{"title":"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","authors":"Swetha Sunkar, K. Namratha, Desam Neeharika","doi":"10.1016/j.mgene.2022.101015","DOIUrl":null,"url":null,"abstract":"<div><p>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 <em>P</em>-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 <em>POSTN, COL1A2, COL1A1, BMP1, MXRA5, MMP13 and SERPINF1</em>. 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.</p></div>","PeriodicalId":38190,"journal":{"name":"Meta Gene","volume":"31 ","pages":"Article 101015"},"PeriodicalIF":0.8000,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Identification of hub genes associated with human osteoarthritis cartilage: An in silico approach\",\"authors\":\"Swetha Sunkar, K. Namratha, Desam Neeharika\",\"doi\":\"10.1016/j.mgene.2022.101015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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 <em>P</em>-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 <em>POSTN, COL1A2, COL1A1, BMP1, MXRA5, MMP13 and SERPINF1</em>. 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.</p></div>\",\"PeriodicalId\":38190,\"journal\":{\"name\":\"Meta Gene\",\"volume\":\"31 \",\"pages\":\"Article 101015\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meta Gene\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214540022000068\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meta Gene","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214540022000068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
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.
Meta GeneBiochemistry, 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.