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. 2021 Jan 17;24(3):300–313. doi: 10.1111/1756-185X.14060

Effect of mannose‐binding lectin gene polymorphisms on the risk of rheumatoid arthritis: Evidence from a meta‐analysis

Jinjian Xu 1,2, Gang Chen 3, Zhen Yan 4, Mochang Qiu 5, Wentao Tong 6, Xiaobin Zhang 6, Li Zhang 5, Yimin Zhu 2, Keqi Liu 5,✉
PMCID: PMC7986746  PMID: 33458965

Abstract

Background

The effect of mannose‐binding lectin (MBL) gene polymorphisms on susceptibility of rheumatoid arthritis (RA) were evaluated in ethnically different populations, whereas the results were always inconsistent.

Materials and methods

Fourteen articles involving 36 datasets were recruited to evaluate the association between MBL gene polymorphisms and rheumatoid arthritis in a meta‐analysis. The random or fixed effect models were used to evaluate the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs).

Results

Stratified analysis by ethnicities was conducted and the result revealed that rs1800450 (T vs C, OR = 1.32, 95% CI: 1.04‐1.67, P < .05) and MBL‐A/O (T vs C, OR = 1.20, 95% CI: 1.08‐1.34, P < .001) were strongly associated with RA in Brazilian populations. In addition, the significant relationship between rs11003125 (T vs C, OR = 1.16, 95% CI: 1.06‐1.26, P < .05) with RA were also observed in East Asian populations. Meanwhile, the inverse associations between rs5030737 with RA in East Asians and rs1800450 with RA in Indians were acquired. However, no association between any MBL polymorphism with RA susceptibility was confirmed in Caucasians.

Conclusions

The structural polymorphisms in exon 1 of MBL gene may significantly contribute to susceptibility and development of RA in Brazilian and Indian populations, whereas the functional polymorphisms in the promoter region were more likely to associate with RA in East Asians.

Keywords: mannose‐binding lectin, meta‐analysis, polymorphism, rheumatoid arthritis

1. INTRODUCTION

Rheumatoid arthritis (RA) is an autoimmune disease characterized by persistent synovitis, systemic inflammation and presence of autoantibodies. 1 RA affects 0.5% ~2% of the world population and the prevalence rate was 0.2%~0.4% in China. 2 , 3 At present, RA is one of the major diseases that seriously destructs life quality of patients and leads to the loss of labor capacity. 4 Although the pathogenesis of RA has not been fully clarified, it is generally believed that environmental, genetic and autoimmune factors may play a vital role in the onset of RA and genetic factors account for about 60% of RA susceptibility. 5

Mannose‐binding lectin (MBL) is a calcium‐dependent collagen lectin secreted by hepatocytes and plays an important role in innate immunity by opsonizing mannose‐ and N‐acetylglucosamine‐rich microorganisms and activating macrophages and complements. 6 The mutation of MBL gene can decrease the level of plasma MBL which may relate to immune deficiency. 7 The MBL gene is mapped on the long arm of chromosome 10q11.2‐10q21 and contains 4 exons. 8 Exon 1 has three functional single nucleotide polymorphisms (SNPs) at codons 54 (allele B, rs1800450), 57 (allele C, rs1800541), and 52 (allele D, rs5030737) in the structural part of the gene. 9 In addition, there are SNPs at positions −550 (allele L, rs11003125) and −221 (allele X, rs7096206) in the promoter region. 10 These variant alleles were associated with lowing serum MBL levels. Previous studies found that MBL gene variants can contribute to the susceptibility of acquired immune deficiency syndrome (AIDS), tuberculosis, systemic lupus erythematosus (SLE), Crohn's disease, RA and other infectious diseases. 11 , 12 , 13 , 14 , 15 However, the associations between MBL gene polymorphisms and RA were studied in various countries and ethnicities, but the results were inconsistent. 8 , 16 , 17 Tsutsumi et al. 18 found that codon 52 and 57 mutations of MBL gene were absent or extremely rare in Japanese; homozygous codon 54 mutation of the MBL gene was significantly increased in patients with autoimmune disorders. In addition, promotor regions of MBL gene suggested that individuals with absent or extremely low serum MBL were at risk of having autoimmune disorders. 19 Moreover, the B variant of the MBL2 gene may be associated with protection from RA in an Indian cohort and the promoter polymorphism rs1800450 seemed to have some roles in disease progression. 8 However, Stanworth et al. 20 declared that no evidence was found to support the association of MBL allele with protection from RA in Caucasian populations and genotype frequencies were similar in case and control groups. Similarly, the negative results were confirmed in a Japanese population. 18

