鉴定与人类骨关节炎软骨相关的枢纽基因:一种计算机方法

IF 0.8 Q4 GENETICS & HEREDITY
Swetha Sunkar, K. Namratha, Desam Neeharika
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引用次数: 1

摘要

骨关节炎是一种常见的骨科疾病,是世界范围内发病率和致残率最高的疾病之一;然而,对其发病机制和诊断方法的研究仍然有限。本研究的重点是分析微阵列数据集,以阐明与骨关节炎相关的枢纽基因和途径。从GEO数据库(GSE169077)中检索基因表达数据,利用GEO2R工具根据调整后的p值和log2FC值测定差异表达基因,发现27个基因显著,其中9个基因上调,18个基因下调。随后进行基因富集分析,确定相关的基因本体术语和途径。利用STRING数据库构建了包含15个节点和22条边的Protein-Protein网络,并导出到Cytoscape 3.8中进行枢纽基因预测。中心基因为POSTN、COL1A2、COL1A1、BMP1、MXRA5、MMP13和serinf1。所鉴定的枢纽基因不仅与骨相关疾病有关,而且很少与其他疾病有关。因此,针对这些基因的疾病管理可能是骨关节炎的一个可行的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of hub genes associated with human osteoarthritis cartilage: An in silico approach

Osteoarthritis is a common orthopedic disease among the greatest causes of morbidity and disability worldwide; however, research on its pathogenesis and diagnostic methods remains limited. The present study focuses on analyzing the microarray dataset to elucidate the hub genes and pathways related to the osteoarthritis. The gene expression data was retrieved from GEO database (GSE169077) and differentially expressed genes were determined using GEO2R tool based on adjusted P-value and log2FC values based on which 27 genes were found to be significant of which 9 genes were up-regulated while 18 genes were down-regulated. This was followed by gene enrichment analysis identify the related Gene Ontology terms and pathways. The Protein-Protein Network is constructed with 15 nodes and 22 edges using STRING database and then exported to Cytoscape 3.8 to predict the hub genes. The hub genes identified are POSTN, COL1A2, COL1A1, BMP1, MXRA5, MMP13 and SERPINF1. The hub genes identified were not only found to be associated with bone related disorders but also few were involved in other diseases. Therefore targeting these genes for disease management could be a viable option in osteoarthritis.

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来源期刊
Meta Gene
Meta Gene Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
1.10
自引率
0.00%
发文量
20
期刊介绍: Meta Gene publishes meta-analysis, polymorphism and population study papers that are relevant to both human and non-human species. Examples include but are not limited to: (Relevant to human specimens): 1Meta-Analysis Papers - statistical reviews of the published literature of human genetic variation (typically linked to medical conditionals and/or congenital diseases) 2Genome Wide Association Studies (GWAS) - examination of large patient cohorts to identify common genetic factors that influence health and disease 3Human Genetics Papers - original studies describing new data on genetic variation in smaller patient populations 4Genetic Case Reports - short communications describing novel and in formative genetic mutations or chromosomal aberrations (e.g., probands) in very small demographic groups (e.g., family or unique ethnic group). (Relevant to non-human specimens): 1Small Genome Papers - Analysis of genetic variation in organelle genomes (e.g., mitochondrial DNA) 2Microbiota Papers - Analysis of microbiological variation through analysis of DNA sequencing in different biological environments 3Ecological Diversity Papers - Geographical distribution of genetic diversity of zoological or botanical species.
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