Back to Journals » Clinical Interventions in Aging » Volume 13

Association between polymorphisms in microRNAs and ischemic stroke in an Asian population: evidence based on 6,083 cases and 7,248 controls

Authors Zou DH, Liu CB, Zhang Q, Li XF, Qin G, Huang Q, Meng YS, Chen L, Wei JR

Received 13 May 2018

Accepted for publication 14 July 2018

Published 12 September 2018 Volume 2018:13 Pages 1709—1726

DOI https://doi.org/10.2147/CIA.S174000

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Dr Zhi-Ying Wu


Donghua Zou,1,* Chunbin Liu,1,* Qian Zhang,1 Xianfeng Li,1 Gang Qin,1 Qi Huang,1 Youshi Meng,1 Li Chen,2 Jinru Wei1

1Department of Stroke Center, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 2Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China

*These authors contributed equally to this work

Background: Polymorphisms in miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832) and miR-499 (rs3746444) have been associated with ischemic stroke (IS), but studies have given inconsistent results.
Methods: This meta-analysis investigated the possible association between IS risk and the four polymorphisms. A total of 14 case-control studies from Asian populations involving 6,083 cases and 7,248 controls for the four polymorphisms were included.
Results: Results showed that the GG genotype of miR-146a (rs2910164) may be associated with increased IS risk according to the recessive model (OR=1.20, 95% CI=1.02-1.42, P=0.03). Similarly, the CC genotype of miR-149 (rs2292832) may be associated with increased IS risk according to the recessive model (OR=1.28, 95% CI=1.08-1.52, P=0.005) and the homozygous model (OR=1.31, 95% CI=1.09-1.58, P=0.004). In contrast, miR-196a2 (rs11614913) and miR-499 (rs3746444) polymorphisms did not show significant association with IS risk in any of the five genetic models.
Conclusion: These results indicate that the GG genotype of miR-146a (rs2910164) and CC genotype of miR-149 (rs2292832) may confer increased susceptibility to IS, while miR-196a2 (rs11614913) and miR-499 (rs3746444) polymorphisms may not be associated with IS risk in Asian populations. These conclusions should be verified in large and well-designed studies.

Keywords: miRNAs, polymorphism, ischemic stroke, meta-analysis

Introduction

Stroke is a significant worldwide problem. An estimated 80% of the patients survive for at least 1 year after stroke, yet >70% have enduring disabilities.1,2 Ischemic stroke (IS) and intracerebral hemorrhage account for ~80%–85% and 15%–20% of all stroke cases, respectively.3 IS is a complex syndrome whose pathological development involves multiple components, which include environmental and genetic factors.4 Established environmental risk factors include age, sex, body mass index, hypertension, diabetes mellitus, smoking, and hyperlipidemia. However, recent studies suggested that genetics may contribute more than environment to IS, considering that a number of single-gene disorders are related to IS.58 Nevertheless, the factors defining genetic susceptibility to IS remain unclear.

MicroRNAs (miRNAs) represent a group of short non-coding RNA molecules, 18–25 nucleotides in length. Bioinformatics data indicate that a single miRNA can bind to as many as 200 gene targets, and miRNAs may regulate the expression of approximately one-third of protein-coding mRNAs. A single-nucleotide polymorphism (SNP) in miRNA may create a mismatch, leading to gene expression disorder and diseases.9 Evidence has indicated that miRNAs regulate various IS-related biological processes, such as atherosclerosis, hypertension, and plaque rupture.10 In fact, altered miRNA expression has been observed in IS in preclinical animal models and patients, suggesting a potential role in predicting the diagnosis and prognosis of IS.11,12

More specifically, the literature suggests an association between IS and polymorphisms in miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444).1326 However, these associations are controversial because individual studies relied on relatively small samples. Therefore, to obtain a more comprehensive understanding of the available evidence, we conducted this meta-analysis of 14 case–control studies to evaluate the possible association between IS risk and miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444) in Asian populations.