Although many studies have been conducted so far to investigate the relationship between MBL gene polymorphisms and susceptibility of RA, the results were inconsistent. This discrepancy may be attributed to small sample sizes, low statistical power, different genetic background, or clinical heterogeneity. Meanwhile, inclusion of data that did not satisfy the requirement of meta‐analysis will produce a spurious association. Therefore, in order to reduce the limitations of a single study and to overcome the possible random errors, a large‐scale meta‐analysis involving multifarious ethnicities and multiple polymorphisms was performed in this study.

2. MATERIALS AND METHODS

2.1. Identification of eligible studies

To analyze the roles of MBL gene polymorphisms in susceptibility of RA, all published literature before June 2020 that researched the relationship between MBL gene polymorphisms and RA risk were included. The electronic databases were used including PubMed databases (National Center for Biotechnology, National Library of Medicine), CNKI (China National Knowledge Infrastructure), and Web of Science to retrieve articles by using the keywords “MBL gene”, “codon 54 (allele B, rs1800450)”, “codon 57 (allele C, rs1800541)”, “codon 52 (allele D, rs5030737)”, “‐550 (allele L, rs11003125)”, “‐221 (allele X, rs7096206)”, “polymorphism” connected to “RA”, “rheumatoid arthritis” without language restrictions. Finally, we extracted data from the published articles, not including meetings or any conference abstracts. All of studies were conducted with case–control or nested case–control design. The diagnosis of RA was according to the American College of Rheumatology (ACR) criteria and proper genotyping methods in most of the studies. 21 , 22 , 23

Three functional single nucleotide polymorphisms (SNP) in codons 54 (allele B), 57 (allele C), and 52 (allele D) were associated with changes in the structure and functional deficiency of protein. In codon 54, an A to G substitution alters an aspartic acid to a glycine at the protein level. In codon 57 there is a G to A substitution (glycine to glutamic acid), and in codon 52 a C to T substitution leads to a change from arginine to cysteine. Altogether, the presence of any variant alleles above has been collectively labeled O, while the simultaneous absence of variants at the 3 positions has been called allele A, the wild‐type allele. 24

2.2. Selection criteria and data extraction

Such major criteria must be followed for included studies: (a) original papers containing complete data; (b) case–control or cohort studies that assessed the association of MBL gene polymorphisms with RA; (c) sufficient data to calculate the odds ratio (OR) or P value; (d) relevant RA outcomes were angiographically confirmed according to the ACR criteria; 25 (e) the genotype distribution in the control group for each individual study should follow Hardy–Weinberg equilibrium (HWE). 26 , 27 The primary reasons for excluded studies: (a) case report, review or meta‐analysis articles; (b) deviation from the major selection criteria; (c) overlapping or that supplied inadequate data; (d) repeated publications or the same authors employed similar data in different papers, the data was only used once.

The study data were extracted based on standard protocols. 28 Disagreement was settled by a consensus between all authors. Where essential information was not presented in articles, every effort was made to contact the authors. All procedures conformed to the guidelines for meta‐analysis of observational studies in epidemiology. 29 The following information were extracted independently by individuals in our study: first author, year of publication, ethnicity, study design, types of RA, HWE status among controls, sample size of cases and controls, number of genotypes and allele frequency.

2.3. Statistical analysis

We calculated the allele frequency for each study in allele counting method; the HWE was tested by using the Chi‐square test. We employed pooled ORs and 95% confidence intervals (CIs) to evaluate the strength of association between polymorphisms and RA for every eligible study.

The methodology of Cochran's Q‐statistic was used to evaluate the heterogeneity, which is similar to the previous study in our lab. 22 , 23 If the P value in heterogeneity test was higher than 0.1, the fixed effect model was used. Moreover, the random effect model was used. We used the following formula to quantify the effect of heterogeneity: I 2 = 100% × (Q − dƒ)/Q. 30 The proportion of between‐study variability attributable to heterogeneity was indicated by I 2 value, and I 2 values of 25%, 50% and 75% were considered to be of low, moderate and high heterogeneity, respectively. If study groups revealed no heterogeneity, the similar results were produced in fixed and random effects models and, otherwise the random effects model usually produced wider CIs than the fixed effects model. 31 In this meta‐analysis, P value of less than .05 was considered as statistically significant.

