Screening of miRNA target genes in coronary artery disease by variational Bayesian Gaussian mixture model

Ma,Xiao‑Lin; Yang,Xu; Fan,Rui

doi:10.3892/etm.2019.7195

Screening of miRNA target genes in coronary artery disease by variational Bayesian Gaussian mixture model

Authors:
- Xiao‑Lin Ma
- Xu Yang
- Rui Fan
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Affiliations: Department of Cardiology, The People's Hospital of Xuancheng City, Xuancheng, Anhui 242000, P.R. China, Department of Cardiovascular Disease, The Second People's Hospital of Yunnan Province, Kunming, Yunnan 650021, P.R. China , Department of Cardiology, Xinjiang Changjizhou People's Hospital, Changjizhou, Xinjiang Uygur Autonomous Region 831100, P.R. China
Published online on: January 22, 2019 https://doi.org/10.3892/etm.2019.7195
Pages: 2129-2136
Copyright: © Ma et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Coronary artery disease (CAD) is a leading cause of death, and microRNAs (miRNAs) are widely involved in physiological and pathological processes of CAD. We chose the targetscore method calculated via the variational Bayesian Gaussian mixture model (VB‑GMM) as the prediction method of target genes. By observing the density overlap, we selected the thresholds of miRNA‑1 and miRNA‑155. In total, 18 target genes of miRNA‑1, and 19 target genes of miRNA‑155 were identified. The threshold of miRNA‑146a was selected using the |logFC| value, and 16 target genes were screened out. In this study, our major contribution was to predict the target messenger RNAs (mRNAs) of the chosen miRNAs with the gene expression profiles, which can effectively reduce the workload of screening. Although the validated genes constituted only a small part in the final prediction results, it is a good sign for research in the future. It means that we could provide new research aims for future studies focusing on miRNA regulatory mechanisms.

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1	Eriksen A, Tillin T, O'Connor L, Brage S, Hughes A, Mayet J, McKeigue P, Whincup P, Chaturvedi N and Forouhi NG: The impact of health behaviours on incident cardiovascular disease in Europeans and South Asians - a prospective analysis in the UK SABRE study. PLoS One. 10:e01173642015. View Article : Google Scholar : PubMed/NCBI
2	Wang L, Zhi H, Li Y, Ma G, Ye X, Yu X, Yang T, Jin H, Lu Z and Wei P: Polymorphism in miRNA-1 target site and circulating miRNA-1 phenotype are associated with the decreased risk and prognosis of coronary artery disease. Int J Clin Exp Pathol. 7:5093–5102. 2014.PubMed/NCBI
3	Lai Y, He S, Ma L, Lin H, Ren B, Ma J, Zhu X and Zhuang S: HOTAIR functions as a competing endogenous RNA to regulate PTEN expression by inhibiting miR-19 in cardiac hypertrophy. Mol Cell Biochem. 432:179–187. 2017. View Article : Google Scholar : PubMed/NCBI
4	Liu H, Li G, Zhao W and Hu Y: Inhibition of miR-92a may protect endothelial cells after acute myocardial infarction in rats: Role of KLF2/4. Med Sci Monit. 22:2451–2462. 2016. View Article : Google Scholar : PubMed/NCBI
5	Castoldi G, Di Gioia CR, Bombardi C, Catalucci D, Corradi B, Gualazzi MG, Leopizzi M, Mancini M, Zerbini G, Condorelli G, et al: MiR-133a regulates collagen 1A1: Potential role of miR-133a in myocardial fibrosis in angiotensin II-dependent hypertension. J Cell Physiol. 227:850–856. 2012. View Article : Google Scholar : PubMed/NCBI
6	Wu ZW, Liu YF, Wang S and Li B: miRNA-146a induces vascular smooth muscle cell apoptosis in a rat model of coronary heart disease via NF-κB pathway. Genet Mol Res. 14:18703–18712. 2015. View Article : Google Scholar : PubMed/NCBI
7	Kishore R, Verma SK, Mackie AR, Vaughan EE, Abramova TV, Aiko I and Krishnamurthy P: Bone marrow progenitor cell therapy-mediated paracrine regulation of cardiac miRNA-155 modulates fibrotic response in diabetic hearts. PLoS One. 8:e601612013. View Article : Google Scholar : PubMed/NCBI
8	Baumgarten A, Bang C, Tschirner A, Engelmann A, Adams V, von Haehling S, Doehner W, Pregla R, Anker MS, Blecharz K, et al: TWIST1 regulates the activity of ubiquitin proteasome system via the miR-199/214 cluster in human end-stage dilated cardiomyopathy. Int J Cardiol. 168:1447–1452. 2013. View Article : Google Scholar : PubMed/NCBI
9	Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP and Burge CB: Prediction of mammalian microRNA targets. Cell. 115:787–798. 2003. View Article : Google Scholar : PubMed/NCBI
10	Friedman RC, Farh KK, Burge CB and Bartel DP: Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 19:92–105. 2009. View Article : Google Scholar : PubMed/NCBI
11	Nam JW, Rissland OS, Koppstein D, Abreu-Goodger C, Jan CH, Agarwal V, Yildirim MA, Rodriguez A and Bartel DP: Global analyses of the effect of different cellular contexts on microRNA targeting. Mol Cell. 53:1031–1043. 2014. View Article : Google Scholar : PubMed/NCBI
12	Li Y, Goldenberg A, Wong KC and Zhang Z: A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information. Bioinformatics. 30:621–628. 2014. View Article : Google Scholar : PubMed/NCBI
13	Zhu J, Chen T, Yang L, Li Z, Wong MM, Zheng X, Pan X, Zhang L and Yan H: Regulation of microRNA-155 in atherosclerotic inflammatory responses by targeting MAP3K10. PLoS One. 7:e465512012. View Article : Google Scholar : PubMed/NCBI
14	Wang Y, Wang X, Li Z, Chen L, Zhou L, Li C and Ouyang DS: Two single nucleotide polymorphisms (rs2431697 and rs2910164) of miR-146a are associated with risk of coronary artery disease. Int J Environ Res Public Health. 14:142017.
15	Takane K, Fujishima K, Watanabe Y, Sato A, Saito N, Tomita M and Kanai A: Computational prediction and experimental validation of evolutionarily conserved microRNA target genes in bilaterian animals. BMC Genomics. 11:1012010. View Article : Google Scholar : PubMed/NCBI
16	Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM, Castle J, Bartel DP, Linsley PS and Johnson JM: Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature. 433:769–773. 2005. View Article : Google Scholar : PubMed/NCBI
17	Selbach M, Schwanhäusser B, Thierfelder N, Fang Z, Khanin R and Rajewsky N: Widespread changes in protein synthesis induced by microRNAs. Nature. 455:58–63. 2008. View Article : Google Scholar : PubMed/NCBI
18	Yin Q, McBride J, Fewell C, Lacey M, Wang X, Lin Z, Cameron J and Flemington EK: MicroRNA-155 is an Epstein-Barr virus-induced gene that modulates Epstein-Barr virus-regulated gene expression pathways. J Virol. 82:5295–5306. 2008. View Article : Google Scholar : PubMed/NCBI