酒精性肝炎microRNA-mRNA差异表达网络的生物信息学分析
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摘要
目的构建酒精性肝炎(AH)的microRNA-mRNA差异表达网络,寻找AH新的诊疗靶标。方法筛选AH差异表达的microRNA和mRNA;基于TargetScan、DIANA、MIRDB、PICTAR、miRWalk2. 0等软件寻找差异microRNA靶基因,选取差异mRNA中与microRNA变化方向相反的靶基因,构建关键microRNA-mRNA网络;通过注释、可视化和集成发现数据库(DAVID)对相关靶基因进行基因本体论(GO)分析、京都基因与基因组百科全书数据库(KEGG)通路分析;通过GCBI (www. gcbi. com. cn)在线软件对靶基因进行疾病富集分析和核心网络构建;通过Cytoscape软件中GeneMANIA数据库(genemania. org)对关键靶基因进行蛋白相互作用分析,对比3种方法通路分析寻找AH发生过程中的关键通路。结果构建以hsa-mir-21-5p、hsa-mir-148a-3p和hsa-mir-30e-5p等5个差异microRNA及Ⅳ胶原α1链(COL4A1)、血栓反应素2(THBS2)和整合素亚单位α6(ITGA6)等51个靶基因为主体的AH关键microRNA-mRNA网络;构建关键靶基因相关的蛋白相互作用网络; GO分析和各种通路分析分析显示,磷脂酰肌醇3-激酶/蛋白激酶B(PI3K-Akt)通路和局部黏附等过程与AH密切相关。结论 AH发病过程中,多种关键靶基因相关蛋白存在复杂的相互作用,COL4A1和THBS2可能通过激活ITGA6调节PI3K-Akt通路和局部黏附等过程,促进AH的发展; microRNA-mRNA网络的构建揭示了AH发生过程中的关键环节,凸显了研究重点,尤其是PI3K-Akt相关基因在AH中的发现,有望为AH的诊疗提供新的靶标。
Objective To establish a microRNA-mRNA differential expression network for alcoholic hepatitis( AH),and to investigatenew targets for the diagnosis and treatment of AH. Methods Differentially expressed microRNAs and mRNAs between AH patients and nor-mal controls were screened out. Related software including TargetScan,DIANA,MIRDB,PICTAR,and miRWalk 2. 0 was used to searchfor the target genes of differentially expressed microRNA,and a key microRNA-mRNA network was established using the differentially ex-pressed mRNAs that changed in an opposite way to microRNA. The Database for Annotation,Visualization and Integrated Discovery wasused for the gene ontology( GO) and Kyoto Encyclopedia of Genes and Genome( KEGG) analyses of target genes. The GCBI online soft-ware( www. gcbi. com. cn) was used for enrichment analysis of target genes and core network establishment. The GeneMANIA database inCytoscape software( genemania. org) was used to perform a protein-protein interaction analysis of key target genes. The above three meth-ods were compared in terms of the search for key pathways involved in the development of AH. Results A key microRNA-mRNA networkwas established with 5 differentially expressed microRNAs including hsa-mir-21-5 p,hsa-mir-148 a-3 p,and hsa-mir-30 e-5 pand 51 target genes including collagen type IV alpha 1 chain( COL4 A1),thrombospondin-2( THBS2),and integrin alpha 6( IGTA6). Aprotein-protein interaction network of key target genes was established. The GO analysis and various pathway analyses showed that the PI3 K-Akt pathway and local adhesion were closely associated with AH. Conclusion During the development of AH,there are complex interac-tions between the related proteins of key target genes. COL4 A1 and THBS2 may promote the development of AH by activating ITGA6 to regu-late the PI3 K-Akt pathway and the process of local adhesion. The establishment of the microRNA-mRNA network reveals the key links inthe development of AH and highlights the focus of research. The discovery of the genes associated with the PI3 K-Akt pathway in AH is ex-pected to provide new targets for the diagnosis and treatment of AH.
