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Long non-coding RNA MIAT in development and disease: a new player in an old game



Long non-coding RNAs (lncRNAs), which are a portion of non-protein-coding RNAs (ncRNAs), have manifested a paramount role in the pathophysiology of human diseases, particularly in pathogenesis and progression of disease.

Main body of the abstract

Myocardial infarction associated transcript (MIAT), which was recently found to demonstrate aberrant expression in various diseases, such as myocardial infarction, schizophrenia, ischemic stroke, diabetic complications, age-related cataract and cancers, is a novel disease-related lncRNA. This work summarize current evidence regarding the biological functions and underlying mechanisms of lncRNA MIAT during disease development.

Short conclusion

LncRNA MIAT likely represents a feasible cancer biomarker or therapeutic target.


With advancements in global transcriptome profiling technique, the deregulation of lncRNAs has recently been demonstrated to be related to various human diseases, including most notably cancers [1, 2], neurological disorders [3], and cardiovascular diseases [4, 5]. Increasingly, some lncRNAs play a crucial role in cancer progression, such as proliferation, invasion and metastasis [6, 7]. Consequently, lncRNAs may be regarded as a promising marker for the prognosis of cancer [8]. According to the draft of the human genome project (HGP), the human genome contains only approximately 20,000 protein-coding genes, which accounts for less than 2% of the entire genome. Generally, at least 70% of the sequences are transcribed into RNAs in higher eukaryotic genomes. To our knowledge, most of these transcripts are ncRNAs, which were originally regarded as transcriptional noise and attracted limited attention [9].

LncRNAs are currently defined as a large and heterogeneous class of transcribed RNA molecules, which lack an open reading frame of significant length, and the length of lncRNA is greater than 200 nucleotides. Similar to protein-coding RNAs, the majority of lncRNAs are RNA polymerase II transcripts with a poly-A tail and 5′ cap. Interestingly, most lncRNAs are predominantly localized within the cell nucleus, and exhibit either lower evolutionary conservation or lower expression level than mRNAs [10,11,12]. Much of works have demonstrated that lncRNAs could regulate gene expression levels, post-transcriptional modifications, bind to transcription factors or miRNAs, and play modulator roles in many biological processes [13,14,15]. Thus, knowledge about their unique RNA properties, more tissue-specific expression fashion and more stable structure, it is expected that lncRNAs might advance our understanding of disease progression and unveil novel biomarkers for diagnosis and prognosis.

MIAT, also termed as Gomafu in human or Rncr2 in mouse [16,17,18], is a promising functional factor among all disease-associated lncRNAs, and exhibits deregulation in multiple diseases, including up-regulation in ischemic stroke, myocardial infarction, neuroendocrine prostate cancer, non-small-cell lung cancer, diabetic cardiomyopathy, cataract, chronic chagas disease cardiomyopathy, chronic lymphocytic leukemia and down-regulation in schizophrenia, diabetic nephropathy, bone disease. The present review summarizes current studies concerning the abnormal expression, biological function, molecular mechanism and clinical significance of MIAT in the initiation and progression of human diseases (Table 1).

Table 1 Functional characterization of MIAT in diseases

Discovery and characterization of lncRNA MIAT

MIAT, which was initially reported in 2000 [19], is located at 22q12.1 with a length of 30,051 bp. Originally, through a large-scale case-control association study using 52,608 haplotype-based single nucleotide polymorphism (SNP) markers, Ishii et al. identified a susceptible locus for myocardial infarction. As a result, within this locus, they isolated a complete cDNA of a novel gene, designated MIAT [18]. In addition, this gene consists of five exons and all the splice junctions are considered to conform to the basic GT/AG rule [20, 21].

Though conventional sequence alignment searches did not identify any nonmammalian orthologous genes of MIAT [17], however, a search identified putative MIAT was orthologous to chick and Xenopus tropicalis. Interestingly, multiple clustered sequence repeats of the sequence ACUAACC were found in the largest exon of each orthologous gene, with anywhere from five to eight such repeats found within each transcript [22]. Furthermore, this repeat sequence includes the ACUAAY consensus recognition site for the RNA binding protein Quaking, which regulates both RNA subcellular localization and stability [23, 24], although the functional significance of this is unclear. In addition, unlike other nuclear-retained lncRNAs such as Xist and Air, MIAT shows no association with chromatin and is tightly associated with the nuclear matrix [17]. Generally, MIAT is highly conserved in placental mammals, and appears to be conserved back to amphibians [18, 25].

