Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis

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Contents lists available at ScienceDirect

www.ashi-hla.org

journal homepage: www.elsevier.com/locate/humimm

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Review

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Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis

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Ke Li a,1, Hongtao Tie b,1, Ning Hu a, Hong Chen a, Xinru Yin c, Chao Peng b, Jingyuan Wan c,⇑, Wei Huang a,⇑ a b c

Department of Orthopaedic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China The First College of Clinical Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China Chongqing Key Laboratory of Biochemistry and Molecular Pharmacology, Chongqing Medical University, Chongqing, China

a r t i c l e

i n f o

Article history: Received 18 October 2013 Accepted 6 May 2014 Available online xxxx Keywords: MicroRNA Polymorphisms Rheumatoid arthritis Meta-analysis

a b s t r a c t Background: It has been reported that two single nucleotide polymorphisms (SNPs) rs2910164 in miRNA146a and rs3746444 in miRNA-499 might be associated with the susceptibility to rheumatoid arthritis (RA). Owing to mixed and inconclusive results, we conducted a meta-analysis to systematically summarize and clarify the association between the two SNPs and RA risk. Methodology/main results: A systematic search of studies on the association of two SNPs with susceptibility to RA was conducted in PubMed and Embase. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to pool the effect size. A total of 6 case-control studies on rs2910164 and 3 studies on rs3746444 were included. Though no evidence of association was found between rs2910164 polymorphism and RA risk in all the genetic models, a trend of reduced risk could be drawn. (C versus G: OR = 0.93, 95% CI 0.82–1.05; GC versus GG: OR = 0.89, 95% CI 0.73–1.10; CC versus GG: OR = 0.84, 95% CI 0.64–1.10; GC/CC versus GG: OR = 0.89, 95% CI 0.73–1.08; CC versus GC/GG: OR = 0.94, 95% CI 0.77–1.14). A significant increased risk of RA was observed in the rs3746444 polymorphism in homozygote comparison, recessive comparison, and allele comparison, but there was insufficient data to fully confirm the association of RA and rs3746444 in miRNA-499. Conclusions: MiRNA-146a rs2910164 polymorphism is not associated with RA risk, while miRNA-499 rs3746444 polymorphism is correlated with RA risk. However, the results of miRNA-499 rs3746444 should be interpreted with caution due to limited sample and heterogeneity. Large-scale and welldesigned studies are needed to validate our findings. Ó 2014 Published by Elsevier Inc. on behalf of American Society for Histocompatibility and Immunogenetics.

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Contents 1. 2.

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3.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods and materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Identification of eligible studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Inclusion and exclusion criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Data extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Methodological quality assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5. Statistics analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Characteristics of studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Association between miRNA-146a rs2910164 polymorphism and RA susceptibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Association between miRNA-499 rs3746444 polymorphism and RA susceptibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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⇑ Corresponding authors. Tel.: +86 023 6848 5038; fax: +86 023 8613 4172 (J. Wan). Tel./fax: +86 023 8901 1212 (W. Huang). 1

E-mail addresses: [email protected] (J. Wan), [email protected] (W. Huang). These authors contributed equally to this work.

http://dx.doi.org/10.1016/j.humimm.2014.05.002 0198-8859/Ó 2014 Published by Elsevier Inc. on behalf of American Society for Histocompatibility and Immunogenetics.

Please cite this article in press as: Li K et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis. Hum Immunol (2014), http://dx.doi.org/10.1016/j.humimm.2014.05.002

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3.4. Sensitivity analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Publication bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction

