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TNFAIP3 gene rs10499194, rs13207033 polymorphisms decrease the risk of rheumatoid arthritis

Accumulating evidences suggested that tumor necrosis factor alpha inducible protein 3 (TNFAIP3) gene rs10499194, rs13207033 polymorphisms may be associated with the risk of rheumatoid arthritis (RA). However, these studies yielded contradictory findings. To clarify convincing associations, we conducted a comprehensive meta-analysis by searching in PubMed, Embase, and the China Knowledge Resource Integrated Database. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by using fixed-effect or random-effect models. A total of 13 case-control studies for rs10499194 polymorphism and 6 studies for rs13207033 polymorphism were included. Our data indicated that TNFAIP3 gene rs10499194, rs13207033 polymorphisms were associated with the decreased risk of RA. Stratification analyses of ethnicity indicated rs10499194, rs13207033 polymorphisms decreased the risk of RA among Caucasian populations, but not among Asian populations. In conclusion, this meta-analysis indicates that TNFAIP3 gene rs10499194, rs13207033 polymorphisms decrease the risk of RA, especially among Caucasian populations.


INTRODUCTION
Rheumatoid arthritis (RA) is an autoimmune inflammatory disease, which is characterized by chronic destructive inflammation in synovial joints. To date, the etiology of RA is poorly understood, but it is believed that complex genetic and environmental factors play important roles in the pathogenesis of RA [1]. Previous studies have suggested that genetic factors may be account for approximately 50-65% of the risk of RA [2]. Human leukocyte antigen (HLA) alleles are well recognized to be implicated in the pathogenesis of RA [3]. However, family studies indicated that HLA alleles contribute to about 30% of genetic susceptibility and that non-HLA loci are also related to RA [2,4].
Tumor necrosis factor alpha inducible protein 3 (TNFAIP3), a deubiquitinating protein, is reported to play a pivotal role in T cell activation and inflammatory signaling [5]. It can deregulate NF-κB-dependent gene expression via deubiquitinating specific NF-κB signaling molecules [6].

Characteristics of the included studies
We yielded a total of 251 citations after initial search. 77 citations were removed because of duplicates, Research Paper www.impactjournals.com/oncotarget and 141 citations were excluded after screening the titles and abstracts. 33 citations were selected for further full text review. 19 citations were excluded due to the following reasons: 9 investigated other polymorphisms; 4 citations did not provide detailed genotyping data; 2 were about juvenile idiopathic arthritis; 3 were reviews; and 1 was not case-control study. We finally identified 14 eligible citations [7,[9][10][11][12][13][14][15][16][17][18][19][20][21] including 17 studies (23,918 cases and 33,486 controls) in this metaanalysis. Selection for eligible studies included in this meta-analysis was presented in Figure 1. 6 studies with 11,166 cases and 11,231 controls examined rs13207033 polymorphism; 13 studies including 15,341 cases and 24,535 controls investigated rs10499194 polymorphism. The characteristics of included studies are summarized in Table 1. The Newcastle-Ottawa Scale (NOS) scores of all included studies ranged from 5 to 7 stars, suggesting that these studies were of high methodological quality.
We assessed sensitivity by omitting each study once at a time in every genetic model for rs10499194 and rs13207033 polymorphisms. The pooled ORs for the effects of these two single nucleotide polymorphisms (SNPs) (rs10499194, TT vs. CT+CC: Figure 5) on the risk for RA risk indicated that our data were stable and trustworthy. Both Egger's and Begg's tests (rs10499194: TT vs. CT+CC, Figure 6) were used to evaluated the publication bias of this meta-analysis. Our data revealed that there was no obvious publication bias for rs10499194 and rs13207033 polymorphisms (data not shown).