LncRNA MIAT in human diseases

Cardiovascular system diseases

Myocardial infarction

Myocardial infarction (MI), which accounts for the leading cause of death in the worldwide [26, 27], is characterized by myocardial remodeling processes involving left ventricular dilation, cardiomyocyte hypertrophy, arrhythmias, cardiac fibrosis, and cell death accompanied by altered expression of genes, leading to heart failure [28,29,30].

Constant researches have led to the fact that MIAT is involved in MI. Ishii et al. originally identified that the aberrant expression of one SNP rs2301523 was related to the pathogenesis of MI. Subsequently, through a large-scale case-control association study using 52,608 gene-based genome-wide tag SNPs, they found that this SNP in MIAT, due to its altered expression by the single nucleotide polymorphism, which had a significant association with the pathogenesis of MI [18]. Through the quantitative PCR technology, Vausort et al. found that Patients with STEMI (ST-elevation myocardial infarction) had lower levels of MIAT in peripheral blood cells compared to patients with NSTEMI. Of all the cardiovascular risk factors, the expression level of MIAT in MI patients was significantly associated with hypertension and smoking. Moreover, MIAT was positively associated with the percentage of lymphocytes and negatively associated with neutrophils and platelets in all the inflammation markers. In addition, according to their 4-month follow-up, the expression level of MIAT was a significant univariate predictor of LV dysfunction [31]. Qu et al. identified MIAT expression was remarkable up-regulated in a mouse model of MI heart compared with that in aninals contrals, Most notably, MIAT knokdown improved cardiac function and inhibited interstitial Fibrosis by inhibiting collagen production and cardiac fibroblasts proliferation [32]. These data suggest that MIAT may serve as a specific biomarker and therapeutic target for MI.

Ischemic stroke

Stroke is the leading cause of death and long-term disability in developed countries [33, 34]. Ischemic stroke (IS) is the most common form of stroke, accounting for approximately 87% of all cases [35, 36]. Thus, developing a noninvasive high-sensitive blood biomarker for early screening and monitoring of brain ischemia patients is feasible and valuable.

Zhu et al. indicated that MIAT expression level was significantly up-regulated in peripheral blood leukocytes of 189 IS patients compared with controls. Moreover, increased MIAT was markedly correlated with NIHSS scores, mRS, high-sensitivity C-reactive protein, and infarct volume in IS. In addition, the overall survival analysis showed that IS patients with higher MIAT expression had a relatively poor prognosis compared with the low group. Meanwhile, the multivariate analysis revealed that MIAT was an independent prognostic marker of functional outcome and death in patients with IS. Furthermore, ROC curves indicated that MIAT could serve as a potential marker for discriminating IS patients from the controls. [37].

Nervous system diseases


Schizophrenia (SCZ) disorder, a debilitating mental disorder affecting about 1% of the population [38], is believed to be the result of combinations of genetic and environmental factors resulting in brain dysfunction [39]. Aprea et al. have demonstrated the physiological roles of MIAT in differentiation of neurons and excitatory neurons in embryonic brain for the first time [40]. Then, Barry et al. further revealed that MIAT was significant decreased at 1 and 3 h and a returned to normal levels by 5 a neuronal stimulation time course using depolarized mouse primary cortical neurons. Moreover, MIAT was observed significantly decreased in depolarized hiPSC-derived neurons. In addition, cortical MIAT was found significantly reduced by 1.75-fold in SCZ of post-mortem superior temporal gyrus in relative to controls [41].Afterwards, Rao et al. observed that rs1894720, one of eight tag SNPs that covered the whole MIAT locus, which was significantly associated with paranoid schizophrenia in two independent Han Chinese schizophrenia case–control cohorts(discovery sample from Shanxi Province: 1093 patients with paranoid schizophrenia and 1180 control subjects; replication cohort from Jilin Province: 1255 cases and 1209 healthy controls) using a two-stage association analysis [42]. Hence, continuing and thorough exploration for MIAT may make a new breakthrough in the diagnosis and treatment of SCZ.