Materials and methods

Search strategy

All clinical and experimental case–control studies of miRNA polymorphisms and IS risk published through February 1, 2018 were identified through systematic searches in PubMed, EMBASE, Google Scholar, and the Chinese National Knowledge Infrastructure (CNKI) databases using English and Chinese. The search terms used were as follows: microRNA; miRNA; these two terms in combination with polymorphism, polymorphisms, SNP, variant, variants, variation, genotype, genetic, or mutation; and all the above-mentioned terms in combination with stroke or ischemic stroke. Reference lists in identified articles and reviews were also searched manually to identify additional eligible studies.

Inclusion criteria

To be included in our review and meta-analysis, studies had to 1) have a case–control design for assessing the association of IS risk with miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444); 2) be accessible as a full-text article and report sufficient data for estimating ORs with 95% CIs; 3) report genotype frequencies; and 4) involve humans rather than animal models.

Data extraction

Two authors (DHZ and CBL) independently extracted the following data from the included studies: first author’s family name, year of publication, ethnicity, testing methods, control source, age, sex, P-value for Hardy–Weinberg equilibrium (HWE) in controls, numbers and genotypes of cases and controls, and frequencies of genotypes in cases and controls. Discrepancies were resolved by consensus. Only those studies that met the predetermined inclusion criteria were included.

Assessment of methodological quality

To assess the quality of the studies included in this analysis, the Newcastle–Ottawa scale was used by two independent assessors (JRW and LC).27 For the Newcastle–Ottawa scale, a full score is nine stars; a score range of 5–9 stars is considered to indicate generally high methodological quality, whereas a range of 0–4 stars is considered to indicate poor quality.28 The quality of all the included studies is summarized in Table 1. Any disagreements about Newcastle–Ottawa scores were resolved by other authors following a comprehensive reassessment. Only high-quality studies were included in our meta-analysis.

Table 1 Methodological quality of the studies included in the final analysis based on the Newcastle–Ottawa scale for assessing the quality of case–control studies
Notes: aWhen there was no significant difference in the response rate between both groups based on a chi-squared test (P>0.05), one point was awarded. bTotal score was calculated by adding up the points awarded in each item.

Statistical analyses

The unadjusted OR with 95% CI was used to assess the strength of the association of IS risk with miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444) based on genotype frequencies in cases and controls. The significance of pooled ORs was determined using the Z-test, with P<0.05 defined as the significance threshold. Meta-analysis was conducted using a fixed-effect model when P>0.10 for the Q-test, indicating the lack of heterogeneity among studies; otherwise, a random-effect model was used. All these statistical tests were performed using Review Manager 5.2 (Cochrane Collaboration, Oxford, England).

Publication bias was assessed using Begg’s funnel plot and Egger’s weighted regression, with P<0.05 considered statistically significant. Begg’s funnel plots and Egger’s weighted regression were calculated using Stata 12.0 (StataCorp LP, College Station, TX, USA).

Results

Description of studies

Figure 1 is a flow diagram illustrating the process of searching for and selecting studies. A total of 184 potentially relevant publications up to February 1, 2018 were systematically identified through searches of the PubMed, EMBASE, Google Scholar, and CNKI databases in English and Chinese. Of these, we excluded 161 studies during initial screening based on review of the titles and abstracts. During analysis of the full text of the remaining articles, two studies were excluded for not being case–control studies, three studies were excluded because they did not report precise genotypes, and two articles were excluded because they investigated polymorphisms of miRNAs other than miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), or miR-499 (rs3746444). A further two studies were excluded because they were not written in English or Chinese.

Figure 1 Flowchart of study selection.

