were identified using the affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes pathways of the DEGs were analyzed using clusterProfiler. Cytoscape, V3.7.1 was utilized to construct protein interaction network and analyze the interactome map of candidate proteins encoded in DEGs. Functionally relevant clusters were detected through Cytohubba and MCODE.
A total of 1013 genes were differentially expressed in lesional skin of which 557 were upregulated and 456 were downregulated. Seven dysregulated genes were extracted in non-lesional skin. The disease gene network of these DEGs revealed 75 newly identified differentially expressed gene that might have a role in development and progression of the disease. GO analysis revealed keratinocyte differentiation and positive regulation of cytokine production to be the most enriched biological process and molecular function. Cytokines -cytokine receptor was the most enriched pathways. Among 1013 identified DEGs in lesional group, 36 DEGs were found to have altered genetic signature including IL1B and STAT3 which are also reported as hub genes. CCNB1, CCNA2, CDK1, IL1B, CXCL8, MKI 67, ESR1, UBE2C, STAT1 and STAT3 were top 10 hub gene.
The hub genes, genomic altered DEGs and other newly identified differentially dysregulated genes would improve our understanding of psoriasis pathogenesis, moreover, the hub genes could be explored as potential therapeutic targets for psoriasis.
银屑病是一种慢性免疫介导的皮肤疾病,全球患病率为 0.2-11.4%。尽管死亡率较低,但该疾病的严重程度可以通过伴随的合并症来理解,这甚至导致了一些患者的心理问题。其病因和疾病机制仍不清楚。
确定潜在的治疗靶点和影响途径,以更好地了解疾病的发病机制。
从 NCBI 的 Gene Expression Omnibus 数据库中检索到 GSE13355 和 GSE14905 基因表达谱。使用 R 软件中的 affy 包整合 GEO 谱,鉴定皮损和非皮损银屑病皮肤的差异表达基因。使用 clusterProfiler 分析差异表达基因的京都基因与基因组百科全书通路。使用 Cytoscape,V3.7.1 构建蛋白质相互作用网络,并分析差异表达基因编码的候选蛋白的互作图谱。通过 Cytohubba 和 MCODE 检测功能相关簇。
皮损皮肤中共有 1013 个基因差异表达,其中 557 个上调,456 个下调。非皮损皮肤中提取出 7 个差异表达基因。这些差异表达基因的疾病基因网络揭示了 75 个新的差异表达基因,这些基因可能在疾病的发展和进展中发挥作用。GO 分析显示,角质形成细胞分化和细胞因子产生的正调控是最丰富的生物学过程和分子功能。细胞因子-细胞因子受体是最丰富的通路。在皮损组中鉴定的 1013 个差异表达基因中,有 36 个差异表达基因的遗传特征发生了改变,包括 IL1B 和 STAT3,这两个基因也被报道为枢纽基因。CCNB1、CCNA2、CDK1、IL1B、CXCL8、MKI67、ESR1、UBE2C、STAT1 和 STAT3 是前 10 个枢纽基因。
枢纽基因、基因组改变的差异表达基因和其他新鉴定的差异失调基因将提高我们对银屑病发病机制的理解,此外,枢纽基因可以作为银屑病的潜在治疗靶点进行探索。