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Rheumatoid arthritis (RA) is a systemic, chronic inflammatory disease that affects joints, which can develop in persons of any age. The prevalence of RA increases with age, affecting approximately 6% of the population over the age of 65 [1]. Untreated patients have a progressive course resulting in either short-term or long-term disability [2]. The main genetic factor of RA is the HLA-DRB1 gene, but the HLA genes only account for one-third of the genetic liability [3]. Recent years, many non-HLA genes have been identified to be associated with RA susceptibility [4]. Noncoding small RNAs, as an epigenetic regulation of gene expression, were reported to contribute to RA susceptibility [5]. MicroRNA (miRNA), a class of small, non-coding, singlestranded RNA, consists of approximately 22 nucleotides and possesses the post-transcriptional regulation via either mRNA degradation or translational repression [5]. MicroRNA is considered to play a crucial rule in gene expression, which can affect many activities in life, such as cell differentiation, proliferation, metabolism, apoptosis and tumorigenesis [6]. It functions by binding to the 30 -untranslated region (30 UTR) [7], 50 -untranslated region (50 UTR), promoter and even the coding sequences of the target mRNAs [8], subsequently, the target mRNA will be degraded or the transcription inhibited. A number of studies pointed out the alterations of miRNAs may play an important role in the pathogenesis of RA [9–11]. Single nucleotide polymorphisms (SNPs) occurring in the miRNA gene region may affect the property of miRNA through altering the miRNA expression and/or maturation [12]. An important polymorphism in the miR-146a rs2910164 was identified, and it had been confirmed that miR-146 rs2910164 was associated with higher cervical cancer, gastric cancer, cervical squamous cell carcinoma, esophageal squamous cell carcinoma, prostate cancer, etc. [13–15]. Recently, miR-146a was found to be overexpressed in synovial fibroblasts, synovial tissue, synovial fluid monocytes, peripheral blood mononuclear cells (PBMC), and serum plasma of RA patients [9]. Another polymorphism rs3746444 of miR-499 was also reported to be involved in RA risk [16]. Though, a number of studies have been conducted to investigate the association between the two SNPs and the risk of RA in diverse population [16–21], the results were mixed and inconclusive. Up to now, there is no meta-analysis investigating the association between them. Therefore, we performed a metaanalysis to evaluate the association between the two SNPs and RA risk.

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2. Methods and materials

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2.1. Identification of eligible studies

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Two independent investigators carried out a systematic search in PubMed and EMbase databases, with the last search update on July 1, 2013. The following terms were used: ‘‘microRNA OR miRNA OR microRNAs’’, ‘‘arthritis’’ and ‘‘polymorphism OR polymorphism’’, without any limitation applied. The reference lists of

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retrieved studies and recent reviews were also manually searched for further relevant studies.

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2.2. Inclusion and exclusion criteria

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Studies in this meta-analysis must meet the following inclusion criteria: (1) evaluation of the association between miR-146a/499 polymorphisms and the RA; (2) case-control study; (3) studies focusing on human being; (4) detailed genotype data could be acquired to calculate the odds ratios (ORs) and 95% confidence intervals (CIs); Exclusion criteria: (1) duplication of previous publications; (2) comment, review and editorial; (3) family-based studies of pedigrees; (4) study with no detailed genotype data. When there were multiple publications from the same population, only the largest study was included. Study selection was achieved by two investigators independently, according to the inclusion and exclusion criteria by screening the title, abstract and full-text. Any dispute was solved by discussion.

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2.3. Data extraction

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The data of the eligible studies were extracted in duplicate by two investigators independently (Li and Tie). The following contents were collected: name of first author, year of publication, the characteristics of cases and controls, country of origin, the detective sample, ethnicity, genotyping methods, the criteria of RA, Hardy–Weinberg equilibrium, number of cases and controls, genotype frequency in cases and controls for miR-146a and miR499 genotypes, respectively. Different ethnicity descents were classified as Caucasian and Asian. Two authors checked the extracted data and reached to consensus on all the data. If a dissent existed, they would recheck the original data of the included studies and have a discussion to reach consensus. If the dissent still existed, the third investigators would be involved to adjudicate the disagreements (Hu).

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2.4. Methodological quality assessment

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The qualities of the included studies were accessed by two authors respectively according to the methodological quality assessment scale (see Supplement information ‘‘Table S1 Scale Q2 for methodological quality assessment’’), which was adjusted from a previous publication [22]. In this scale, five items, including the representativeness of cases, source of controls, sample size, quality control of genotyping methods, Hardy–Weinberg equilibrium (HWE), were carefully checked. The quality score ranges from 0 to 10, and a high score means good quality of the study. Two investigators scored the studies independently and solved disagreement through discussion.

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2.5. Statistics analysis

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We conducted our meta-analysis according to the PRISMA checklists and followed the guideline [23]. Hardy–Weinberg equilibrium (HWE) was evaluated for each study by Chi-square test in

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Please cite this article in press as: Li K et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis. Hum Immunol (2014), http://dx.doi.org/10.1016/j.humimm.2014.05.002