In the end, 14 studies1326 were included in this meta-analysis based on our search strategy and inclusion criteria. Their characteristics are summarized in Table 2. Of these, 13 studies13,14,1626 (Table 3) involving 5,726 cases and 7,175 controls evaluated the association between miR-146a (rs2910164) polymorphism and IS risk. Seven studies16,1820,2426 (Table 3) involving 3,090 cases and 3,047 controls evaluated the association between miR-196a2 (rs11614913) polymorphism and IS risk. Six studies1517,2426 (Table 3) involving 2,448 cases and 2,322 controls evaluated miR-149 (rs2292832) polymorphism and IS risk. The remaining seven studies16,18,20,2326 (Table 3) involving 3,082 cases and 3,044 controls evaluated miR-499 (rs3746444) polymorphism and IS risk. The distribution of genotypes in controls was consistent with HWE (P>0.05) in all but three studies.14,20,22 The overall quality of the included studies was adequate, and the mean Newcastle–Ottawa score for the included studies was 6.57 (Table 1).

Table 2 Characteristics of the studies included in the meta-analysis
Note: aThese data are expressed as median (25th, 75th quartiles).
Abbreviations: LDR, ligase detection reaction; PCR, polymerase chain reaction; RFLP, restriction fragment length polymorphism; SNP, single-nucleotide polymorphism.

Table 3 Genotype distributions of miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444)
Abbreviation: HWE, Hardy–Weinberg equilibrium.

Quantitative data synthesis

IS risk and miR-146a (rs2910164) polymorphism

The overall results for miR-146a (rs2910164) are summarized in Table 4 and Figure 2. On the basis of 5,726 cases and 7,175 controls from 13 studies,13,14,1626 the overall results indicated that the GG genotype of miR-146a (rs2910164) may be associated with increased IS risk according to the recessive model (OR=1.20, 95% CI=1.02–1.42, P=0.03; Figure 2B).

Table 4 Overall meta-analysis of the association between ischemic stroke and polymorphisms in miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444)

Figure 2 Forest plot describing the association between the miR-146a (rs2910164) polymorphism and ischemic stroke risk according to different genetic models: (A) allelic (G-allele vs C-allele), (B) recessive (GG vs GC+CC), (C) dominant (CC vs GC+GG), (D) homozygous (GG vs CC), and (E) heterozygous (GC vs CC).

IS risk and miR-196a2 (rs11614913) polymorphism

The overall results are summarized in Table 4 and Figure 3. On the basis of 3,090 cases and 3,047 controls from seven studies,16,1820,2426 miR-196a2 (rs11614913) polymorphism did not show significant association with IS risk in any of the following five genetic models: allelic model, OR=1.04, 95% CI=0.97–1.12, P=0.27 (Figure 3A); recessive model, OR=1.04, 95% CI=0.93–1.17, P=0.46 (Figure 3B); dominant model, OR=0.95, 95% CI=0.85–1.08, P=0.44 (Figure 3C); homozygous model, OR=0.95, 95% CI=0.85–1.08, P=0.44 (Figure 3D); and heterozygous model, OR=1.07, 95% CI=0.93–1.23, P=0.37 (Figure 3E).

Figure 3 Forest plot describing the association between the miR-196a2 (rs11614913) polymorphism and ischemic stroke risk according to different genetic models: (A) allelic, (B) recessive, (C) dominant, (D) homozygous, and (E) heterozygous.

IS risk and miR-149 (rs2292832) polymorphism

The overall results for miR-149 (rs2292832) are summarized in Table 4 and Figure 4. On the basis of 2,448 cases and 2,322 controls from six studies,16,18,20,2326 the overall results indicated that the CC genotype of miR-149 (rs2292832) may be associated with increased IS risk according to the recessive model (OR=1.28, 95% CI=1.08–1.52, P=0.005; Figure 4B) and homozygous model (OR=1.31, 95% CI=1.09–1.58, P=0.004; Figure 4D).

Figure 4 Forest plot describing the association between the miR-149 (rs2292832) polymorphism and ischemic stroke risk according to different genetic models: (A) allelic, (B) recessive, (C) dominant, (D) homozygous, and (E) heterozygous.

