MicroRNA target gene prediction of ischemic stroke by using variational Bayesian inference for Gauss mixture model

Wu,Jun; Wang,Bin; Zhou,Ju; Ji,Fajing

doi:10.3892/etm.2019.7262

MicroRNA target gene prediction of ischemic stroke by using variational Bayesian inference for Gauss mixture model

Authors:
- Jun Wu
- Bin Wang
- Ju Zhou
- Fajing Ji
View Affiliations

Affiliations: Department of Neurology, Xiangyang Central Hospital, Xianyang, Shanxi 712000, P.R. China, Jinan ZhangQiu District Hospital of TCM, Jinan, Shandong 250200, P.R. China, Department of Rehabilitation Medicine, Shanxian Central Hospital, Heze, Shandong 274300, P.R. China
Published online on: February 13, 2019 https://doi.org/10.3892/etm.2019.7262
Pages: 2734-2740
Copyright: © Wu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

MicroRNAs (miRNAs) as biomarkers of numerous diseases, are a novel group of single‑stranded, non‑coding small RNA molecules, which can regulate the gene expression and transcription or translation of target genes. Therefore, accurately identifying miRNAs and predicting their potential target genes correlated with ischemic stroke contribute to quick understanding and diagnosis of the pathogenesis of ischemic stroke. In order to identify the targets of miRNAs, the differential expression and expression profiling of mRNAs in genome are integrated by using the Gene Expression Omnibus (GEO) database and limma package. Furthermore, the probabilistic scoring approach called TargetScore, is proposed as a promising new technique combined with the expression and sequence information of the known genes. In this study, the priori and posterior probabilities of target genes were obtained by Variational Bayesian‑Gaussian Mixture Model (VB‑GMM). Consequently, the target genes of miR‑124, miR‑221 and miR‑223, correlated with ischemic stroke, were predicted using the new target prediction algorithm. Ultimately, the comparable downregulation target genes were obtained by integrating the transcendental and posterior values.