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control groups, and P < 0.05 was considered a significant departure from HWE. OR and 95% CIs were calculated to evaluate the strength of the association between miR-146a/499 SNPs and susceptibility to RA. Pooled ORs were performed for allelic comparison (miR-146a: C versus G, miR-499: G versus A), heterozygote model (miR-146a: GC versus GG, miR-499: AG versus AA), homozygote model (miR-146a: CC versus GG miR-499: GG versus AA), dominant model (miR-146a: CC + GC versus GG, miR-499: AG + GG versus AA), recessive model (miR-146a: CC versus CG + GG miR499: GG versus AG + AA), respectively. The statistical significant level was determined by Z-test with P value less than 0.05. Heterogeneity was evaluated by Q statistic (significance level of P < 0.1) and I2 statistic(greater than 50% as evidence of significant inconsistency) [24]. Either fixed-effect or random effects model was used to pool the effect sizes [25] according to the heterogeneity. The studies without deviation from HWE among controls were used to do a supplementary meta-analysis. Sensitivity analysis was also performed to evaluate the effect of each study on the combined ORs by omitting each study in each turn. Besides, subgroup analyses were stratified by ethnicity. Potential publication bias was checked

by Begg’s funnel [26] plots and Egger’s regression test [27]. An asymmetric plot and the P value of Egger’s test less than 0.05 was considered a significant publication bias. All statistical analyses were performed with Stata 12.0 software (StataCorp, College Station, TX, USA). A two-tailed P < 0.05 was considered significant except for specified conditions, where a certain P value was declared.

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3. Results

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3.1. Characteristics of studies

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A total of 69 studies were acquired from PubMed and Embase databases (PubMed: 21, Embase: 48). The literature selection process was shown in Fig. 1. 59 articles were excluded, of which 14 were duplicate ones and 45 with no relation to this topic. The remaining ten studies were full-text reviewed, and four studies were excluded, among which, one had no relation to rheumatoid arthritis [28], one was not a case-control study [29], and the other

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Fig. 1. Flow Chart of study selection.

Table 1 Characteristics of studies included in the meta-analysis. Study ID

Year

miRNA-146a rs2910164 G>C Chatzikyriakidou et al. 2010 Yang et al. 2011 ´ enez-Morales et al. Jim 2012 Qian et al. 2012 El-Shal et al. 2013 HASHEMI et al. 2013 miRNA-499 rs3746444 A>G Yang et al. 2011 El-Shal et al. 2013 HASHEMI et al. 2013

Ethnicity

Case

P for HWE⁄

Quality

Greece China Mexican China Egypt Iran

Caucasian Asian Caucasian Asian Caucasian Caucasian

GG 73 28 102 16 30 57

GC 53 95 80 65 103 39

CC 10 85 28 42 84 8

GG 80 30 236 35 15 64

GC 53 116 229 109 119 37

CC 14 94 66 76 111 9

0.50 0.529 0.67 0.93 0.007 0.55

7 8 8 8 7 8

China Egypt Iran

Asian Caucasian Caucasian

AA 159 113 46

GA 42 93 32

GG 7 11 26

AA 182 167 74

GA 53 70 25

GG 5 8 11

GG 0.88 0.98 0.003

8 8 6

Country

Control

HWE: Hardy–Weinberg equilibrium.

Please cite this article in press as: Li K et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis. Hum Immunol (2014), http://dx.doi.org/10.1016/j.humimm.2014.05.002

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two were letters [30] and meeting report [31]. Finally, in the current study, 6 eligible case-control studies [16–21] that meet the inclusion criteria were included in our meta-analysis. The characteristics of each study were shown in the Table 1. In three studies [16,18,19], genotype frequencies of miR-146a rs2910164 and miR499 rs3746444 were presented separately, thus each of them were treated as separate studies. Therefore, all the six included studies containing 998 cases and 1,493 controls for miR146a rs2910164 and 3 studies involving 529 cases and 595 controls for miR499 rs3746444 were finally analyzed in our meta-analysis. For miRNA-146a rs2910164, the subjects in four included studies [17–20] were of Caucasian and the other two of Asian population [16,21]. As for miRNA-499 rs3746444, two studies were carried out in Caucasian [18,19] and the other one in Asian [16]. Different genotyping methods were utilized including polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP), TaqMan, polymerase chain reaction–ligation detection reaction (LDR–PCR) and T-ARMS-PCR. The genotyping distribution was in agreement with HWE in all studies except for one study [18] of

miRNA-146a rs2910164 and one study [19] of miRNA-499 rs3746444.

