乙肝病毒相关急性肝衰竭患者Hub基因的鉴定及其潜在分子机制

IF 1.7 4区 生物学 Q4 EVOLUTIONARY BIOLOGY
Evolutionary Bioinformatics Pub Date : 2020-10-10 eCollection Date: 2020-01-01 DOI:10.1177/1176934320943901
Ying Sun, Haitao Yu, Fangfang Li, Liqiang Lan, Daxin He, Haijun Zhao, Dachuan Qi
{"title":"乙肝病毒相关急性肝衰竭患者Hub基因的鉴定及其潜在分子机制","authors":"Ying Sun,&nbsp;Haitao Yu,&nbsp;Fangfang Li,&nbsp;Liqiang Lan,&nbsp;Daxin He,&nbsp;Haijun Zhao,&nbsp;Dachuan Qi","doi":"10.1177/1176934320943901","DOIUrl":null,"url":null,"abstract":"<p><p>Hepatitis B virus (HBV) infection is a major cause of acute liver failure (ALF) in China, and mortality rates are high among patients who do not receive a matched liver transplant. This study aimed to determine potential mechanisms involved in HBV-ALF pathogenesis. Gene expression profiles under access numbers GSE38941 and GSE14668 were downloaded from the Gene Expression Omnibus database, including cohorts of HBV-ALF liver tissue and normal samples. Differentially expressed genes (DEGs) with false discovery rates (FDR) <0.05 and |log<sub>2</sub>(fold change)| >1 as thresholds were screened using the Limma package. Gene modules associated with stable disease were mined using weighed gene co-expression network analysis (WGCNA). A co-expression network was constructed and DEGs were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A gene-based network was constructed to explore major factors associated with disease progression. We identified 2238 overlapping DEGs as crucial gene cohorts in ALF development. Based on a WGCNA algorithm, 10 modules (modules 1-10) were obtained that ranged from 75 to 1078 genes per module. Cyclin-dependent kinase 1 (<i>CDK1</i>), cyclin B1 (<i>CCNB1</i>), and cell-division cycle protein 20 (<i>CDC20</i>) hub genes were screened using the co-expression network. Furthermore, 17 GO terms and 6 KEGG pathways were identified, such as cell division, immune response process, and antigen processing and presentation. Two overlapping signaling pathways that are crucial factors in HBV-ALF were screened using the Comprehensive Toxicogenomics Database (CTD). Several candidate genes including <i>HLA-E, B2M, HLA-DPA1</i>, and <i>SYK</i> were associated with HBV-ALF progression. Natural killer cell-mediated cytotoxicity and antigen presentation contributed to the progression of HBV-ALF. The <i>HLA-E, B2M, HLA-DPA1</i>, and <i>SYK</i> genes play critical roles in the pathogenesis and development of HBV-ALF.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"16 ","pages":"1176934320943901"},"PeriodicalIF":1.7000,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1176934320943901","citationCount":"2","resultStr":"{\"title\":\"Identification of Hub Genes and Potential Molecular Mechanisms in Patients with HBV-Associated Acute Liver Failure.\",\"authors\":\"Ying Sun,&nbsp;Haitao Yu,&nbsp;Fangfang Li,&nbsp;Liqiang Lan,&nbsp;Daxin He,&nbsp;Haijun Zhao,&nbsp;Dachuan Qi\",\"doi\":\"10.1177/1176934320943901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Hepatitis B virus (HBV) infection is a major cause of acute liver failure (ALF) in China, and mortality rates are high among patients who do not receive a matched liver transplant. This study aimed to determine potential mechanisms involved in HBV-ALF pathogenesis. Gene expression profiles under access numbers GSE38941 and GSE14668 were downloaded from the Gene Expression Omnibus database, including cohorts of HBV-ALF liver tissue and normal samples. Differentially expressed genes (DEGs) with false discovery rates (FDR) <0.05 and |log<sub>2</sub>(fold change)| >1 as thresholds were screened using the Limma package. Gene modules associated with stable disease were mined using weighed gene co-expression network analysis (WGCNA). A co-expression network was constructed and DEGs were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A gene-based network was constructed to explore major factors associated with disease progression. We identified 2238 overlapping DEGs as crucial gene cohorts in ALF development. Based on a WGCNA algorithm, 10 modules (modules 1-10) were obtained that ranged from 75 to 1078 genes per module. Cyclin-dependent kinase 1 (<i>CDK1</i>), cyclin B1 (<i>CCNB1</i>), and cell-division cycle protein 20 (<i>CDC20</i>) hub genes were screened using the co-expression network. Furthermore, 17 GO terms and 6 KEGG pathways were identified, such as cell division, immune response process, and antigen processing and presentation. Two overlapping signaling pathways that are crucial factors in HBV-ALF were screened using the Comprehensive Toxicogenomics Database (CTD). Several candidate genes including <i>HLA-E, B2M, HLA-DPA1</i>, and <i>SYK</i> were associated with HBV-ALF progression. Natural killer cell-mediated cytotoxicity and antigen presentation contributed to the progression of HBV-ALF. The <i>HLA-E, B2M, HLA-DPA1</i>, and <i>SYK</i> genes play critical roles in the pathogenesis and development of HBV-ALF.</p>\",\"PeriodicalId\":50472,\"journal\":{\"name\":\"Evolutionary Bioinformatics\",\"volume\":\"16 \",\"pages\":\"1176934320943901\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2020-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/1176934320943901\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Evolutionary Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1177/1176934320943901\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q4\",\"JCRName\":\"EVOLUTIONARY BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolutionary Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1177/1176934320943901","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"EVOLUTIONARY BIOLOGY","Score":null,"Total":0}
引用次数: 2

