BioMed Research International
Volume 2019 (2019), Article ID 7305750, 9 pages
https://doi.org/10.1155/2019/7305750

Research Article

Association of rs2910164 Polymorphism in miRNA-146 and rs3746444 Polymorphism in miRNA-499 with Inflammatory Arthritis: A Meta-Analysis

Dingjian Wang and Guixia Pan

Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui 230032, China

Correspondence should be addressed to Guixia Pan; pgxkd@163.com

Received 14 March 2019; Accepted 23 April 2019; Published 16 May 2019

Academic Editor: Salvatore Gallone

Copyright © 2019 Dingjian Wang and Guixia Pan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Objectives. The purpose of this study was to explore the association of miRNA-146 and miRNA-499 polymorphisms with inflammatory arthritis. Methods. A systematic search of studies on the association of miRNA-146 and miRNA-499 polymorphisms with inflammatory arthritis susceptibility was conducted in PubMed, Web of science, Elsevier ScienceDirect, and Cochrane Library. Eventually, 18 published studies were included. The strength of association between miRNA-146/499 polymorphisms and inflammatory arthritis susceptibility was assessed by odds ratios (ORs) with its 95% confidence intervals (CIs). Results. A total of 18 case-control studies, consisting of 3385 inflammatory arthritis patients and 4584 controls, were included in the meta-analysis. This meta-analysis showed significant association between miRNA-499 rs3746444 polymorphism and inflammatory arthritis susceptibility in overall population (C vs T, OR: 1.422, 95% CI= 1.159-1.745, P=0.001). Similar results were found in subgroup analysis by region. But we did not find association between miRNA-146 rs2910164 polymorphism and inflammatory arthritis susceptibility in overall population (C vs T, OR: 1.061, 95% CI= 0.933-1.207, P=0.365). Conclusions. The present study indicates that miRNA-499 rs3746444 polymorphism is associated with inflammatory arthritis susceptibility. However, there is lack of association between miRNA-146 rs2910164 polymorphism and inflammatory arthritis susceptibility. But, we also find miRNA-146 rs2910164 and miRNA-499 rs3746444 polymorphism are associated with inflammatory arthritis in Middle East. Therefore, more large-scale studies are warranted to replicate our findings.

1. Introduction

Inflammatory arthritis is a group of complex diseases, including rheumatoid arthritis (RA), psoriatic arthritis (PsA), juvenile idiopathic arthritis (JIA), etc. And it is characterized by inflammatory cell infiltration into the joints [1, 2]. There is no doubt that environmental factors and genetic factors play an important role in the development of inflammatory arthritis.

MicroRNAs (miRNAs) are small noncoding RNAs, which are about 22 nucleotides long. They play an important role in regulating transcription and translation [3–6]. Some studies indicated that they also participate in cell proliferation, differentiation, and apoptosis [7, 8]. And, miRNAs can cause the degradation or translation repression of their target miRNA by binding to the 3′-untranslated region of specific mRNAs (messenger RNAs) [9–12]. Recently, some studies reported that miRNA may associate with inflammatory arthritis, such as miRNA-146 rs2910164 and miRNA-499 rs3746444. Therefore, we chose miRNA-146 rs2910164 and miRNA-499 rs3746444 to explore the association between its polymorphisms and inflammatory arthritis.

MiRNA-146 is located on human chromosome 5q34 and related to immune regulation, inflammatory signaling pathway, because it can regulate the expression of IL-1 receptor-associated kinase (IRAK1) and IRAK2 and targets TNF receptor-associated factor 6 (TRAF6) [13]. And, miRNA-499 is related to the expression of Interleukin-17 receptor B (IL-17RB), IL-2RB, IL-6, B and T lymphocyte attenuator (BTLA), and peptidyl arginine deiminase 4 (PADI4) [14]. Both miRNA-146 and miRNA-499 are thought to be involved in autoimmune and inflammatory diseases [15].

Considering the results of miRNA-146 and miRNA-499 polymorphisms with inflammatory arthritis are inconsistent [16–20], this discrepancy might be caused by some studies that have small sample size, low statistical power, ethnicity differences, and publication bias. It is necessary to conduct meta-analysis to explore this association.