Neuroendocrine prostate cancer

Prostate cancer (PCa) represents the second most frequently diagnosed neoplasm and is the fifth leading cause of cancer death worldwide [43]. Between 0.5 and 2% of newly diagnosed prostate neoplasms are classified as neuroendocrine PCa (NEPC), which is insensitive to all forms of hormonal treatment [44], is often diagnosed at a metastatic stage [45]. In addition, no treatment has demonstrated efficacy in extending the survival of NEPC patients, while median NEPC survival is only 7 months [46]. Crea et al. discovered that MIAT was the most highly up-regulated transcript in 18 prostatic adenocarcinoma and three NEPC models. Moreover, unsupervised hierarchical clustering demonstrated that MIAT expression could efficiently discriminate NEPC and adenocarcinoma samples in a clinical cohort. In addition, oncomine database analyses revealed that MIAT expression was restricted to a small percentage of PCas, with high metastatic potential, poor prognosis and frequent Rb mutations [47]. Notably, all those are hallmarks of NEPC [48, 49]. In general, MIAT displays advantageous characteristics as a novel biomarker and as a therapeutic target in prostate cancer.

Non-small-cell lung cancer

Lung cancer remains the leading cause of death from cancer worldwide [50]. Non-small-cell lung cancer (NSCLC), which accounts for approximately 80% of all lung cancer cases, is the primary category of lung cancer, and its prognosis is poor despite recent progress in chemotherapy [51]. Therefore, an urgent need to develop reliable prognostic biomarkers and molecular targets aimed to reduce the morbidity and mortality associated with NSCLC. Zhang et al. reported that the expression of MIAT in 31 NSCLC tissues was up-regulated compared to mixed 30 normal tissues. Furthermore, MIAT expression was significantly higher in all human lung cancer lines compared to control group. In addition, knockdown of MIAT substantially inhibited the invasive ability of NSCLC cells [52]. Taken together, MIAT may therefore serve as a valuable prognostic biomarker and therapeutic target for NSCLC.

Endocrine system diseases

Diabetes mellitus

Diabetes mellitus (DM) is commonly derived from the defects in insulin secretion or insulin action, or both of them and the chronic DM would induce the damage or dysfunction of several organs, such as heart, eyes, nerves, as well as kidney and blood vessels [53, 54]. Recently, MIAT emerged as a potential regulator for diabetic complications [55].

Diabetic cardiomyopathy (DCM), which is defined as myocardial dysfunction occurring in the absence of coronary artery disease and hypertension, carries a substantial risk for the subsequent development of heart failure. Zhou et al. demonstrated that the expression level of MIAT was up-regulated in the myocardium of diabetic rats and MIAT knockdown was found to inhibit apoptosis in cardiomyocytes exposed to high glucose. Moreover, decreased MIAT expression was shown to improve diabetic rats’ cardiac structure, such as LVEDD (left ventricular end-diastolic dimension) and LVESD (left ventricular end systolic diameter). In addition, LVFS (left ventricular fractional shortening), LVEF (left ventricular ejection fraction) and E/A ratio, indicators of left ventricular systolic and diastolic function, could be improved by down-regulated MIAT in diabetic rats [56].

Diabetic nephropathy (DN) is one of the most common diabetic complications that develops secondary to diabetes, represents the leading cause of chronic kidney failure, and it remains a major contributor to increase morbidity and mortality among individuals with diabetes [55]. Zhou et al. discovered that MIAT wan lowly expressed in renal tubule of diabetic rats compared with that in normal controls. Moreover, down-regulated MIAT was negatively related to serum creatinine and BUN in diabetic rats. In addition, expression level of MIAT was significantly decreased in human renal tubular epithelial cells due to the increase of glucose. Biologically, MIAT over-expression significantly improved human renal tubular cell viability in vitro experiment [57]. These data suggested that MIAT was important for high glucose induced organ injury. Hence, MIAT is expected to serve as a novel diagnostic biomarker and therapeutic target.

Other diseases

Shen et al. reported that MIAT level was significantly up-regulated in the plasma fraction of cataract patients, MIAT knockdown could affect the proliferation, apoptosis and migration of Human lens epithelial cells (HLECs) [58]. Jin et al. indicated the expression of MIAT was down-regulated in a time-dependent manner during human adipose-derived stem cells (hASCs) osteo-induction, MIAT knockdown promoted osteogenic differentiation of hASCs both in vitro and in vivo. Furthermore, decreased MIAT expression reversed the negative effects of TNFα on osteoblast differentiation in hASCs [59]. Frade et al. confirmed that MIAT was specially increased in heart tissue biopsies from chronic chagas disease cardiomyopathy (CCC) patients but not in those from dilated cardiomyopathy (DCM) or control tissue. Moreover, overexpression of MIAT was confirmed in mouse model of T.cruzi infection [60]. Sattari et al. reported that MIAT was increased in malignant mature B cells including established cell lines of chronic lymphocytic leukemia (CLL) and non-Hodgkin lymphoma origin as well as primary leukemic cells obtained from CLL patients. Furthermore, decreased MIAT expression inhibited cell proliferation compared to the growth of control treated cells. These date suggested that MIAT functioned to protect malignant mature B cells from cell apoptosis [61].