摘要

乙型肝炎病毒(HBV)感染是中国急性肝衰竭(ALF)的主要原因,未接受匹配肝移植的患者死亡率很高。本研究旨在确定HBV-ALF发病机制的潜在机制。从Gene expression Omnibus数据库下载访问号为GSE38941和GSE14668的基因表达谱,包括HBV-ALF肝组织和正常样本的队列。使用Limma软件包筛选假发现率(FDR) 2(fold change)| >1为阈值的差异表达基因(DEGs)。使用加权基因共表达网络分析(WGCNA)挖掘与稳定性疾病相关的基因模块。构建共表达网络,并利用基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析对基因序列进行分析。构建了一个基于基因的网络来探索与疾病进展相关的主要因素。我们确定了2238个重叠的deg作为ALF发展的关键基因群。基于WGCNA算法,得到10个模块(模块1 ~ 10),每个模块的基因数量在75 ~ 1078个之间。利用共表达网络筛选细胞周期蛋白依赖性激酶1 (CDK1)、细胞周期蛋白B1 (CCNB1)和细胞分裂周期蛋白20 (CDC20)枢纽基因。此外,还鉴定了17个GO术语和6个KEGG途径,如细胞分裂、免疫反应过程和抗原加工和递呈。使用综合毒物基因组学数据库(CTD)筛选了HBV-ALF中至关重要的两个重叠信号通路。包括HLA-E、B2M、HLA-DPA1和SYK在内的几个候选基因与HBV-ALF进展相关。自然杀伤细胞介导的细胞毒性和抗原呈递促进了HBV-ALF的进展。HLA-E、B2M、HLA-DPA1和SYK基因在HBV-ALF的发病和发展中起关键作用。
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 and Potential Molecular Mechanisms in Patients with HBV-Associated Acute Liver Failure.

Identification of Hub Genes and Potential Molecular Mechanisms in Patients with HBV-Associated Acute Liver Failure.

Identification of Hub Genes and Potential Molecular Mechanisms in Patients with HBV-Associated Acute Liver Failure.

Identification of Hub Genes and Potential Molecular Mechanisms in Patients with HBV-Associated Acute Liver Failure.

Hepatitis B virus (HBV) infection is a major cause of acute liver failure (ALF) in China, and mortality rates are high among patients who do not receive a matched liver transplant. This study aimed to determine potential mechanisms involved in HBV-ALF pathogenesis. Gene expression profiles under access numbers GSE38941 and GSE14668 were downloaded from the Gene Expression Omnibus database, including cohorts of HBV-ALF liver tissue and normal samples. Differentially expressed genes (DEGs) with false discovery rates (FDR) <0.05 and |log2(fold change)| >1 as thresholds were screened using the Limma package. Gene modules associated with stable disease were mined using weighed gene co-expression network analysis (WGCNA). A co-expression network was constructed and DEGs were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A gene-based network was constructed to explore major factors associated with disease progression. We identified 2238 overlapping DEGs as crucial gene cohorts in ALF development. Based on a WGCNA algorithm, 10 modules (modules 1-10) were obtained that ranged from 75 to 1078 genes per module. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), and cell-division cycle protein 20 (CDC20) hub genes were screened using the co-expression network. Furthermore, 17 GO terms and 6 KEGG pathways were identified, such as cell division, immune response process, and antigen processing and presentation. Two overlapping signaling pathways that are crucial factors in HBV-ALF were screened using the Comprehensive Toxicogenomics Database (CTD). Several candidate genes including HLA-E, B2M, HLA-DPA1, and SYK were associated with HBV-ALF progression. Natural killer cell-mediated cytotoxicity and antigen presentation contributed to the progression of HBV-ALF. The HLA-E, B2M, HLA-DPA1, and SYK genes play critical roles in the pathogenesis and development of HBV-ALF.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Evolutionary Bioinformatics
Evolutionary Bioinformatics 生物-进化生物学
CiteScore
4.20
自引率
0.00%
发文量
25
审稿时长
12 months
期刊介绍: Evolutionary Bioinformatics is an open access, peer reviewed international journal focusing on evolutionary bioinformatics. The journal aims to support understanding of organismal form and function through use of molecular, genetic, genomic and proteomic data by giving due consideration to its evolutionary context.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信