2. Methods

2.1. Search Strategy

A systematic search of studies on the association of miRNA-146 and miRNA-499 polymorphisms with inflammatory arthritis susceptibility was conducted in PubMed, Web of science, Elsevier ScienceDirect, and Cochrane Library. Keywords for the search were as follows: (“microRNA” or “miRNA” or “microRNAs”) and (“Inflammatory arthritis”) and (“polymorphism” or “variant” or “genotype” or “SNP” or “mutations”). All relevant studies were retrieved. We screened those studies by reading its titles, abstracts, and contents carefully.

2.2. Eligibility Criteria

The inclusion criteria were (i) studies involving the association between miRNA gene polymorphisms and inflammatory arthritis; (ii) case-control study; (iii) studies based on human; (iv) studies providing the detailed relevant genotype data of both case group and control group. Studies were excluded if (i) the study was a review, editorial, abstract, case report, or unpublished article; (ii) studies were nonhuman studies or animal experiments or cell experiments; (iii) studies had no controls or no detailed relevant genotype data.

2.3. Data Extraction

The data of the eligible studies were extracted by one investigator (Mr.Wang). The following information were collected: first author’s name; year of publication; type of disease; country; region; genotyping methods; number of cases and controls in each study; characteristics of controls; category of polymorphisms and other additional information.

2.4. Quality Assessment

The included studies in this meta-analysis were evaluated by another inspector (Pan). The quality assessment was based on the modified Newcastle-Ottawa Quality Assessment Scale (NOS). The scale consists of eight multiple-choice questions that involve subjects' selection, comparability in cases and controls, and assessment of exposure. High-quality response earns a point, totaling up to nine points (the comparability question earns up to two points). The higher score indicates better quality.

2.5. Statistical Analysis

All statistical analyses were performed by Stata 12.0 (StataCorp, College Station, TX, USA) software. OR and 95% CI were used to evaluate the strength of association between miRNA-146/499 polymorphisms with inflammatory arthritis susceptibility under different genetic models. The effect of heterogeneity was evaluated using statistics. Heterogeneity was recognized as statistically significant when %. According to the value of , we chose fixed-effects or random-effects model. All subgroups were analyzed. Sensitivity analysis was used to evaluate the influence of individual study on the overall OR. Publication bias was assessed by Funnel’s plot, Begg’s test and Egger’s test. An asymmetric plot and the value of Egger’s test or Begg’s test less than 0.05 were considered as significant publication bias.

3. Results

3.1. Literature Search

A total of 390 studies were retrieved from PubMed, Web of science, Elsevier Science Direct and Cochrane Library. Finally, 18 eligible studies were included in this meta-analysis. A flowchart of the included and excluded studies was shown in Figure 1.

Figure 1: A flowchart of the included and excluded studies.

3.2. Characteristics of the Included Studies

Table 1 showed the main features of those included studies. Those studies were all English articles, which have been published from 2010 to 2018. All studies included in this meta-analysis were case-control studies. Eighteen studies involving 3385 inflammatory arthritis patients and 4584 controls were included in this meta-analysis.

Table 1: The main features of included studies.

Author
Year
Disease
Country
Region
Genotyping methods
Number of Cases
Number of controls
Characteristics of controls
Polymorphisms
NOS score

Chatzikyriakidou A
2010
RA
Greece
Europe
PCR–RFLP
136
147
Healthy
rs2910164(miRNA-146)
6

Yang XK
2016
RA
China
Asia
TaqMan
386
576
Healthy
rs3746444(miRNA-499)
7

Singh S
2014
JIA-ERA
India
Asia
PCR–RFLP
150
216
Healthy
rs2910164(miRNA-146)
7

El-Shal AS
2013
RA
Egypt
Middle East
PCR–RFLP
217
245
Healthy
rs2910164(miRNA-146),
rs3746444(miRNA-499)
6

Shaker OG
2018
RA
Egypt
Middle East
TaqMan
104
112
Healthy
rs2910164(miRNA-146),
rs3746444(miRNA-499)
7

Hashemi M
2012
RA
Iran
Middle East
T-ARMS-PCR
104
110
Healthy
rs2910164(miRNA-146),
rs3746444(miRNA-499)
6