Regulation mechanisms of MIAT

The competitive endogenous RNA (ceRNA) hypothesis has been proposed that protein-coding messenger RNAs and non-coding RNAs communicate with each other by competing for binding to shared miRNAs, a family of small non-coding RNAs responsible for the post-transcriptional regulation of gene expression [62]. The ceRNA regulatory network is a major mechanism of MIAT in disease development. Investigations had reported that MIAT, which worked as a ceRNA for miR-150-5p and constituted a MIAT/miR-150-5p/VEGF feedback loop, regulated endothelial and Müller cell function, such as proliferation, migration and apoptosis [55, 63]. Shen et al. found that MIAT acted as a ceRNA, and formed a MIAT/miR-150-5p/Akt feedback loop to regulate HLEC function, including proliferation, apoptosis and migration [58]. Qu et al. confirmed that MIAT functioned as a ceRNA for miR-24 to modulate Furin and TGF-β1 expression, suggested that a MIAT/miR-24/Furin/TGF-β1 modality participated in MI or other cardiac pathological processes associated with fibrosis [37]. Zhou et al. demonstrated that MIAT might function as a ceRNA to upregulate DAPK2 expression by sponging miR-22-3p, which consequently leaded to cardiomyocyte apoptosis involved in the pathogenesis of DCM [56]. Zhang et al. reported that MIAT could enhance the expression of ZEB1 by acting as a miR-150 sponge to promote cell invasion during NSCLC [52].

In addition to acting as a ceRNA, MIAT can also activate various signaling pathways. Zhou et al. discovered that MIAT over-expression enhanced Nrf2 (nuclear factor erythroid 2-related factor 2) expression in high glucose incubated renal tubular epithelial cell line HK-2, Furthermore, alteration of cellular MIAT expression level caused negatively expression of Nrf2 protein but had no effect on Nrf2 mRNA level. In addition, the MIAT was indicated to pro-stability act on Nrf2 expression in HK-2. Biologically, decreased MIAT expression reduced cell viability, whereas this inhibitory action was abrogated by Nrf2 overexpression. Hence, MIAT/Nrf2 signal axis might serve as an important signaling pathway for high glucose induced renal tubular epithelial injury [57]. Barry et al. revealed that MIAT strongly bound to the splicing regulator QKI and SRSF1 (serine/arginine-rich splicing factor 1) in nuclear compartment of SZ neuron. Furthermore, increased MIAT significantly decreased DISC1 (disrupted in schizophrenia 1), ERBB4 (v-erb-a erythroblastic leukemia viral oncogene homolog 4) and their alternatively spliced variants in SZ patient brains. In addition, the expression level of MIAT was related to dopamine (DRD2) and glutamate (GRM3) pathways, DRD2 splice-variant expression was reciprocally regulated by MIAT, GRM3 were upregulated by MIAT knockdown. Hence, MIAT expression might contribute to the pathophysiology of SZ by acting as a splicing factor scaffold for the SZ-associated splicing factor [36]. Sattari et al. showed that MIAT constituted positive feedback regulatory loop with its transcriptional regulator OCT4 to promote celluar proliferation in human malignant mature B cells [61]. These findings reveal the complexity of these interactions, which contribute to malignant transformation and disease progression.

Conclusion and future perspectives

MIAT, a well-characterized disease-related lncRNA, can impact cellular functions such as proliferation, apoptosis, and invasion in various human diseases. The regulatory mechanisms of MIAT are extraordinarily complicated and involve multiple steps (Fig. 1). The aberrant expression of MIAT exhibits a critical role in disease development, and may serve as a potential biomarker for diagnosis and prognosis. However, the chemical stability and expression levels of MIAT in biological specimens have not been clearly validated. Due to its strong disease specificity and reduced systemic toxicity, MIAT, which acts as a viable therapeutic target, is extremely promising. Taken together, the research that focuses on MIAT is still in the early stage, and some pivotal matters for its clinical application still need to be resolved. The detailed regulatory mechanisms upstream and downstream of MIAT should be paid attention to exploring, and consolidate the underlying mechanisms from the former. Undoubtedly, efforts to clarify the underlying mechanisms promise that MIAT will ultimately reach the clinic.