IS risk and miR-499 (rs3746444) polymorphism

The overall results are summarized in Table 4 and Figure 5. On the basis of 3,082 cases and 3,044 controls from seven studies,16,18,20,2326 miR-499 (rs3746444) polymorphism did not show significant association with IS risk in any of the following five genetic models: allelic model, OR=1.09, 95% CI=0.95–1.25, P=0.20 (Figure 5A); recessive model, OR=1.21, 95% CI=0.91–1.61, P=0.19 (Figure 5B); dominant model, OR=0.93, 95% CI=0.78–1.12, P=0.44 (Figure 5C); homozygous model, OR=1.20, 95% CI=0.90–1.60, P=0.21 (Figure 5D); or heterozygous model, OR=1.06, 95% CI=0.87–1.28, P=0.57 (Figure 5E).

Figure 5 Forest plot describing the association between the miR-149 (rs2292832) polymorphism and ischemic stroke risk according to different genetic models: (A) allelic, (B) recessive, (C) dominant, (D) homozygous, and (E) heterozygous.

Sensitivity analysis

Sensitivity analysis was conducted for miR-146a (rs2910164) by excluding the studies by Li et al14 and Qu et al;22 the P-value for HWE was less than 0.05 for these two studies. The recessive model gave different results (OR=1.19, 95% CI=0.98–1.45, P=0.07) than those obtained when all studies were meta-analyzed. Sensitivity analysis was conducted for miR-146a (rs2910164) by excluding one study by Jeon et al.16 Again, the recessive model gave different results (OR=1.18, 95% CI=0.99–1.41, P=0.07) than when all studies were included. Therefore, the results for miR-146a (rs2910164) should be interpreted with caution.

Sensitivity analysis was conducted for miR-196a2 (rs11614913) by excluding the study by Jeon et al.16 The results were similar to those obtained with all studies, regardless of the genetic model. This implies that our meta-analysis results for miR-196a2 (rs11614913) are robust. Similar robustness was observed when we performed sensitivity analysis for miR-149 (rs2292832) and for miR-499 (rs3746444) by excluding the study by Jeon et al.16

Sensitivity analysis was conducted for miR-499 (rs3746444) by excluding a study by Huang et al,20 in which the P-value of HWE was less than 0.05. The results were not altered in any of the five genetic models.

Publication bias

Begg’s funnel plot and Egger’s test were performed to detect potential publication bias in this meta-analysis. No obvious asymmetry was observed in Begg’s funnel plots in the recessive model, and Egger’s tests (Figure 6) indicated no publication bias.

Figure 6 Begg’s funnel plot and Egger’s test to assess publication bias in the meta-analysis of potential associations between ischemic stroke risk and (A and B) miR-146a (rs2910164), (C and D) miR-196a2 (rs11614913), (E and F) miR-149 (rs2292832), and (G and H) miR-499 (rs3746444).
Note: All analyses were performed using a recessive genetic model.

Discussion

Previous studies have demonstrated that mutations in the pre-miRNA of miR-146a, miR-499, miR-149, and miR-196a2 decrease the levels of the corresponding mature miRNAs.20,29,30 These four miRNAs affect thrombosis or inflammation pathways in the circulatory system by regulating tumor necrosis factor-α (TNF-α),31 methylenetetrahydrofolate reductase,32 annexin A1,33 C-reactive protein,34 the NF-κB pathway, and the MAP kinase pathway.35 Many studies have been conducted to reveal the impact of SNPs on precursor and mature miRNAs and their associations with IS risk.1326 In fact, several meta-analyses have been conducted to explore the association between miRNA polymorphisms and IS risk. The results have been inconsistent, largely due to limited sample size.3639 Therefore, we conducted this meta-analysis on all eligible studies to provide a more precise estimate of the association of IS risk with miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444). Interestingly, all the case–control studies in our meta-analysis analyzed Asian populations.