In order to get exacting search results, we evaluated possible publication bias by Egger's linear regression test. If P value <.05 the statistical publication bias was considered. Moreover, the Begg's test also used a funnel plot to evaluate the publication bias. 32 For sensitivity analysis, we removed 1 study orderly from the total and tested residual studies. 33 All standard methods in this meta‐analysis were conducted in a previous study by us. Statistical analysis was carried out using the software program STATA15.0 (Stata Corporation).

3. RESULTS

3.1. Studies included in the meta‐analysis

In this meta‐analysis, totally 318 relevant articles were searched. After reading titles and abstracts, we excluded irrelevant studies, leaving 105 articles for further reading. Then, we excluded 54 articles, because of no data, insufficient data, repeated date, family‐based studies and not referring to RA. Thus, 51 articles met the study inclusion criteria. Lastly, 15 articles that included insufficient data, 5 articles in which the control populations deviated from HWE and 18 reviews or meta‐analysis researches about MBL gene polymorphisms were excluded. 25 , 44 After filtering, 13 eligible studies involving 36 data sets were finally included. 8 , 53 Eventually, 13 studies provided 5972 cases and 6663 controls: codon 54 (allele B, rs1800450), 1472 patients and 1554 controls; codon 57 (allele C, rs1800541), 240 patients and 264 controls; codon 52 (allele D, rs5030737), 520 patients and 642 controls; −550 (allele L, rs11003125), 785 patients and 841 controls; −221 (allele X, rs7096206), 1097 patients and 1151 controls; MBL‐A/O, 1858 patients and 2211 controls were pooled to evaluate the relationship between SNPs of MBL and RA in the meta‐analysis (Table 1). The flowchart of selecting articles is presented in Figure 1.

TABLE 1.