View Figures

View References

1	Lloyd-Jones D, Adams R, Carnethon M, De Simone G, Ferguson TB, Flegal K, Ford E, Furie K, Go A, Greenlund K, et al: American Heart Association Statistics Committee and Stroke Statistics Subcommittee: Heart disease and stroke statistics - 2009 update: A report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 119:e1822009.
2	Kalache A and Aboderin I: Stroke: The global burden. Health Policy Plan. 10:1–21. 1995. View Article : Google Scholar : PubMed/NCBI
3	Goldstein LB, Adams R, Becker K, Furberg CD, Gorelick PB, Hademenos G, Hill M, Howard G, Howard VJ, Jacobs B, et al: Primary prevention of ischemic stroke: A statement for healthcare professionals from the Stroke Council of the American Heart Association. Stroke. 32:280–299. 2001. View Article : Google Scholar : PubMed/NCBI
4	Love S: Apoptosis and brain ischaemia. Prog Neuropsychopharmacol Biol Psychiatry. 27:267–282. 2003. View Article : Google Scholar : PubMed/NCBI
5	Yuan J: Neuroprotective strategies targeting apoptotic and necrotic cell death for stroke. Apoptosis. 14:469–477. 2009. View Article : Google Scholar : PubMed/NCBI
6	Stapf C and Mohr JP: Ischemic stroke therapy. Annu Rev Med. 53:453–475. 2002. View Article : Google Scholar : PubMed/NCBI
7	Schellinger PD, Kaste M and Hacke W: An update on thrombolytic therapy for acute stroke. Curr Opin Neurol. 17:69–77. 2004. View Article : Google Scholar : PubMed/NCBI
8	Krützfeldt J and Stoffel M: MicroRNAs: A new class of regulatory genes affecting metabolism. Cell Metab. 4:9–12. 2006. View Article : Google Scholar : PubMed/NCBI
9	Carè A, Catalucci D, Felicetti F, Bonci D, Addario A, Gallo P, Bang ML, Segnalini P, Gu Y, Dalton ND, et al: MicroRNA-133 controls cardiac hypertrophy. Nat Med. 13:613–618. 2007. View Article : Google Scholar : PubMed/NCBI
10	Zhang J, Zhao H, Gao Y and Zhang W: Secretory miRNAs as novel cancer biomarkers. Biochim Biophys Acta. 1826:32–43. 2012.PubMed/NCBI
11	Lionetti M, Musto P, Di Martino MT, Fabris S, Agnelli L, Todoerti K, Tuana G, Mosca L, Gallo Cantafio ME, Grieco V, et al: Biological and clinical relevance of miRNA expression signatures in primary plasma cell leukemia. Clin Cancer Res. 19:3130–3142. 2013. View Article : Google Scholar : PubMed/NCBI
12	Khoo SK, Neuman LA, Forsgren L, Petillo D and Brundin P: Could miRNA expression changes be a reliable clinical biomarker for Parkinson's disease? Neurodegener Dis Manag. 3:455–465. 2013. View Article : Google Scholar
13	Bartel DP: MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell. 116:281–297. 2004. View Article : Google Scholar : PubMed/NCBI
14	Bushati N and Cohen SM: microRNA functions. Annu Rev Cell Dev Biol. 23:175–205. 2007. View Article : Google Scholar : PubMed/NCBI
15	Voinnet O: Origin, biogenesis, and activity of plant microRNAs. Cell. 136:669–687. 2009. View Article : Google Scholar : PubMed/NCBI
16	Chuck G, Candela H and Hake S: Big impacts by small RNAs in plant development. Curr Opin Plant Biol. 12:81–86. 2009. View Article : Google Scholar : PubMed/NCBI
17	Cortez MA, Bueso-Ramos C, Ferdin J, Lopez-Berestein G, Sood AK and Calin GA: MicroRNAs in body fluids - the mix of hormones and biomarkers. Nat Rev Clin Oncol. 8:467–477. 2011. View Article : Google Scholar : PubMed/NCBI
18	Bentwich I, Avniel A, Karov Y, Aharonov R, Gilad S, Barad O, Barzilai A, Einat P, Einav U, Meiri E, et al: Identification of hundreds of conserved and nonconserved human microRNAs. Nat Genet. 37:766–770. 2005. View Article : Google Scholar : PubMed/NCBI
19	Lewis BP, Burge CB and Bartel DP: Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 120:15–20. 2005. View Article : Google Scholar : PubMed/NCBI
20	Jeyaseelan K, Herath WB and Armugam A: MicroRNAs as therapeutic targets in human diseases. Expert Opin Ther Targets. 11:1119–1129. 2007. View Article : Google Scholar : PubMed/NCBI
21	Dharap A, Bowen K, Place R, Li LC and Vemuganti R: Transient focal ischemia induces extensive temporal changes in rat cerebral microRNAome. J Cereb Blood Flow Metab. 29:675–687. 2009. View Article : Google Scholar : PubMed/NCBI
22	Alexiou P, Maragkakis M, Papadopoulos GL, Reczko M and Hatzigeorgiou AG: Lost in translation: An assessment and perspective for computational microRNA target identification. Bioinformatics. 25:3049–3055. 2009. View Article : Google Scholar : PubMed/NCBI
23	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
24	Enright AJ, John B, Gaul U, Tuschl T, Sander C and Marks DS: MicroRNA targets in Drosophila. Genome Biol. 5:R12003. View Article : Google Scholar : PubMed/NCBI
25	Krek A, Grün D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, et al: Combinatorial microRNA target predictions. Nat Genet. 37:495–500. 2005. View Article : Google Scholar : PubMed/NCBI
26	Kertesz M, Iovino N, Unnerstall U, Gaul U and Segal E: The role of site accessibility in microRNA target recognition. Nat Genet. 39:1278–1284. 2007. View Article : Google Scholar : PubMed/NCBI
27	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
28	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
29	Baek D, Villén J, Shin C, Camargo FD, Gygi SP and Bartel DP: The impact of microRNAs on protein output. Nature. 455:64–71. 2008. View Article : Google Scholar : PubMed/NCBI
30	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