A previous meta-analysis by Zhu et al39 found the C allele of miR-146a (rs2910164) to be associated with lower IS risk, but this trend was observed only in Koreans according to the allelic model. Our meta-analysis, in contrast, suggests that this C allele is not significantly associated with IS risk; instead, we found the GG genotype of miR-146a (rs2910164) to be associated with increased risk. Our result may be more reliable than that of the previous meta-analysis by Zhu et al39 because our meta-analysis contained nine more case–control studies14,15,17,2126 with larger samples. Our subgroup analysis suggesting a significant relationship between the C allele of miR-146a (rs2910164) and lower IS risk contained only one case–control study, which was by Jeon et al.16

While the meta-analysis by Zhu et al39 reported an association between the A allele of miR-499 (rs3746444) and decreased IS risk in Chinese, our meta-analysis did not detect this association, either across Asian populations or specifically in the Chinese population (data not shown). Our result may be more reliable because our meta-analysis included four more case–control studies2326 than the one by Zhu et al.39 The results of our meta-analysis are consistent with those reported in the meta-analysis by Xiao et al.37

Our meta-analysis suggests a significant association between the CC genotype of miR-149 (rs2292832) and increased IS risk. In contrast, the meta-analysis of Xiao et al37 based on two case–control studies indicated that the TT genotype and T allele of miR-149 (rs2292832) are associated with significantly lower IS risk, whereas another meta-analysis36 based on three case–control studies found the CC genotype and C allele of miR-149 (rs2292832) to be significantly associated with IS risk. Our meta-analysis contained three more case–control studies2426 than either of these other meta-analyses, which may make it more reliable.

Our meta-analysis did not find a significant association between miR-196a2 (rs11614913) polymorphism and IS risk. This result confirms other meta-analyses3739 based on smaller samples.

To the best of our knowledge, the current meta-analysis involves the largest sample (6,083 cases and 7,248 controls) than previous studies3639 investigating the possible association of IS risk with miR-146a (rs2910164), miR-196a2 (rs11614913), miR-149 (rs2292832), and miR-499 (rs3746444) in Asian populations. Nevertheless, the meta-analysis is limited by the designs of the included studies. First, the P-value for HWE was less than 0.05 in two studies14,22 on miR-146a (rs2910164) and one study26 on miR-499 (rs3746444). These results suggested that these study populations may not be representative of the broader target population. Second, the results may be affected by both genetic and environmental factors, but most studies did not report environmental exposure, making it impossible to include them in the meta-analysis. Third, our exclusion of unpublished data and of papers published in languages other than English and Chinese may have biased our results. Fourth, the studies may be subject to performance bias, attrition bias, and reporting bias, although Newcastle–Ottawa scores were at least 5 for all 14 studies, indicating high quality. Fifth, stroke is a heterogeneous disease and has different subtypes that may affect the results of genetic association studies, but most case–control studies in our meta-analysis appeared not to use a well-phenotyped population. This may make the results less accurate. Finally, all the patients in this meta-analysis were Asian and this may limit the relevance of the results to other populations. Thus, more large and well-designed studies are warranted in non-Asian populations.

Conclusion

This meta-analysis suggests that the GG genotype of miR-146a (rs2910164) and the CC genotype of miR-149 (rs2292832) may confer increased susceptibility to IS in Asian populations, whereas polymorphism in miR-196a2 (rs11614913) and miR-499 (rs3746444) may not be associated with IS risk. These conclusions should be verified in large and well-designed studies.

Acknowledgments

This study was supported by grants from the Natural Science Foundation of China (81560205 and 81760217), the Guangxi Natural Science Foundation (2016GXNSFCA380012 and 2017GXNSFAA198135), the Guangxi Colleges and Universities Science and Technology Research Project (KY2015ZD030), the Project of Nanning Scientific Research and Technology Development Plan (20163142), and the Scientific Research Project of Guangxi Health and Family Planning Commission (Z20170001) and China Scholarship Council (201708455059).

Author contributions

The study was designed by JRW and LC. The research was performed by DHZ, CBL, and QZ. Statistical analyses were performed by XFL, GQ, QH, and YSM. The manuscript was written by DHZ. All authors contributed toward data analysis, drafting and critically revising the paper and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.


References

1.

Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics – 2012 update: a report from the American Heart Association. Circulation. 2012;125(1):e2–e220.