The basic information of included studies in this meta‐analysis

Study Y Ethnicity Polymorphisms Sample size Genotypes Allele frequencies (%)
Control Case Control Case
Control Case CC CT TT CC CT TT C T C T
Bhawna et al. 8 2005 Indian rs5030737 119 120 104 15 0 100 20 0 93.7 6.3 91.7 8.3
Bhawna et al. 8 2005 Indian rs5030737 145 120 132 13 0 100 20 0 95.5 4.5 91.7 8.3
Hou et al. 47 2013 Chinese rs5030737 378 280 362 15 0 278 2 0 97.9 2.1 99.6 0.4
Stanworth et al. 20 1999 Caucasian rs1800450 114 182 84 28 2 142 35 5 86.0 14.0 87.6 12.4
Ip et al. 46 2000 Chinese rs1800450 196 211 153 42 1 143 64 4 88.8 11.2 82.9 17.1
Horiuchi et al. 18 2000 Japanese rs1800450 105 59 66 29 10 42 13 4 76.7 23.3 82.2 17.8
Tsutsumi et al. 53 2001 Japanese rs1800450 129 95 88 39 2 58 32 5 83.3 16.7 77.9 22.1
Bhawna et al. 8 2005 Indian rs1800450 119 120 72 47 0 106 14 0 80.3 19.7 94.2 5.8
Bhawna et al. 8 2005 Indian rs1800450 145 120 94 49 2 106 14 0 81.7 18.3 94.2 5.8
Min et al. 49 2006 Chinese rs1800450 48 93 36 12 0 66 24 3 87.5 12.5 83.9 16.1
Hou et al. 47 2013 Chinese rs1800450 378 280 231 138 10 195 76 9 79.2 20.8 83.2 16.8
Isabela et al. 16 2014 Brazilian rs1800450 200 156 148 45 7 96 55 5 85.3 14.7 79.2 20.8
Isabela et al. 16 2014 Brazilian rs1800450 120 156 79 41 0 96 55 5 82.9 17.1 79.2 20.8
Bhawna et al. 8 2005 Indian rs1800451 119 120 111 8 0 110 10 0 96.6 3.4 95.8 4.2
Bhawna et al. 8 2005 Indian rs1800451 145 120 129 16 0 110 10 0 94.5 5.5 95.8 4.2
Ip et al. 46 2000 Chinese rs7096206 174 115 119 50 5 68 41 6 82.8 17.2 76.5 23.5
Bhawna et al. 8 2005 Indian rs7096206 119 120 70 43 6 60 50 10 76.9 23.1 70.8 29.2
Bhawna et al. 8 2005 Indian rs7096206 90 120 46 32 12 60 50 10 68.9 31.1 70.8 29.2
Min et al. 49 2006 Chinese rs7096206 48 50 38 9 1 33 15 2 88.5 11.5 81.0 19.0
Isabela et al. 16 2014 Brazilian rs7096206 200 156 130 58 12 109 38 9 79.5 20.5 82.1 18.9
Isabela et al. 16 2014 Brazilian rs7096206 120 156 91 28 1 109 38 9 87.5 12.5 82.1 17.9
Hou et al. 17 2020 Chinese rs7096206 400 380 232 160 8 230 143 7 77.9 22.1 79.3 20.7
Ip et al. 46 2000 Chinese rs11003125 174 115 48 87 39 20 56 39 52.6 47.4 41.7 58.3
Bhawna et al 8 2005 Indian rs11003125 119 120 16 54 49 15 54 51 36.1 63.9 35.0 65.0
Bhawna et al. 8 2005 Indian rs11003125 100 120 17 42 41 15 54 51 38.0 62.0 35.0 65.0
Min et al. 49 2006 Chinese rs11003125 48 50 17 23 8 15 25 10 59.4 40.6 54.0 46.0
Hou et al. 17 2020 Chinese rs11003125 400 380 111 225 64 100 181 99 56.0 44.0 50.2 49.8
Jacobsen et al. 51 2000 Caucasian MBL‐A/O 250 68 157 86 7 35 28 5 80.0 20.0 72.1 27.9
Koert et al. 45 2008 Caucasian MBL‐A/O 194 218 120 65 9 128 81 9 78.6 21.4 77.3 22.7
Fernanda et al. 19 2012 Brazilian MBL‐A/O 345 322 207 120 18 171 131 20 77.4 22.6 73.4 26.6
Fernanda et al. 19 2012 Brazilian MBL‐A/O 244 300 148 83 13 160 123 17 77.7 22.3 73.8 26.2
Fernanda et al. 19 2012 Brazilian MBL‐A/O 101 22 59 37 5 11 8 3 76.7 23.3 68.2 31.8
Isabela et al. 16 2014 Brazilian MBL‐A/O 200 156 119 73 8 75 73 8 77.8 22.2 71.4 28.6
Isabela et al. 16 2014 Brazilian MBL‐A/O 120 156 62 58 0 75 73 8 75.8 24.2 71.4 28.6
Malthe et al. 48 2014 Caucasian MBL‐A/O 383 301 159 193 31 130 143 28 66.7 33.3 66.9 33.1
Malthe et al. 48 2014 Caucasian MBL‐YA/O 374 315 150 193 31 144 143 28 65.9 34.1 68.4 31.6
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C, represent wild‐type allele; T, represent minor allele; MBL‐A/O, the presence of any of rs5030737, rs1800450, rs1800451 has been collectively labeled O, while the simultaneous absence of variants at the 3 positions has been called allele A, the wild‐type allele; MBL‐YA/O, the MBL‐A/O and presence of rs7096206.

FIGURE 1.

FIGURE 1

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The process of the articles selected in this meta‐analysis

3.2. Meta‐analysis results

In this meta‐analysis we recruited allele model, dominant gene model and recessive gene model to confirm the association between 5 MBL SNPs with RA in multiple ethnicities. The results of stratification by ethnicity revealed the heterogeneity had disappeared (P > .01, I 2 < 30%; Figure 2A‐D).

FIGURE 2.

