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唐 欣,陈茉弦,孟繁媛,刘 垚,赵洪波.脑性瘫痪儿童肌肉痉挛相关基因的生物信息学分析[J].中国康复医学杂志,2018,(5):499~505
脑性瘫痪儿童肌肉痉挛相关基因的生物信息学分析    点此下载全文
唐 欣  陈茉弦  孟繁媛  刘 垚  赵洪波
昆明医科大学康复学院,昆明,650500
基金项目:云南省卫生科技计划项目(内设机构)(2017NS310)
DOI:
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摘要:
      摘要 目的:对儿童脑瘫肌肉痉挛相关基因进行生物信息学分析,探索脑瘫肌肉痉挛发生的分子机制。 方法:在GEO数据库下载脑瘫肌肉痉挛的基因表达谱芯片数据GSE31243,用R软件的limma包筛选差异表达基因,筛选标准为FDR<0.05及|log FC|>1;使用clusterProfiler软件包进行GO富集分析和KEGG通路分析;通过STRING数据库进行差异表达基因对应的蛋白互作网络分析。 结果:共筛选得到85个差异表达基因,包括41个上调基因和44个下调基因;GO功能富集分析发现生物学过程主要集中在细胞外基质组织,胶原纤维组织,骨骼系统发育和细胞对氨基酸刺激的反应等功能上;差异通路主要有ECM受体相互作用,蛋白质消化吸收,粘着斑、松弛素信号通路和PI3K-Akt信号通路等;蛋白互作网络分析发现,COL1A1、COL3A1、COL1A2、COL4A1和LUM等蛋白有较高的degree值。 结论:大多数表达差异的基因与细胞外基质有关,表明细胞外基质产物的增加与脑瘫肌肉痉挛相关,COL1A1,COL3A1、COL1A2、COL4A1和LUM等基因可能在脑瘫肌肉痉挛中起重要作用。基于生物信息学分析有助于进一步地了解脑瘫儿童肌肉痉挛的分子机制,从而为该病的治疗提供理论基础。
关键词:脑性瘫痪  肌肉痉挛  表达谱  生物信息学  机制
Bioinformatics analysis of muscle spasticity related genes in children with cerebral palsy    Download Fulltext
School of Rehabilitation, Kunming Medical University, Kunming, 650500
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Abstract:
      Abstract Objective: To explore the molecular mechanism of the muscle spasticity related genes in children with cerebral palsy by bioinformatics analysis. Method: Gene expression profile data GSE31243 about muscle spasticity in cerebral palsy were downloaded from Gene Expression Ominibus (GEO). Limma package was used to detect differentially expressed genes (DEGs) and the criteria were FDR<0.05 and |log fold change|>1. GO functional enrichment analysis and KEGG pathway analysis were performed using the clusterProfiler package. STRING database was used to construct protein-protein interaction (PPI) network. Result: A total of 85 differentially expressed genes were screened, including 41 up-regulated genes and 44 down-regulated genes. GO function analysis revealed that the genes’ functions were mainly involved in extracellular matrix organization, collagen fibril organization, skeletal system development and response to amino acid. KEGG pathway analysis suggested that the main metabolic pathways of these genes were ECM-receptor interaction,protein digestion and absorption,focal adhesion,relaxin signaling pathway and PI3K-Akt signaling pathway. PPI network analysis showed that COL1A1,COL3A1, COL1A2, COL4A1 and LUM had higher degree. Conclusion: Most of the genes that differentially expressed are related with extracellular matrix indicating the matrix plays an important role in muscle from cerebral palsy. COL1A1, COL3A1, COL1A2, COL4A1 and LUM may play key roles in muscle spasticity with cerebral palsy. Based on bioinformatics analysis can help to further understand the molecular mechanism of muscle spasticity in cerebral palsy, so as to provide a theoretical basis for the treatment of the disease.
Keywords:cerebral palsy  muscle spasticity  gene expression profile  bioinformatics  mechanism
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