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Bioinformatics Analysis of the Molecular Mechanism and Potential Treatment Target of Ankylosing Spondylitis
Computational and Mathematical Methods in Medicine ( IF 2.809 ) Pub Date : 2021-07-22 , DOI: 10.1155/2021/7471291
Fanyan Meng 1 , Ningna Du 1 , Daoming Xu 1 , Li Kuai 1 , Lanying Liu 1 , Minning Xiu 2
Affiliation  

Ankylosing spondylitis (AS) is an autoimmune disease that mainly affects the spinal joints, sacroiliac joints, and adjacent soft tissues. We conducted bioinformatics analysis to explore the molecular mechanism related to AS pathogenesis and uncover novel potential molecular targets for the treatment of AS. The profiles of GSE25101, containing gene expression data extracted from the blood of 16 AS patients and 16 matched controls, were acquired from the Gene Expression Omnibus (GEO) database. The background correction and standardization were carried out utilizing the transcript per million (TPM) method. After analysis of AS patients and the normal groups, we identified 199 differentially expressed genes (DEGs) with upregulation and 121 DEGs with downregulation by the limma R package. The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) biological process enrichment analysis revealed that the DEGs with upregulation were mainly associated with spliceosome, ribosome, RNA-catabolic process, electron transport chain, etc. And the DEGs with downregulation primarily participated in T cell-associated pathways and processes. After analysis of the protein-protein interaction (PPI) network, our data revealed that the hub genes, comprising MRPL13, MRPL22, LSM3, COX7A2, COX7C, EP300, PTPRC, and CD4, could be the treatment targets in AS. Our data furnish new hints to uncover the features of AS and explore more promising treatment targets towards AS.

中文翻译:

强直性脊柱炎分子机制及潜在治疗靶点的生物信息学分析

强直性脊柱炎(AS)是一种主要累及脊柱关节、骶髂关节及邻近软组织的自身免疫性疾病。我们进行了生物信息学分析,以探索与 AS 发病机制相关的分子机制,并发现治疗 AS 的新的潜在分子靶点。GSE25101 的配置文件包含从 16 名 AS 患者和 16 名匹配对照的血液中提取的基因表达数据,是从基因表达综合 (GEO) 数据库中获取的。使用百万分之转录本 (TPM) 方法进行背景校正和标准化。在对 AS 患者和正常组进行分析后,我们通过 limma R 包确定了 199 个具有上调的差异表达基因(DEG)和 121 个具有下调的差异表达基因(DEG)。京都基因与基因组百科全书(KEGG)通路和基因本体论(GO)生物过程富集分析结果显示,上调的DEGs主要与剪接体、核糖体、RNA分解代谢过程、电子传递链等相关。下调的 DEGs 主要参与 T 细胞相关通路和过程。在对蛋白质-蛋白质相互作用 (PPI) 网络进行分析后,我们的数据显示,包含 MRPL13、MRPL22、LSM3、COX7A2、COX7C、EP300、PTPRC 和 CD4 的中枢基因可能是 AS 的治疗靶点。我们的数据为揭示 AS 的特征和探索更有希望的 AS 治疗目标提供了新的线索。
更新日期:2021-07-22
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