2.

Lo AC, Guarino P, Krebs HI, et al. Multicenter randomized trial of robot-assisted rehabilitation for chronic stroke: methods and entry characteristics for VA ROBOTICS. Neurorehabil Neural Repair. 2009;23(8):775–783.

3.

Norrving B, Kissela B. The global burden of stroke and need for a continuum of care. Neurology. 2013;80(3 Suppl 2):S5–S12.

4.

Dichgans M. Genetics of ischaemic stroke. Lancet Neurol. 2007;6(2):149–161.

5.

Holliday EG, Maguire JM, Evans TJ, et al. Common variants at 6p21.1 are associated with large artery atherosclerotic stroke. Nat Genet. 2012;44(10):1147–1151.

6.

International Stroke Genetics Consortium (ISGC), Wellcome Trust Case Control Consortium 2 (WTCCC2), Bellenguez C, Bevan S, Gschwendtner A, et al. Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke. Nat Genet. 2012;44(3):328–333.

7.

Hachiya T, Kamatani Y, Takahashi A, et al. Genetic predisposition to ischemic stroke. Stroke. 2017;48(2):253–258.

8.

Malik R, Chauhan G, Traylor M, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018;50(4):524–537.

9.

Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120(1):15–20.

10.

Rink C, Khanna S. MicroRNA in ischemic stroke etiology and pathology. Physiol Genomics. 2011;43(10):521–528.

11.

Ambros V. The functions of animal microRNAs. Nature. 2004;431(7006):350–355.

12.

Tan KS, Armugam A, Sepramaniam S, et al. Expression profile of MicroRNAs in young stroke patients. PLoS One. 2009;4(11):e7689.

13.

Sun J. Association of miRNA-146a and EPHX2 Polymorphisms with Risk of Ischemic Stroke in Changsha Han Population and the Mechanisms [master’s thesis]. Changsha, Hunan Province, China: Central South University; 2011.

14.

Li L. Association of miRNA-146a Polymorphism with Risk of Cardiovascular Disease and Ischemia Stroke and the Mechanisms [master’s thesis]. Changsha, Hunan Province, China: Central South University; 2010.

15.

He S, Han Y. Association between miR-149 polymorphism and ischemic stroke of Han population in Hanzhong of Shanxi. J Mod Lab Med. 2013;2834:3238.

16.

Jeon YJ, Kim OJ, Kim SY, et al. Association of the miR-146a, miR-149, miR-196a2, and miR-499 polymorphisms with ischemic stroke and silent brain infarction risk. Arterioscler Thromb Vasc Biol. 2013;33(2):420–430.

17.

Hu Y, Li S, Jiang X, et al. Study on the association of miR-146aC> G, miR-149 T> C polymorphism with susceptibility to ischemic stroke. Prog Mod Biomed. 2014;14:5648–5651.

18.

Liu Y, Ma Y, Zhang B, Wang SX, Wang XM, Yu JM. Genetic polymorphisms in pre-microRNAs and risk of ischemic stroke in a Chinese population. J Mol Neurosci. 2014;52(4):473–480.

19.

Zhu R, Liu X, He Z, Li Q. miR-146a and miR-196a2 polymorphisms in patients with ischemic stroke in the northern Chinese Han population. Neurochem Res. 2014;39(9):1709–1716.

20.

Huang S, Zhou S, Zhang Y, et al. Association of the genetic polymorphisms in pre-microRNAs with risk of ischemic stroke in a Chinese population. PLoS One. 2015;10(2):e0117007.

21.

Zhong H, Cai Y, Cheng J, et al. Apolipoprotein E Epsilon 4 enhances the association between the rs2910164 polymorphism of mir-146a and risk of atherosclerotic cerebral infarction. J Atheroscler Thromb. 2016;23(7):819–829.

22.

Qu JY, Xi J, Zhang YH, et al. Association of the microRNA-146a SNP rs2910164 with ischemic stroke incidence and prognosis in a chinese population. Int J Mol Sci. 2016;17(5):660.