DISCUSSION
In this current meta-analysis, we found that TNFAIP3 gene rs10499194, rs13207033 polymorphisms were associated with the decreased risk of RA. Stratification analyses of ethnicity indicated that rs10499194 and rs13207033 polymorphisms decreased the risk of RA among Caucasians, but not among Asians.
Studies have demonstrated that NF-κB-dependent gene expression is significantly associated with the development of RA [21]. TNFAIP3 is an inhibitor of the NF-κB signaling pathway and it is indispensable in the development of RA [22]. Defects in TNFAIP3 expression are associated with development of RA [23]. Matmati et al. indicated that TNFAIP3 deficiency in myeloid cells triggers erosive polyarthritis resembling RA [24]. They revealed a pivotal and cell-specific function for TNFAIP3 in the pathogenesis of RA [24]. Recently, a number of [7,[9][10][11][12][13][14][15][16][17][18][19][20][21] studies explored the associations between TNFAIP3 gene polymorphisms (rs10499194, rs13207033) and RA risk. However, these studies obtained inconsistent results. The limitations of these studies including clinical heterogeneity, different ethnic populations, inadequate statistical power, and small sample sizes may contribute to the disaccord. Therefore, to obtain reliable conclusions, it is indispensable to conduct a comprehensive meta-analysis to demonstrate the associations between TNFAIP3 gene rs10499194, rs13207033 polymorphisms and RA susceptibility. Our data indicated that TNFAIP3 gene rs10499194 and rs13207033 polymorphisms decreased the risk of RA.
Previously, Lee et al. also performed a metaanalysis to investigate TNFAIP3 gene rs10499194 polymorphism with RA susceptibility [25]. They indicated that rs10499194 polymorphism was not associated with RA susceptibility [25]. Stratification   analyses of ethnicity in their meta-analysis [25] suggested that rs10499194 polymorphism was weakly associated with an increased risk of RA among Asian populations, while no association was observed among Caucasian populations. However, our meta-analysis found that rs10499194 polymorphism was significantly associated with a decreased risk of RA among Caucasian populations, but not among Asian populations, indicating that diversity inheritance of different ethnicities. The reasons why the decreased risk of RA among Asians is not obvious are still unclear. The clinical heterogeneity, different ethnicities and small sample sizes may explain it. We think previous meta-analysis [25]  Due to these above limitations of previous meta-analysis, we re-conducted this meta-analysis. We believe our metaanalysis has some strength over previous meta-analysis for the following reasons. One, we identified 13 studies [7, 9, 11-13, 16, 18-21], including 15,341 cases and 24,535 controls with regard to rs10499194 polymorphism and the sample size of this meta-analysis was large enough. Two, sensitivity analysis indicated that our data about rs10499194 polymorphism were trustworthy and robust. Three, the power analysis indicated that our study had a power of 99.9% to detect the effect of rs10499194 polymorphism on RA susceptibility, assuming an OR of 0.80. Regarding TNFAIP3 gene rs13207033 polymorphism, six studies explored the association between this SNP and RA risk. A study from UK [15] found rs13207033 polymorphism was significantly associated with a decreased risk of RA, but the remaining five studies [10,11,14,17,21] did not replicate the association. Therefore, we conducted the meta-analysis to demonstrate this SNP with RA risk. To our knowledge, this is the first meta-analysis to address the association between this SNP and RA risk. A weak association was obtained about rs13207033 polymorphism in our study. Stratification analyses by ethnicity also found a weak association between rs13207033 polymorphism and Caucasian RA risk.
Several potential limitations should be addressed in this meta-analysis. First, due to limited data, we could not perform further stratification analyses of other potential factors, such as anti-citrullinated peptide antibody (ACPA) and rheumatoid factor (RF). Second, our results were based on unadjusted estimates for confounding factors, which might have affected the final conclusions. Third, we could not assess potential gene-gene and gene-environment interactions because of the lack of relevant data. Fourth, the heterogeneity of this meta-analysis was high in some genetic models. Fifth, the conclusions about rs10499194 polymorphism among Asians should be interpreted with caution due to limited sample size.
In conclusion, this meta-analysis indicates that TNFAIP3 gene rs10499194, rs13207033 polymorphisms are associated with the decreased risk of RA, especially among Caucasians. Further studies are necessary to validate whether TNFAIP3 gene rs10499194, rs13207033 polymorphisms contribute to RA susceptibility in other ethnic groups.

Literature search and criteria of inclusion
We systematically searched the PubMed, Embase, and China Knowledge Resource Integrated Database to identify studies through July 26, 2016. The following search terms were used: "tumor necrosis factor alpha inducible protein 3," ''TNFAIP3,'' ''A20,'' ''Rheumatoid Arthritis,'' ''RA,'' ''polymorphism,'' ''SNP'' and ''polymorphisms''. No restrictions were placed on the search. Additional initially omitted studies (such as reference lists of identified studies) have been identified by hand screening. The identified studies conformed to the following criteria: (1) studies that evaluated the association between RA risk and TNFAIP3 gene rs10499194 or rs13207033 polymorphism, (2) studied on human beings, (3) study provided sufficient data to calculate the odds ratios (ORs) and 95% confidence intervals (CIs), and P value, and (4) case-control study.

Data extraction and quality assessment
Relevant information was carefully extracted from all eligible studies. The extracted information from all eligible studies including: name of first author, publication year, country of origin, ethnicity, and genotype numbers of cases and controls. Two reviewers independently performed the extraction of data and assessed the study quality based on the NOS [27]. All disagreements were discussed and resolved with consensus.

Statistical analysis
All statistical analyses were performed using the Stata 11.0 software (StataCorp, College Station, TX, USA). ORs and 95%CIs were used to assess the strength of associations between TNFAIP3 gene rs10499194, rs13207033 polymorphisms and RA risk. Stratification analysis was carried out by ethnicity. P < 0.05 was considered statistically significant. When a Q test indicated P < 0.1 or I 2 > 50% indicated heterogeneity across studies, a random-effect model was used. Otherwise, the fixed-effects model was applied [28]. Pooled ORs were calculated for allele model, dominant model, recessive model, homozygous model, and heterozygous model. We performed sensitivity analyses by omitting each study in turn to determine the effect on the test of heterogeneity and evaluated the stability of the overall results. We assessed the departure from the HWE in the controls using Pearson's χ2 test. Potential publication bias was assessed