Fig. 1

MIAT mediates mechanisms involved in disease progression



Blood urea nitrogen


Chronic chagas disease cardiomyopathy


Competitive endogenous RNA


Chronic lymphocytic leukemia


Diabetic cardiomyopathy


Disrupted in schizophrenia 1


Diabetic mellitus


Diabetic Nephropathy


v-erb-a erythroblastic leukemia viral oncogene homolog 4


Human adipose-derived stem cells


Heart failure


Human genome project


Ischemic stroke


Long non-coding RNAs


Left ventricular


Left ventricular end-diastolic dimension


Left ventricular ejection fraction


Left ventricular end systolic diameter


Left ventricular fractional shortening


Myocardial infarction


Myocardial infarction associated transcript


Noncoding RNA


Neuroendocrine PCa


Nuclear factor erythroid 2-related factor 2


Non-small-cell lung cancer


Prostate cancer




Single nucleotide polymorphism


Serine/arginine-rich splicing factor 1


ST-elevation myocardial infarction


Zinc finger E-box binding homeobox 1


  1. 1.

    Song W, Zou SB. Prognostic role of lncRNA HOTAIR in esophageal squamous cell carcinoma. Clin Chim Acta. 2016;463:169–73.

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Cheng N, Li X, Zhao C, Ren S, Chen X, Cai W, et al. Microarray expression profile of long non-coding RNAs in EGFR-TKIs resistance of human non-small cell lung cancer. Oncol Rep. 2015;33:833–9.

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Ng SY, Lin L, Soh BS, Stanton LW. Long noncoding RNAs in development and disease of the central nervous system. Trends Genet. 2013;29:461–8.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Molina E, Chew GS, Myers SA, Clarence EM, Eales JM, Tomaszewski M, et al. A novel Y-specific long non-coding RNA associated with cellular lipid accumulation in HepG2 cells and atherosclerosis-related genes. Sci Rep. 2017;7(1):16710.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Holdt LM, Beutner F, Scholz M, Gielen S, Gäbel G, Bergert H, et al. ANRIL expression is associated with atherosclerosis risk at chromosome 9p21. Arterioscler Thromb Vasc Biol. 2010;30:620–7.

    CAS  Article  PubMed  Google Scholar 

  6. 6.

    Shao Y, Ye M, Li Q, Sun W, Ye G, Zhang X, et al. LncRNA-RMRP promotes carcinogenesis by acting as a miR-206 sponge and is used as a novel biomarker for gastric cancer. Oncotarget. 2016;7:37812–24.

    PubMed  PubMed Central  Google Scholar 

  7. 7.

    Isin M, Dalay N. LncRNAs and neoplasia. Clin Chim Acta. 2015;444:280–8.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Du Z, Fei T, Verhaak RG, Su Z, Zhang Y, Brown M, et al. Integrative genomic analyses reveal clinically relevant long noncoding RNAs in human cancer. Nat Struct Mol Biol. 2013;20:908–13.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Li JL, Li ZL, Zheng WY, Li XH, Wang ZD, Cui YF, et al. LncRNA-ATB: An indispensable cancer-related long noncoding RNA. Cell Prolif. 2017;50(6):12381.

  10. 10.

    Rinn JL, Chang HY. Genome regulation by long noncoding RNAs. Annu Rev Biochem. 2012;81:145–66.

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    Ravasi T, Suzuki H, Pang KC, Katayama S, Furuno M, Okunishi R, et al. Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome. Genome Res. 2006;16:11–9.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Batista PJ, Chang HY. Long noncoding RNAs: cellular address codes in development and disease. Cell. 2013;152:1298–307.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Wang W, Zhuang Q, Ji K, Wen B, Lin P, Zhao Y, et al. Identification of miRNA, lncRNA and mRNA-associated ceRNA networks and potential biomarker for MELAS with mitochondrial DNA A3243G mutation. Sci Rep. 2017;7:41639.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Zhou M, Wang X, Shi H, Cheng L, Wang Z, Zhao H, et al. Characterization of long non-coding RNA-associated ceRNA network to reveal potential prognostic lncRNA biomarkers in human ovarian cancer. Oncotarget. 2016;7:12598–611.

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Zhou M, Diao Z, Yue X, Chen Y, Zhao H, Cheng L, et al. Construction and analysis of dysregulated lncRNA-associated ceRNA network identified novel lncRNA biomarkers for early diagnosis of human pancreatic cancer. Oncotarget. 2016;7:56383–94.