Objective To establish a microRNA-mRNA differential expression network for alcoholic hepatitis( AH),and to investigatenew targets for the diagnosis and treatment of AH. Methods Differentially expressed microRNAs and mRNAs between AH patients and nor-mal controls were screened out. Related software including TargetScan,DIANA,MIRDB,PICTAR,and miRWalk 2. 0 was used to searchfor the target genes of differentially expressed microRNA,and a key microRNA-mRNA network was established using the differentially ex-pressed mRNAs that changed in an opposite way to microRNA. The Database for Annotation,Visualization and Integrated Discovery wasused for the gene ontology( GO) and Kyoto Encyclopedia of Genes and Genome( KEGG) analyses of target genes. The GCBI online soft-ware( www. gcbi. com. cn) was used for enrichment analysis of target genes and core network establishment. The GeneMANIA database inCytoscape software( genemania. org) was used to perform a protein-protein interaction analysis of key target genes. The above three meth-ods were compared in terms of the search for key pathways involved in the development of AH. Results A key microRNA-mRNA networkwas established with 5 differentially expressed microRNAs including hsa-mir-21-5 p,hsa-mir-148 a-3 p,and hsa-mir-30 e-5 pand 51 target genes including collagen type IV alpha 1 chain( COL4 A1),thrombospondin-2( THBS2),and integrin alpha 6( IGTA6). Aprotein-protein interaction network of key target genes was established. The GO analysis and various pathway analyses showed that the PI3 K-Akt pathway and local adhesion were closely associated with AH. Conclusion During the development of AH,there are complex interac-tions between the related proteins of key target genes. COL4 A1 and THBS2 may promote the development of AH by activating ITGA6 to regu-late the PI3 K-Akt pathway and the process of local adhesion. The establishment of the microRNA-mRNA network reveals the key links inthe development of AH and highlights the focus of research. The discovery of the genes associated with the PI3 K-Akt pathway in AH is ex-pected to provide new targets for the diagnosis and treatment of AH.
引文
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[23] PIANO MR. Alcohol's effects on the cardiovascular system[J]. Alcohol Res,2017,38(2):219-241.
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[25] REHM J,ROERECKE M. Cardiovascular effects of alcohol con-sumption[J]. Trends Cardiovasc Med,2017,27(8):534-538.
[26] GHIGO A,LAFFARGUE M,LI M,et al. PI3K and calcium sig-naling in cardiovascular disease[J]. Circ Res,2017,121(3):282-292.
[27] GHIGO A,MORELLO F,PERINO A,et al. Therapeutic appli-cations of PI3K inhibitors in cardiovascular diseases[J]. Fu-ture Med Chem,2013,5(4):479-492.
[2] PAUL G,YAN Z. Biogenesis of mammalian microRNAs:Aglobal view[J]. Genomics Proteomics Bioinformatics,2012,10(5):239-245.
[3] ZHAO XM,LIU KQ,ZHU G,et al. Identifying cancer-relatedmicroRNAs based on gene expression data[J]. Bioinformat-ics,2015,31(8):1226-1234.
[4] GENG YJ,LI SD,LIU ZZ,et al. Inhibitory effect of microRNA-149-5p in the proliferation and migration of HepG2 and Be1-7402 hepatoma cells[J]. J Clin Hepatol,2017,33(6):1126-1130.(in Chinese)耿亚军,李树栋,刘中政,等. microRNA-149-5p过表达对肝癌细胞HepG2和Bel-7402增殖及迁移的抑制作用[J].临床肝胆病杂志,2017,33(6):1126-1130.
[5] BECKER S,FLORIAN A,PATRASCU A,et al. Identification ofcardiomyopathy associated circulating miRNA biomarkers inpatients with muscular dystrophy using a complementary car-diovascular magnetic resonance and plasma profiling ap-proach[J]. J Cardiovasc Magn Reson,2016,18(1):244.
[6] AGARWAL V,BELL GW,NAM JW,et al. Predicting effectivemicroRNA target sites in mammalian mRNAs[J]. e Life,2015,4:e05005.
[7] RECZKO M,MARAGKAKIS M,ALEXIOU P,et al. FunctionalmicroRNA targets in protein coding sequences[J]. Bioinfor-matics,2012,28(6):771-776.