Yang B
2010
RA
China
Asia
PCR–RFLP
208
240
Healthy
rs2910164(miRNA-146),
rs3746444(miRNA-499)
7

Aleman-Avila I
2017
RA
Mexico
North America
TaqMan
412
486
Healthy
rs2910164(miRNA-146),
rs3746444(miRNA-499),
rs11614913(miRNA-196)
7

Zhou X
2015
RA
China
Asia
NA
598
821
NA
rs2910164(miRNA-146)
5

Hassine HB
2017
RA
Tunisia
Middle East
PCR–RFLP
165
150
Healthy
rs2910164(miRNA-146)
6

Maharaj AB(1)
2018
PsA
South Africa
Africa
PCR–RFLP
84
62
Healthy
rs2910164(miRNA-146)
6

Maharaj AB(2)
2018
PsA
South Africa
Africa
PCR–RFLP
32
38
Healthy
rs2910164(miRNA-146)
6

Jimenez-Morales S
2012
JRA
Mexico
North America
TaqMan
210
531
Healthy
rs2910164(miRNA-146)
7

Ciccacci C
2016
RA
Italy
Europe
TaqMan
192
298
Healthy
rs2910164(miRNA-146)
7

Ayeldeen G
2018
RA
Egypt
Middle East
real-time PCR
52
56
Healthy
rs2910164(miRNA-146),
rs3746444(miRNA-499)
6

Toraih EA
2016
RA
Egypt
Middle East
TaqMan
95
200
Healthy
rs3746444(miRNA-499),
rs11614913(miRNA-196)
6

Fattah SA
2018
RA
Egypt
Middle East
PCR–RFLP
100
100
Healthy
rs3746444(miRNA-499)
6

Bogunia-Kubik K
2016
RA
Poland
Europe
PCR–RFLP
111
130
Healthy
rs2910164(miRNA-146)
6

Chatzikyriakidou A
2010
PsA
Greece
Europe
PCR–RFLP
29
66
NA
rs2910164(miRNA-146)
6

HWE: Hardy–Weinberg equilibrium; NOS: Newcastle-Ottawa Quality Assessment Scale.

3.3. Meta-Analysis of Association between miRNA-146 rs2910164 Polymorphism and Inflammatory Arthritis

Meta-analysis indicated that there is lack of association between miRNA-146 rs2910164 polymorphism and inflammatory arthritis susceptibility in the overall population (G vs C, OR: 1.061, 95% CI= 0.933-1.207, P=0.365; GC+CC vs GG, OR: 0.919, 95% CI=0.762-1.110, P=0.381; CC vs GG+GC, OR: 0.935, 95% CI=0.821-1.065, P=0.310). After stratifying by region, it only showed the association between miRNA-146 rs2910164 polymorphism and inflammatory arthritis susceptibility in Middle East (Figure 2). This may be due to the differences in geographic region, ethnicity, and sample size.

Figure 2: The forest plot about association between miRNA-146 rs2910164 and inflammatory arthritis under allelic model (G vs C).

3.4. Meta-Analysis of Association between miRNA-499 rs3746444 Polymorphism and Inflammatory Arthritis

Meta-analysis indicated significant association between miRNA-499 rs3746444 polymorphism and inflammatory arthritis susceptibility in the overall population (C vs T, OR: 1.422, 95% CI= 1.159-1.745, P=0.001; TC +CC vs TT, OR: 1.409, 95% CI=1.072-1.852, P=0.014; CC vs TT+TC, OR: 1.872, 95% CI=1.420-2.467, P<0.001). After stratifying by region, the association between miRNA-499 rs3746444 polymorphism and inflammatory arthritis susceptibility was still extant in Middle East (Figure 3). But, we did not find this association in Asia and North America.

Figure 3: The forest plot about association between miRNA-499 rs3746444 and inflammatory arthritis under allelic model (C vs T).

3.5. Heterogeneity and Publication Bias

The results of heterogeneity test were shown in Table 2. And the results of Begg’s test and Egger’s test were also shown in Table 2. As for some studies that had heterogeneity (%), the random-effects models were performed; others were analyzed by fixed-effects model. As for miRNA-499 rs3746444 polymorphism, the plot of sensitivity analysis was shown in Figure 4. And there was no significant evidence of publication bias found in the meta-analysis.