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3.2. Association between miRNA-146a rs2910164 polymorphism and RA susceptibility

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We firstly analyzed the association between miRNA-146a rs2910164 polymorphism and the susceptibility to RA No significant heterogeneity was identified by Q-test and I-squared statistic in any of the genetic models; therefore fixed-effects model was used. Overall, significant association was not identified in any genetic model (C versus G: OR = 0.93, 95% CI 0.82–1.05, PH = 0.465 Fig. 2; GC versus GG: OR = 0.89, 95% CI 0.73–1.10, PH = 0.180; CC versus GG: OR = 0.84, 95% CI 0.64–1.10, PH = 0.219; GC/CC versus GG: OR = 0.89, 95% CI 0.73–1.08, PH = 0.151; CC versus GC/GG: OR = 0.94, 95% CI 0.77–1.14, PH = 0.801), however, a Q3 trend of reduced risk could be seen (see Table 2). Next, subgroup analysis was conducted according to ethnicity. In Caucasians, significant statistical heterogeneity was identified

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Fig. 2. Forest plot of allele comparison of miRNA-146a rs2910164 for overall comparison (C versus G).

Table 2 Summary of polled ORs in the meta-analysis. N

OR

PH

OR

PH

OR

PH

OR

PH

OR

PH

miRNA-146a Overall Ethnicity Asian Caucasian

6

C/G 0.93(0.82–1.05)

0.465

GC/GG 0.89(0.73–1.10)

0.180

CC/GG 0.84(0.64–1.10)

0.219

CC + GC/GG 0.89(0.73–1.08)

0.151

CC/CG + GG 0.94(0.77–1.14)

0.801

2 4

1.03(0.84–1.27) 0.88(0.76–1.03)

0.380 0.366

1.04(0.68–1.62) 0.85(0.67–1.08)

0.380 0.101

1.06(0.68–1.67) 0.74(0.52–1.04)

0.637 0.151

1.06(0.70–1.60) 0.83(0.58–1.19)

0.457 0.079

1.04(0.77–1.39) 0.86(0.66–1.13)

0.772 0.697

miRNA-499 Overall Caucasian

3 2

G/A 1.62(1.02–2.59) 1.95(1.51–2.50)

0.010 0.152

AG/AA 1.22(0.89–2.61) 1.99(1.42–2.78)

0.025 0.901

GG/AA 2.59(1.52–4.42) 2.95(1.61–5.38)

0.406 0.319

AG + GG/AA 1.68(0.96–2.93) 2.15(1.57–2.94)

0.010 0.424

GG/AG + AA 2.17(1.29–3.66) 2.33(1.30–4.19)

0.507 0.297

Please cite this article in press as: Li K et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis. Hum Immunol (2014), http://dx.doi.org/10.1016/j.humimm.2014.05.002

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in the dominant model so that random-effects model was used. Fixed-effects model was used in other four genetic models. No association was found to be significant in any genetic models(C versus G: OR = 0.88, 95% CI 0.76–1.03, PH = 0.366; GC versus GG: OR = 0.85, 95% CI 0.67–1.08, PH = 0.101; CC versus GG: OR = 0.74, 95% CI 0.52–1.04, PH = 0.151; GC/CC versus GG: OR = 0.83, 95% CI 0.58–1.19, PH = 0.079; CC versus GC/GG: OR = 0.86, 95% CI 0.66– 1.13, PH = 0.697), a more obvious trend of reduced risk can be drawn. In Asians, homogeneity existed in all of the five genetic models, thus fixed-effects model was employed. No significant association was found either. (C versus G: OR = 1.03, 95% CI 0.84– 1.27, PH = 0.866; GC versus GG: OR = 1.04, 95% CI 0.68–1.62, PH = 0.380; CC versus GG: OR = 1.06, 95% CI 0.68–1.67, PH = 0.637; GC/CC versus GG: OR = 1.06, 95% CI 0.70–1.60, PH = 0.457; CC versus GC/GG: OR = 1.04, 95% CI 0.77–1.39, PH = 0.772). 3.3. Association between miRNA-499 rs3746444 polymorphism and RA susceptibility The association between miRNA-499 rs3746444 polymorphism and the risk of RA was analyzed in three independent studies. For the limited studies and heterogeneity, this result should be treated with caution. Random-effects model was used in the dominant model, heterozygote model, and allele model due to presence of heterogeneity, and Fixed-effects model was used in the other two models. A significant increased risk of RA was observed in homozygote comparison (GG versus AA: OR = 2.59, 95% CI 1.52–4.42, PH = 0.406), recessive comparison (GG versus AG/AA: OR = 2.17, 95% CI 1.29–3.66, PH = 0.507) and allele comparison (G versus A: OR = 1.62, 95% CI 1.02–2.59, PH = 0.010 Fig. 3). No significant association was found in heterozygote comparison (AG versus AA: OR = 1.22, 95% CI 0.89–2.61, PH = 0.025) or dominant comparison (AG/GG versus AA: OR = 1.68, 95% CI 0.96–2.93, PH = 0.010). However, a trend of increased susceptibility still existed. Two out of the three studies were carried out in Caucasian population. Subgroup analysis of Caucasian population was assessed, and significant statistical association was identified in