31	Arvey A, Larsson E, Sander C, Leslie CS and Marks DS: Target mRNA abundance dilutes microRNA and siRNA activity. Mol Syst Biol. 6:3632010. View Article : Google Scholar : PubMed/NCBI
32	Fasanaro P, Greco S, Ivan M, Capogrossi MC and Martelli F: microRNA: Emerging therapeutic targets in acute ischemic diseases. Pharmacol Ther. 125:92–104. 2010. View Article : Google Scholar : PubMed/NCBI
33	Yin KJ, Deng Z, Huang H, Hamblin M, Xie C, Zhang J and Chen YE: miR-497 regulates neuronal death in mouse brain after transient focal cerebral ischemia. Neurobiol Dis. 38:17–26. 2010. View Article : Google Scholar : PubMed/NCBI
34	Chen Y, Song Y, Huang J, Qu M, Zhang Y, Geng J, Zhang Z, Liu J and Yang GY: Increased circulating exosomal miRNA-223 is associated with acute ischemic stroke. Front Neurol. 8:572017. View Article : Google Scholar : PubMed/NCBI
35	Zhu F, Liu JL, Li JP, Xiao F, Zhang ZX and Zhang L: MicroRNA-124 (miR-124) regulates Ku70 expression and is correlated with neuronal death induced by ischemia/reperfusion. J Mol Neurosci. 52:148–155. 2014. View Article : Google Scholar : PubMed/NCBI
36	Wang Y, Zhang Y, Huang J, Chen X, Gu X, Wang Y, Zeng L and Yang GY: Increase of circulating miR-223 and insulin-like growth factor-1 is associated with the pathogenesis of acute ischemic stroke in patients. BMC Neurol. 14:772014. View Article : Google Scholar : PubMed/NCBI
37	Maitrias P, Metzinger-Le Meuth V, Massy ZA, M'Baya-Moutoula E, Reix T, Caus T and Metzinger L: MicroRNA deregulation in symptomatic carotid plaque. J Vasc Surg. 62:1245–1250. 2015. View Article : Google Scholar : PubMed/NCBI
38	Bazan HA, Hatfield SA, O'Malley CB, Brooks AJ, Lightell D Jr and Woods TC: Acute loss of miR-221 and miR-222 in the atherosclerotic plaque shoulder accompanies plaque rupture. Stroke. 46:3285–3287. 2015. View Article : Google Scholar : PubMed/NCBI
39	Khan AA, Betel D, Miller ML, Sander C, Leslie CS and Marks DS: Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs. Nat Biotechnol. 27:549–555. 2009. View Article : Google Scholar : PubMed/NCBI
40	Davis S and Meltzer PS: GEOquery: A bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics. 23:1846–1847. 2007. View Article : Google Scholar : PubMed/NCBI
41	Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D and Altman RB: Missing value estimation methods for DNA microarrays. Bioinformatics. 17:520–525. 2001. View Article : Google Scholar : PubMed/NCBI
42	Huang JC, Morris QD and Frey BJ: Bayesian inference of MicroRNA targets from sequence and expression data. J Comput Biol. 14:550–563. 2007. View Article : Google Scholar : PubMed/NCBI
43	Le HS and Bar-Joseph Z: Inferring interaction networks using the ibp applied to microrna target prediction. Adv Neural Inf Process Syst. 2011:235–243. 2011.
44	Rajewsky N: microRNA target predictions in animals. Nat Genet. 38 (Suppl):S8–S13. 2006. View Article : Google Scholar : PubMed/NCBI
45	Watanabe Y, Tomita M and Kanai A: Computational methods for microRNA target prediction. Methods Enzymol. 427:65–86. 2007. View Article : Google Scholar : PubMed/NCBI
46	van Dongen S, Abreu-Goodger C and Enright AJ: Detecting microRNA binding and siRNA off-target effects from expression data. Nat Methods. 5:1023–1025. 2008. View Article : Google Scholar : PubMed/NCBI
47	Chen HX, Liu YS and Zhang XJ: TargetScore used to reveal potential targets of miRNA203 and miRNA-146a in psoriasis by integrating microRNA overexpression and microarray data. Medicine (Baltimore). 97:e126712018. View Article : Google Scholar : PubMed/NCBI
48	An YT, Zhu P, Zhong Y, Sheng YC, Zhao Z, Min Y and Xia YY: A neuroprotective mechanism of YGY-E in cerebral ischemic injury in rats. CNS Neurosci Ther. 18:14–20. 2012. View Article : Google Scholar : PubMed/NCBI
49	Yu H, Wu M, Zhao P, Huang Y, Wang W and Yin W: Neuroprotective effects of viral overexpression of microRNA-22 in rat and cell models of cerebral ischemia-reperfusion injury. J Cell Biochem. 116:233–241. 2015. View Article : Google Scholar : PubMed/NCBI
50	Jeyaseelan K, Lim KY and Armugam A: MicroRNA expression in the blood and brain of rats subjected to transient focal ischemia by middle cerebral artery occlusion. Stroke. 39:959–966. 2008. View Article : Google Scholar : PubMed/NCBI
51	Yuan Y, Wang JY, Xu LY, Cai R, Chen Z and Luo BY: MicroRNA expression changes in the hippocampi of rats subjected to global ischemia. J Clin Neurosci. 17:774–778. 2010. View Article : Google Scholar : PubMed/NCBI
52	Krützfeldt J, Kuwajima S, Braich R, Rajeev KG, Pena J, Tuschl T, Manoharan M and Stoffel M: Specificity, duplex degradation and subcellular localization of antagomirs. Nucleic Acids Res. 35:2885–2892. 2007. View Article : Google Scholar : PubMed/NCBI
53	Buller B, Liu X, Wang X, Zhang RL, Zhang L, Hozeska-Solgot A, Chopp M and Zhang ZG: MicroRNA-21 protects neurons from ischemic death. FEBS J. 277:4299–4307. 2010. View Article : Google Scholar : PubMed/NCBI
54	Shi G, Liu Y, Liu T, Yan W, Liu X, Wang Y, Shi J and Jia L: Upregulated miR-29b promotes neuronal cell death by inhibiting Bcl2L2 after ischemic brain injury. Exp Brain Res. 216:225–230. 2012. View Article : Google Scholar : PubMed/NCBI
55	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
56	Tsai PC, Liao YC, Wang YS, Lin HF, Lin RT and Juo SH: Serum microRNA-21 and microRNA-221 as potential biomarkers for cerebrovascular disease. J Vasc Res. 50:346–354. 2013. View Article : Google Scholar : PubMed/NCBI