Table 2: The results of meta-analysis, heterogeneity test, and publication bias.

polymorphism
Number of studies
Comparable genotype
No. of Cases/Controls
Test of association
Test of heterogeneity
Test of publication bias
Model

Begg’s test
Egger’s test

OR (95%CI)
P
I²
PH
Z
P
t
P

rs2910164
(miRNA-146)

Overall
16
G vs C
2802/3708
1.061(0.933-1.207)
0.365
58.80%
0.002
0.14
0.893
0.60
0.559
R

Region

Europe
4
G vs C
468/641
1.017(0..836-1.236)
0.868
0.00%
0.753
1.02
0.308
-2.93
0.100
F

Asia
3
G vs C
956/1277
0.991(0.877-1.120)
0.890
0.00%
0.412
1.04
0.296
-1.89
0.309
F

Middle East
5
G vs C
642/673
1.449(1.229-1.709)
0.001
47.30%
0.108
0.24
0.806
0.53
0.630
F

Africa
2
G vs C
116/100
0.615(0.405-0.935)
0.023
0.50%
0.316
0.00
1.000
NA
NA
F

North America
2
G vs C
620/1017
0.955(0.820-1.111)
0.551
36.40%
0.210
0.00
1.000
NA
NA
F

HWE

Y
13
G vs C
2524/3359
1.053(0.916-1.211)
0.469
61.90%
0.002
0.18
0.855
0.99
0.344
R

Overall
16
GC+CC
vs GG
2802/3708
0.919(0.762-1.110)
0.381
57.20%
0.002
-0.05
1.000
0.05
0.963
R

Region

Europe
4
GC+CC
vs GG
468/641
1.000(0.784-1.276)
0.998
0.00%
0.606
1.70
0.089
13.66
0.005
F

Asia
3
GC+CC
vs GG
956/1277
0.980(0.795-1.209)
0.851
0.00%
0.869
0.00
1.000
0.16
0.896
F

Middle East
5
GC+CC vs GG
642/673
0.530(0.320-0.877)
0.014
64.30%
0.024
0.73
0.462
-0.99
0.394
R

Africa
2
GC+CC vs GG
116/100
1.915(1.107-3.314)
0.020
49.40%
0.160
0.00
1.000
NA
NA
F

North America
2
GC+CC vs GG
620/1017
1.009(0.735-1.385)
0.956
57.20%
0.127
0.00
1.000
NA
NA
R

HWE

Y
13
GC+CC vs GG
2524/3359
0.942(0.780-1.137)
0.532
55.80%
0.007
0.06
0.951
0.02
0.982
R

Overall
16
CC vs GG+GC
2802/3708
0.935(0.821-1.065)
0.310
34.60%
0.086
1.22
0.224
0.98
0.343
F

Region

Europe
4
CC vs GG+GC
468/641
0.914(0.581-1.439)
0.699
0.00%
0.839
-0.34
1.000
0.23
0.837
F

Asia
3
CC vs GG+GC
956/1277
1.149(0.803-1.645)
0.447
59.10%
0.087
1.04
0.296
2.69
0.227
R

Middle East
5
CC vs GG+GC
642/673
0.631(0.483-0.823)
0.001
0.00%
0.431
0.24
0.806
-0.60
0.590
F

Africa
2
CC vs GG+GC
116/100
2.211(0.674-7.256)
0.191
0.00%
0.581
0.00
1.000
NA
NA
F

North America
2
CC vs GG+GC
620/1017
1.151(0.837-1.582)
0.387
0.00%
0.739
0.00
1.000
NA
NA
F

HWE

Y
13
CC vs GG+GC
2524/3359
0.959(0.834-1.103)
0.556
40.20%
0.066
0.55
0.583
0.37
0.722
F

rs3746444
(miRNA-499)

Overall
9
C vs T
1678/2125
1.422(1.159-1.745)
0.001
63.30%
0.005
1.15
0.251
1.30
0.234
R

Region

Asia
2
C vs T
594/816
1.128(0.904-1.406)
0.286
0.00%
0.573
0.00
1.000
NA
NA
F

Middle East
6
C vs T
672/823
1.614(1.219-2.137)
0.001
66.80%
0.010
0.75
0.452
0.77
0.485
R