5

all the genetic models (G versus A: OR = 1.95, 95% CI 1.51–2.50, PH = 0.152; GG versus AA: OR = 2.95, 95% CI 1.61–5.38, PH = 0.319; GG versus AG/AA: OR = 2.33, 95% CI 1.30–4.19, PH = 0.297; AG versus AA: OR = 1.99, 95% CI 1.42–2.78, PH = 0.901; AG/GG versus AA: OR = 2.15, 95% CI 1.57–2.94, PH = 0.424).

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3.4. Sensitivity analysis

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Sensitivity analysis was performed to examine the influence set by the individual study on the pooled ORs for miRNA-146a rs2910164 by deleting each study once in every genetic model. Consistently, the pooled estimate remained no significant. As for miR-499 rs3746444, sensitivity analysis was also carried out by excluding one study [19], which was deviated from HWE. The pooled estimates of the remaining two studies showed no significant association in any genetic model.

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3.5. Publication bias

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No publication bias for the association between miRNA-146a rs2910164 and RA susceptibility was identified by Begg’s funnel plot (P = 0.707, C versus G) or Egger’s regression test (P = 0.430, C versus G). Symmetrical funnel plots were obtained in all the genetic models (Fig. 4C versus G). No funnel plot or Egger’s test were performed for the association between miRNA-499 rs3746444 and RA susceptibility owing to the limited number of included studies.

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4. Discussion

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In this meta-analysis, six eligible case-control studies including 998 cases and 1493 controls for miRNA-146a rs2910164 and three studies including 529 cases and 595 controls for miRNA-499 rs3746444 were analyzed. In consistent with a previous meta-analysis focused on autoimmune disease [32], no evidence was found for the association between miRNA-146a rs2910164 and RA susceptibility in any genetic models. Similar results were found in

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Fig. 3. Forest plot of allele comparison of miRNA-499 rs3746444 for overall comparison (G versus A).

Please cite this article in press as: Li K et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis. Hum Immunol (2014), http://dx.doi.org/10.1016/j.humimm.2014.05.002

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Fig. 4. Begg’s funnel plot for publication bias analysis for miRNA-146a polymorphism rs2910164 (C versus G).

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subgroup analysis by ethnicity and sensitivity analysis. As for association between miRNA-499 rs3746444 and RA susceptibility, a positive relationship between them was identified in homozygote, recessive, and allele models. Additionally, in Caucasian population, significant results were observed in all the genetic models. However, this finding should be interpreted with caution for limited sample heterogeneity. MiRNA could perform degradation or translational repression of target mRNA by binding to the 30 UTR, 50 UTR or even the coding sequences of the target mRNA [5]. It’s known that even a minor variation in miRNAs could have enormous effect on the expression of different target genes and thus lead to the susceptibility of several diseases including RA [33]. It is reported that increased expression of miRNAs have been detected in different cell types of RA patients, and miRNA-146a was shown to play a negative feedback in the immune response of RA [34]. miRNA-146a rs2710164 polymorphism was supposed to affect the expression level of miRNA-146a [13,14], which led to less efficient inhibition of target genes, including two important molecules for RA, IL-1 receptor-associated kinase 1 (IRAK1) and TNF receptor-associated factor 6 (TRAF6) [13], hence, miRNA146a rs2710164 could result in RA development. To our surprise, our results revealed no evidence of genetic association between miRNA-146a rs2910164 and the susceptibility to RA, Neither allele frequency nor genotype distribution showed significant association with the risk of RA. Since each mature miRNAs binds to a distinct set of target genes, different target genes can be affected by the miRNAs, When SNP occurs in miR-146a, it potentially generates 2 isoforms (marked ): miR-146aG from the allele carrying G, and miR-146aC from the C allele. Thus, GG and CC homozygotes each produce 2 subsets whereas GC heterozygotes, differing from both homozygotes, produce 3 mature miRNAs (miR-146a and both miR-146aG and miR-146aC). The production of distinct miRNAs and the regulation of different target genes by heterozygote compared to homozygote may explain this phenomenon [35]. As for miRNA-499, it can target IL-17 receptor B (IL-17RB), IL-6 and other cytokines, all of which play an important role in the pathogenesis of RA [36,37]. IL-17, a pro-inflammation cytokine, could induce the expression of TNF-a, IL-1b, IL-6, IL-23 and G-CSF. It was reported that IL-17 overexpressed in synovium, synovial fluid and PBMC in RA patients, and was considered as an important factor for RA pathogenesis [18]. Thus, there is a potential mechanism by which miRNA-499 rs3746444 could increase the risk of RA.