23.

Lyu G, Wang S, Wang Q. Association of miR-146a rs2910164 and miR-499 rs3746444 polymorphisms with risk of ischemic stroke. New Med. 2016;47:257.

24.

Zhu X. Association of miRNAs and MTHFR Gene Polymorphisms with Ischemic Stroke in the Chinese Han Population [Ph.D. thesis]. Qingdao, Shandong Province, China: Qingdao University; 2016.

25.

Luo HC, Luo QS, Wang CF, Lei M, Li BL, Wei YS. Association of miR-146a, miR-149, miR-196a2, miR-499 gene polymorphisms with ischemic stroke in a Chinese people. Oncotarget. 2017;8(46):81295.

26.

Zhu H, Zhang H, Bao L, Dai M. Analysis of association of genetic polymorphisms of microRNAs with ischemic stroke. Chin J Med Genet. 2017;34:261–265.

27.

Wells GA, Shea B, O’connell D, et al. Newcastle-Ottawa Scale (NOS) for Assessing the Quality of NonranStudies in Meta-analyses. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm. Available in March, 2016.

28.

Ownby RL, Crocco E, Acevedo A, John V, Loewenstein D. Depression and risk for Alzheimer disease: systematic review, meta-analysis, and metaregression analysis. Arch Gen Psychiatry. 2006;63(5):530–538.

29.

Shen J, Ambrosone CB, Dicioccio RA, Odunsi K, Lele SB, Zhao H. A functional polymorphism in the miR-146a gene and age of familial breast/ovarian cancer diagnosis. Carcinogenesis. 2008;29(10):1963–1966.

30.

Hoffman AE, Zheng T, Yi C, et al. microRNA miR-196a-2 and breast cancer: a genetic and epigenetic association study and functional analysis. Cancer Res. 2009;69(14):5970–5977.

31.

El Gazzar M, Church A, Liu T, Mccall CE. MicroRNA-146a regulates both transcription silencing and translation disruption of TNF-α during TLR4-induced gene reprogramming. J Leukoc Biol. 2011;90(3):509–519.

32.

Wu C, Gong Y, Sun A, et al. The human MTHFR rs4846049 polymorphism increases coronary heart disease risk through modifying miRNA binding. Nutr Metab Cardiovasc Dis. 2013;23(7):693–698.

33.

Luthra R, Singh RR, Luthra MG, et al. MicroRNA-196a targets annexin A1: a microRNA-mediated mechanism of annexin A1 downregulation in cancers. Oncogene. 2008;27(52):6667–6678.

34.

Yang B, Chen J, Li Y, et al. Association of polymorphisms in pre-miRNA with inflammatory biomarkers in rheumatoid arthritis in the Chinese Han population. Hum Immunol. 2012;73(1):101–106.

35.

Cheng HS, Sivachandran N, Lau A, et al. MicroRNA-146 represses endothelial activation by inhibiting pro-inflammatory pathways. EMBO Mol Med. 2013;5(7):1017–1034.

36.

du J, Cui C, Zhang S, Yang X, Lou J. Association of microRNA-146a and microRNA-149 polymorphisms with strokes in asian populations: an updated meta-analysis. Angiology. 2017;68(10):863–870.

37.

Xiao Y, Bao MH, Luo HQ, Xiang J, Li JM. A Meta-analysis of the association between polymorphisms in microRNAs and risk of ischemic stroke. Genes. 2015;6(4):1283–1299.

38.

Qin B, Zheng Y, Zhang W, et al. Lack of associations between rs2910164 and rs11614913 polymorphisms and the risk of ischemic stroke. Int J Clin Exp Med. 2015;8(10):18359–18366.

39.

Zhu J, Yue H, Qiao C, Li Y. Association between single-nucleotide polymorphism (SNP) in miR-146a, miR-196a2, and miR-499 and risk of ischemic stroke: a meta-analysis. Med Sci Monit. 2015;21:3658–3663.

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]