    PubMed  PubMed Central  Google Scholar 

  16. 16.

    Blackshaw S, Harpavat S, Trimarchi J, Cai L, Huang H, Kuo WP, et al. Genomic analysis of mouse retinal development. PLoS Biol. 2004;2:E247.

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Sone M, Hayashi T, Tarui H, Agata K, Takeichi M, Nakagawa S. The mRNA-like noncoding RNA Gomafu constitutes a novel nuclear domain in a subset of neurons. J Cell Sci. 2007;120:2498–506.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Ishii N, Ozaki K, Sato H, Mizuno H, Saito S, Takahashi A, et al. Identification of a novel non-coding RNA, MIAT, that confers risk of myocardial infarction. J Hum Genet. 2006;51:1087–99.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Ohnishi Y, Tanaka T, Yamada R, Suematsu K, Minami M, Fujii K, et al. Identification of 187 single nucleotide polymorphisms (SNPs) among 41 candidate genes for ischemic heart disease in the Japanese population. Hum Genet. 2000;106:288–92.

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    Mount SM. A catalogue of splice junction sequences. Nucleic Acids Res. 1982;10:459–72.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Shapiro MB, Senapathy P. RNA splice junctions of different classes of eukaryotes: sequence statistics and functional implications in gene expression. Nucleic Acids Res. 1987;15:7155–74.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Rapicavoli NA, Poth EM, Blackshaw S. The long noncoding RNA RNCR2 directs mouse retinal cell specification. BMC Dev Biol. 2010;10:49.

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Ryder SP, Williamson JR. Specificity of the STAR/GSG domain protein Qk1: implications for the regulation of myelination. RNA. 2004;10:1449–58.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Galarneau A, Richard S. Target RNA motif and target mRNAs of the quaking STAR protein. Nat Struct Mol Biol. 2005;12:691–8.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Tsuiji H, Yoshimoto R, Hasegawa Y, Furuno M, Yoshida M, Nakagawa S. Competition between a noncoding exon and introns: Gomafu contains tandem UACUAAC repeats and associates with splicing factor-1. Genes Cells. 2011;16:479–90.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Wang S, Fan Y, Feng X, Sun C, Shi Z, Li T, et al. Nicorandil alleviates myocardial injury and post-infarction cardiac remodeling by inhibiting Mst1. Biochem Biophys Res Commun. 2018;495(1):292–9.

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, et al. Heart disease and stroke Statistics-2017 update: a report from the American Heart Association. Circulation. 2017;135(10):e146–603.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Manabe I, Shindo T, Nagai R. Gene expression in fibroblasts and fibrosis: involvement in cardiac hypertrophy. Circ Res. 2002;91:1103–13.

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Dean RG, Balding LC, Candido R, Burns WC, Cao Z, Twigg SM, et al. Connective tissue growth factor and cardiac fibrosis after myocardial infarction. J Histochem Cytochem. 2005;53:1245–56.

    CAS  Article  PubMed  Google Scholar 

  30. 30.

    Yu CM, Tipoe GL, Wing-Hon Lai K, Lau CP. Effects of combination of angiotensin-converting enzyme inhibitor and angiotensin receptor antagonist on inflammatory cellular infiltration and myocardial interstitial fibrosis after acute myocardial infarction. J Am Coll Cardiol. 2001;38:1207–15.

    CAS  Article  PubMed  Google Scholar 

  31. 31.

    Vausort M, Wagner DR, Devaux Y. Long noncoding RNAs in patients with acute myocardial infarction. Circ Res. 2014;115:668–77.

    CAS  Article  PubMed  Google Scholar 

  32. 32.

    Qu X, Du Y, Shu Y, Gao M, Sun F, Luo S, et al. MIAT is a pro-fibrotic long non-coding RNA governing cardiac fibrosis in post-infarct myocardium. Sci Rep. 2017;7:42657.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Hachinski V, Donnan GA, Gorelick PB, Hacke W, Cramer SC, Kaste M, et al. Stroke: working toward a prioritized world agenda. Cerebrovasc Dis. 2010;30:127–47.

    Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Yue YH, Bai XD, Zhang HJ, Li YM, Hu L, Liu LY, et al. Gene polymorphisms affect the effectiveness of atorvastatin in treating ischemic stroke patients. Cell Physiol Biochem. 2016;39:630–8.