North America
1
C vs T
412/486
1.215(0.845-1.748)
0.294
NA
NA
NA
NA
NA
NA
F

HWE

Y
7
C vs T
1479/1815
1.390(1.214-1.591)
0.001
31.00%
0.191
0.30
0.764
0.99
0.368
F

Overall
9
TC+CC vs TT
1678/2125
1.409(1.072-1.852)
0.014
67.50%
0.002
0.10
0.917
1.03
0.335
R

Region

Asia
2
TC+CC vs TT
594/816
1.138(0.891-1.454)
0.301
0.00%
0.374
0.00
1.000
NA
NA
F

Middle East
6
TC+CC vs TT
672/823
1.634(1.062-2.513)
0.026
73.40%
0.002
0.75
0.452
0.10
0.924
R

North America
1
TC+CC vs TT
412/486
1.188(0.809-1.742)
0.379
NA
NA
NA
NA
NA
NA
F

HWE

Y
7
TC+CC vs TT
1479/1815
1.399(1.190-1.645)
0.001
38.20%
0.138
0.00
1.000
1.11
0.319
F

Overall
9
CC vs TT+TC
1678/2125
1.872(1.420-2.467)
0.001
0.00%
0.588
0.10
0.917
0.42
0.686
F

Region

Asia
2
CC vs TT+TC
594/816
1.224(0.551-2.717)
0.619
0.00%
0.495
0.00
1.000
NA
NA
F

Middle East
6
CC vs TT+TC
672/823
1.960(1.455-2.641)
0.001
0.00%
0.462
0.38
0.707
0.66
0.545
F

North America
1
CC vs TT+TC
412/486
3.557(0.369-34.331)
0.273
NA
NA
NA
NA
NA
NA
F

HWE

Y
7
CC vs TT+TC
1479/1815
1.910(1.334-2.736)
0.001
0.00%
0.696
0.00
1.000
-0.21
0.840
F

R: random-effects model; F: fixed-effects model; Y: yes (studies that suitable for HWE); : the value of in the heterogeneity test.

Figure 4: The plot of sensitivity analysis about association between miRNA-499 rs3746444 and inflammatory arthritis.

4. Discussion

Both environmental factors and genetic factors are related to the development of inflammatory arthritis. As for miRNAs, it is reported that they are involved in cancers and autoimmune diseases [15, 21]. But some recent studies about miRNA-146/499 polymorphisms and inflammatory arthritis are inconsistent; it needs us to explore the real association between miRNA-146/499 polymorphisms and inflammatory arthritis by conducting this meta-analysis.

Present meta-analysis included 18 relevant studies, 9 only about miRNA-146 rs2910164, 3 only about miRNA-499 rs3746444, and 6 about both miRNA-146 rs2910164 and miRNA-499 rs3746444. There were 5 studies not met Hardy–Weinberg equilibrium; we did not exclude those 5 studies. We conducted subgroup analysis according to HWE and found that the results are similar (Table 2).

Of course, there were some limitations in this meta-analysis. First, we searched literature based on English; it may cause language bias. Second, the number of included studies was not sufficient, which could not conduct comprehensive analysis. Third, our data of meta-analysis were from retrospective research, which may be related to the methodological deficiencies. Finally, our meta-analysis did not take the interactions between environmental factors and genetic factors into account. Therefore, the results should be interpreted with caution.

In conclusion, the present study indicates that miRNA-499 rs3746444 polymorphism is associated with inflammatory arthritis susceptibility. However, there is lack of association between miRNA-146 rs2910164 polymorphism and inflammatory arthritis susceptibility. But, we find miRNA-146 rs2910164 and miRNA-499 rs3746444 polymorphism are associated with inflammatory arthritis in Middle East. Therefore, it is necessary to conduct more large-sample and more high-quality studies to further validate our findings.

Conflicts of Interest

All members declare they have no conflicts of interest.

Acknowledgments

This study was supported by grants from the Anhui Medical University Doctoral Research Foundation (XJ201414), Anhui Province Postdoctoral Foundation (2017B237), and the National Natural Science Foundation of China (11801010; 11526034).

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