[8] WONG N,WANG XW. miRDB:An online resource for microR-NA target prediction and functional annotations[J]. NucleicAcids Res,2015,43(D1):d146-d152.
[9] AZRA K,DOMINIC G,MATTHEW NP,et al. Combinatorial mi-croRNA target predictions[J]. Nat Genet,2005,37:495-500.
[10] DWEEP H,STICHT C,PANDEY P,et al. miRWalk-data-base:Prediction of possible miRNA binding sites by"walk-ing"the genes of 3 genome[J]. J Biomed Inform,2011,44(5):839-847.
[11] DWEEP H,GRETZ N. miRWalk2. 0:A comprehensive atlas ofmicroRNA-target interactions[J]. Nat Methods,2015,12(8):697-697.
[12] GLYNN D,SHERMAN BT,HOSACK DA,et al. DAVID:Data-base for annotation,visualization,and integrated discovery[J]. Genom Biol,2003,4(5):p3.
[13] BARRETT T,SUZEK TO,TROUP DB,et al. NCBI GEO:Min-ing millions of expression profiles—database and tools[J].Nucleic Acids Res,2005,33:d562-d566.
[14] AFFO S,DOMINGUEZ M,LOZANO JJ,et al. Transcriptomeanalysis identifies TNF superfamily receptors as potential thera-peutic targets in alcoholic hepatitis[J]. Gut,2013,62(3):452-460.
[15] BLAYA D,COLL M,RODRIGO-TORRES D,et al. IntegrativemicroRNA profiling in alcoholic hepatitis reveals a role for mi-croRNA-182 in liver injury and inflammation[J]. Gut,2016,65(9):1535-1545.
[16] SMYTH GK. Linear models and empirical Bayes methods forassessing differential expression in microarray experiments[J]. Stat Appl Genet Mol Biol,2004,3(3):Article3.
[17] RITCHIE ME,PHIPSON B,WU D,et al. Limma powers differ-ential expression analyses for RNA-sequencing and microar-ray studies[J]. Nucleic Acids Res,2015,43(7):e47.
[18] WANG J,CHU ESH,CHEN HY,et al. microRNA-29b pre-vents liver fibrosis by attenuating hepatic stellate cell activationand inducing apoptosis through targeting PI3K/AKT pathway[J]. Oncotarget,2015,6(9):7325-7338.
[19] MATHURIN P,BEUZSIN F,LOUVET A,et al. Fibrosis pro-gression occurs in a subgroup of heavy drinkers with typicalhistological features[J]. Aliment Pharmacol Ther,2007,25(9):1047-1054.
[20] MCKNIGHT-EILY LR,HENLEY SJ,GREEN PP,et al. Alco-hol screening and brief intervention:A potential role in cancerprevention for young adults[J]. Am J Prev Med,2017,53(3S1):s55-s62.
[21] SCHEIDELER JK,KLEIN WMP. Awareness of the link betweenalcohol consumption and cancer across the world:A review[J]. Cancer Epidemiol Biomarkers Prev,2018,27(4):429-437.
[22] GU S,NGUYEN BN,RAO S,et al. Alcohol,stem cells andcancer[J]. Genes Cancer,2017,8(9-10):695-700.
[23] PIANO MR. Alcohol's effects on the cardiovascular system[J]. Alcohol Res,2017,38(2):219-241.
[24] GOEL S,SHARMA A,GARG A. Effect of alcohol consumption oncardiovascular health[J]. Curr Cardiol Rep,2018,20(4):19.
[25] REHM J,ROERECKE M. Cardiovascular effects of alcohol con-sumption[J]. Trends Cardiovasc Med,2017,27(8):534-538.
[26] GHIGO A,LAFFARGUE M,LI M,et al. PI3K and calcium sig-naling in cardiovascular disease[J]. Circ Res,2017,121(3):282-292.
[27] GHIGO A,MORELLO F,PERINO A,et al. Therapeutic appli-cations of PI3K inhibitors in cardiovascular diseases[J]. Fu-ture Med Chem,2013,5(4):479-492.