    CAS  Article  PubMed  Google Scholar 

  35. 35.

    Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Heart disease and stroke Statistics-2016 update: a report from the American Heart Association. Circulation. 2016;133:e38–360.

    Article  PubMed  Google Scholar 

  36. 36.

    Kim BJ, Lee SH, Ryu WS, Kim CK, Yoon BW. Adipocytokines and ischemic stroke: differential associations between stroke subtypes. J Neurol Sci. 2012;312:117–22.

    CAS  Article  PubMed  Google Scholar 

  37. 37.

    Zhu M, Li N, Luo P, Jing W, Wen X, Liang C, Tu J. Peripheral Blood Leukocyte expression of lncRNA MIAT and its diagnostic and prognostic value in ischemic stroke. J Stroke Cerebrovasc Dis. 2018;27(2):326–37.

  38. 38.

    Rössler W, Salize HJ, van Os J, Riecher-Rössler A. Size of burden of schizophrenia and psychotic disorders. Eur Neuropsychopharmacol. 2005;15:399–409.

    Article  PubMed  Google Scholar 

  39. 39.

    Small SA, Schobel SA, Buxton RB, Witter MP, Barnes CA. A pathophysiological framework of hippocampal dysfunction in ageing and disease. Nat Rev Neurosci. 2011;12:585–601.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Aprea J, Prenninger S, Dori M, Ghosh T, Monasor LS, Wessendorf E, et al. Transcriptome sequencing during mouse brain development identifies long non-coding RNAs functionally involved in neurogenic commitment. EMBO J. 2013;32:3145–60.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Barry G, Briggs JA, Vanichkina DP, Poth EM, Beveridge NJ, Ratnu VS, et al. The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing. Mol Psychiatry. 2014;19:486–94.

    CAS  Article  PubMed  Google Scholar 

  42. 42.

    Rao SQ, Hu HL, Ye N, Shen Y, Xu Q. Genetic variants in long non-coding RNA MIAT contribute to risk of paranoid schizophrenia in a Chinese Han population. Schizophr Res. 2015;166:125–30.

    Article  PubMed  Google Scholar 

  43. 43.

    Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65:87–108.

    Article  PubMed  Google Scholar 

  44. 44.

    Berman-Booty LD, Knudsen KE. Models of neuroendocrine prostate cancer. Endocr Relat Cancer. 2015;22:R33–49.

    CAS  Article  PubMed  Google Scholar 

  45. 45.

    Aggarwal R, Zhang T, Small EJ, Armstrong AJ. Neuroendocrine prostate cancer: subtypes, biology, and clinical outcomes. J Natl Compr Cancer Netw. 2014;12:719–26.

    Article  Google Scholar 

  46. 46.

    Wang HT, Yao YH, Li BG, Tang Y, Chang JW, Zhang J. Neuroendocrine prostate Cancer (NEPC) progressing from conventional prostatic adenocarcinoma: factors associated with time to development of NEPC and survival from NEPC diagnosis-a systematic review and pooled analysis. J Clin Oncol. 2014;32:3383–90.

    Article  PubMed  Google Scholar 

  47. 47.

    Crea F, Venalainen E, Ci X, Cheng H, Pikor L, Parolia A, et al. The role of epigenetics and long noncoding RNA MIAT in neuroendocrine prostate cancer. Epigenomics. 2016;8:721–31.

    CAS  Article  PubMed  Google Scholar 

  48. 48.

    Tan HL, Sood A, Rahimi HA, Wang W, Gupta N, Hicks J, et al. Rb loss is characteristic of prostatic small cell neuroendocrine carcinoma. Clin Cancer Res. 2014;20:890–903.

    CAS  Article  PubMed  Google Scholar 

  49. 49.

    Lugnani F, Simone G, Biava PM, Ablin RJ. The role of neuroendocrine cells in prostate cancer: a comprehensive review of current literature and subsequent rationale to broaden and integrate current treatment modalities. Curr Med Chem. 2014;21:1082–92.

    CAS  Article  PubMed  Google Scholar 

  50. 50.

    McGuire S. World Cancer report 2014. Geneva, Switzerland: World Health Organization, International Agency for Research on Cancer, WHO press, 2015. Adv Nutr. 2016;7:418–9.