Significant heterogeneity was found for association of miRNA499 rs3746444 and RA in three genetic models. However, when we restricted the ethnicity to Caucasian, there was no heterogeneity existing, suggesting that ethnicity, to some extent, contributed to the source of heterogeneity. Though heterogeneity existed, our results remained stable, and the results became more significant in Caucasian. Additionally, no heterogeneity was identified for miRNA-146a rs2710164. The results from our subgroup and sensitivity analyses were consistent and robust. During the subgroup analysis, we found that ethnicity had no effect on the association between miRNA-146a rs2710164 and RA in any of the genetic models, suggesting miR146a rs2710164 was not associated with RA in either Asian or Caucasian. For miRNA-499 rs3746444, significant increased risk of RA was observed in homozygote, recessive and allele comparison. When focused on Caucasian population through subgroup analysis, positive association was observed in all the genetic models, while the study conducted in Han Chinese population showed no significant association in any of the genetic models. It can be explained by the different life styles, ethnicity, etc. As for sensitivity analysis of miRNA-146a rs2710164, although the included studies differed from one another in various aspects, the association could be driven by none of the single study. However, for miRNA-499 rs3746444, sensitivity analysis showed that the study with deviation from HWE conducted by Hashemi et al. could alter the association between miRNA-499 rs3746444 and RA. Nevertheless, a trend of increased susceptibility of RA still existed. Our meta-analysis has several strengths. First of all, this is the first meta-analysis focused on the association between miRNAs polymorphism and the susceptibility to rheumatoid arthritis. Compared with the former meta-analysis about autoimmune diseases [32], more studies were included and supplementary analysis including subgroup and sensitivity analysis were performed. Additionally, another miRNA polymorphism of miRNA-499 rs3746444 was also explored. In addition, all the included studies had high qualities according to the methodological quality assessment. Moreover, no publication bias was identified by either Begg’s funnel plot or Egger’s regression test. Finally, no limitation was made in literature search, thus selection bias was well controlled. In spite of the considerable efforts to explore the possible relationship between the two SNPs and RA risk, some limitations should be considered. Firstly, the number of included studies for miRNA-499 rs3746444 polymorphism limited further analysis due to shortage of original studies. Secondly, two studies did not conform to Hardy–Weinberg equilibrium expectations, of which one was for miRNA-146a rs2910164 and one for miRNA-499 rs3746444, separately. Though, when restricted to those who were in Hardy–Weinberg equilibrium, the pooled estimate of the association between miRNA-146a rs2910164 polymorphism and susceptibility of RA remained insignificant. Thirdly, heterogeneity was detected in some genetic models of rs3746444. Ethnicity and sample size might contribute to the heterogeneity. After omitting the study carried out in Chinese population, the pooled ORs became significant in all the genetic models without evidence of heterogeneity. In conclusion, our results suggested that miRNA-146a rs291 0164 polymorphism may not be associated with the susceptibility of RA, while miRNA-499 rs3746444 polymorphism is significantly associated with increased risk of RA, especially in Caucasians. However, there was insufficient data to fully confirm the association of RA and rs3746444 in miRNA-499, and the results should be interpreted with caution. Well-designed studies with larger sample size and more ethnic groups are required to validate the risk identified in the current meta-analysis.

Please cite this article in press as: Li K et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis. Hum Immunol (2014), http://dx.doi.org/10.1016/j.humimm.2014.05.002

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Acknowledgments Q4 This work was supported by grants from the National Natural Q6 Science Foundation of China (Nos. 81072650, 81373870). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Appendix A. Supplementary data

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Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.humimm.2014. 05.002.

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Please cite this article in press as: Li K et al. Association of two polymorphisms rs2910164 in miRNA-146a and rs3746444 in miRNA-499 with rheumatoid arthritis: A meta-analysis. Hum Immunol (2014), http://dx.doi.org/10.1016/j.humimm.2014.05.002

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