    Article  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Li W, Sun M, Zang C, Ma P, He J, Zhang M, et al. Upregulated long non-coding RNA AGAP2-AS1 represses LATS2 and KLF2 expression through interacting with EZH2 and LSD1 in non-small-cell lung cancer cells. Cell Death Dis. 2016;7:e2225.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Zhang HY, Zheng FS, Yang W, Lu JB. The long non-coding RNA MIAT regulates zinc finger E-box binding homeobox 1 expression by sponging miR-150 and promoteing cell invasion in non-small-cell lung cancer. Gene. 2017;633:61–5.

    CAS  Article  PubMed  Google Scholar 

  53. 53.

    Zimmet PZ, Magliano DJ, Herman WH, Shaw JE. Diabetes: a 21st century challenge. Lancet Diabetes Endocrinol. 2014;2:56–64.

    Article  PubMed  Google Scholar 

  54. 54.

    Merovci A, Solis-Herrera C, Daniele G, Eldor R, Fiorentino TV, Tripathy D, et al. Dapagliflozin improves muscle insulin sensitivity but enhances endogenous glucose production. J Clin Invest. 2014;124:509–14.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Yan B, Yao J, Liu JY, Li XM, Wang XQ, Li YJ, et al. lncRNA-MIAT regulates microvascular dysfunction by functioning as a competing endogenous RNA. Circ Res. 2015;116:1143–56.

    CAS  Article  PubMed  Google Scholar 

  56. 56.

    Zhou X, Zhang W, Jin M, Chen J, Xu W, Kong X. lncRNA MIAT functions as a competing endogenous RNA to upregulate DAPK2 by sponging miR-22-3p in diabetic cardiomyopathy. Cell Death Dis. 2017;8:e2929.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Zhou L, Xu DY, Sha WG, Shen L, Lu GY, Yin X. Long non-coding MIAT mediates high glucose-induced renal tubular epithelial injury. Biochem Biophys Res Commun. 2015;468:726–32.

    CAS  Article  PubMed  Google Scholar 

  58. 58.

    Shen Y, Dong LF, Zhou RM, Yao J, Song YC, Yang H, et al. Role of long non-coding RNA MIAT in proliferation, apoptosis and migration of lens epithelial cells: a clinical and in vitro study. J Cell Mol Med. 2016;20:537–48.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  59. 59.

    Jin C, Zheng Y, Huang Y, Liu Y, Jia L, Zhou Y. Long non-coding RNA MIAT knockdown promotes osteogenic differentiation of human adipose-derived stem cells. Cell Biol Int. 2017;41:33–41.

    CAS  Article  PubMed  Google Scholar 

  60. 60.

    Frade AF, Laugier L, Ferreira LR, Baron MA, Benvenuti LA, Teixeira PC, et al. Myocardial infarction-associated transcript, a long noncoding RNA, is overexpressed during dilated cardiomyopathy due to chronic Chagas disease. J Infect Dis. 2016;214:161–5.

    CAS  Article  PubMed  Google Scholar 

  61. 61.

    Sattari A, Siddiqui H, Moshiri F, Ngankeu A, Nakamura T, Kipps TJ, ET AL. Upregulation of long noncoding RNA MIAT in aggressive form of chronic lymphocytic leukemias. Oncotarget. 2016;7:54174–82.

    Article  PubMed  PubMed Central  Google Scholar 

  62. 62.

    Tay Y, Rinn J, Pandolfi PP. The multilayered complexity of ceRNA crosstalk and competition. Nature. 2014;505:344–52.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Jiang Q, Shan K, Qun-Wang X, Zhou RM, Yang H, Liu C, et al. Long non-coding RNA-MIAT promotes neurovascular remodeling in the eye and brain. Oncotarget. 2016;7:49688–98.

    PubMed  PubMed Central  Google Scholar 

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This study was funded by National Natural Science Foundation of China (81602088), China Postdoctoral Science Foundation (2017 M621305), Health and Family Planning Commission Research Project of Heilongjiang Province (2016–049), Heilongjiang Postdoctoral Science Foundation (LBH-Z16096) and Innovative Science Foundation of Harbin Medical University (2016LCZX09).

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CS wrote the manuscript. LNH and ZLL collected and interpreted date. KML and YX analyzed date. XMJ and YFC corrected and reviewed the manuscript. All authors read and approved the final manuscript.

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Correspondence to Xingming Jiang or Yunfu Cui.

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Sun, C., Huang, L., Li, Z. et al. Long non-coding RNA MIAT in development and disease: a new player in an old game. J Biomed Sci 25, 23 (2018).

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  • Long non-coding RNA
  • LncRNA
  • MIAT
  • Diseases