FIGURE 2

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Forest plot for the meta‐analysis of allele model (T vs C). A, MBL gene polymorphisms and RA in Brazilians. B, MBL gene polymorphisms and RA in Caucasians. C, MBL gene polymorphisms and RA in East Asians. D, MBL gene polymorphisms and RA in Indians

3.3. Mannose‐binding lectin SNPs and RA in Brazilians

The results found that rs1800450 (T vs C, OR = 1.32, 95% CI: 1.04‐1.67, P OR < .05) and MBL‐A/O (T vs C, OR = 1.20, 95% CI: 1.08‐1.34, P OR < .001) were strongly associated with RA in a Brazilian population (Table 2, Figure 2A). Meanwhile, the overall study displayed the same significant association (T vs C, OR = 1.20, 95% CI: 1.09‐1.31, P OR < .001), and no heterogeneity (P H = .597) (Table 2, Figure 2A). In addition, rs1800450 (TT + TC vs CC, OR = 1.30, 95% CI: 1.04‐1.62, P OR < .05) and MBL‐A/O (TT + TC vs CC, OR = 1.18, 95% CI: 1.07‐1.31, P OR < .05) were strongly related to RA in the dominant model (Table 2, Figure 3A), whereas, the association was weak in the recessive gene model (Table 2, Figure 4A). However, pooled associations of rs1800450 and MBL‐A/O not only in the dominant model (TT + TC vs CC, OR = 1.17, 95% CI: 1.07‐1.27, P OR < .0001) were strong (Table 2, Figure 3A), but also in the recessive model (TT vs TC + CC, OR = 1.44, 95%CI: 1.04‐1.99, P OR < .05) (Table 2, Figure 4A).

TABLE 2.

The association between MBL polymorphisms and RA risk in meta‐analysis

Sub‐group analysis No. of data sets No. of cases/controls Allele model (T vs C) Dominant model (CC vs TT + CT) Recessive model (TT vs CC + CT)
Cases Controls OR (95% CI) P OR P H OR (95% CI) P OR P H OR (95% CI) P OR P H
Brazilian
rs1800450 2 754 740 1.32 (1.04‐1.67)∗ <.05 .546 1.30 (1.04‐1.62)∗ <.05 .225 1.55 (0.59‐4.12) .377 .141
rs7096206 2 736 752 1.06 (0.83‐1.35) .666 .058 1.00 (0.78‐1.27) .969 .146 1.54 (0.74‐3.20) .248 .070
MBL‐A/O 5 2432 2479 1.20 (1.08‐1.34)** <.001 .959 1.18 (1.07‐1.31)∗ <.05 .890 1.39 (0.95‐2.05) .093 .379
Overall 9 3922 3971 1.20 (1.09‐1.31)*** <.0001 .597 1.17 (1.07‐1.27) *** <.0001 .489 1.44 (1.04‐1.99)∗ <.05 .298
Caucasian
rs1800450 1 409 260 0.88 (0.58‐1.34) .556 NA 0.84 (0.55‐1.26) .391 NA 1.57 (0.31‐7.94) .588 NA
MBL‐A/O 3 1510 2092 1.06 (0.94‐1.20) .357 .170 1.04 (0.94‐1.16) .463 .176 1.20 (0.81‐1.78) .372 .310
MBL‐YA/O 1 829 1003 0.93 (0.80‐1.08) .326 NA 0.91 (0.80‐1.03) .141 NA 1.07 (0.66‐1.75) .779 NA
Overall 5 2748 3355 1.00 (0.91‐1.10) .973 .225 0.98 (0.90‐1.06) .592 .180 1.16 (0.86‐1.57) .335 .623
East Asian
rs5030737 1 562 772 0.17 (0.04‐0.73) * <.05 NA 0.18 (0.04‐0.78) * <.05 NA NA
rs1800450 5 1735 2017 1.02 (0.88‐1.19) .769 .012 0.99 (0.85‐1.14) .872 .011 1.44 (0.81‐2.56) .214 .426
rs7096206 3 1320 1492 1.06 (0.90‐1.24) .495 .062 1.04 (0.90‐1.21) .567 .082 1.28 (0.63‐2.61) .499 .647
rs11003125 3 1649 1800 1.16 (1.06‐1.26) * <.05 .692 1.05 (0.98‐1.13) .133 .338 1.56 (1.25‐1.94) <.0001 .783
Overall 12 5266 6081 1.09 (1.02‐1.17)* <.05 .003 1.02 (0.96‐1.09) .531 .005 1.52 (1.24‐1.84) <.0001 .851
Indian
rs5030737 2 520 556 1.56 (0.98‐2.48) .062 .475 1.56 (1.00‐2.44) .053 .459 NA NA NA
rs1800450 2 508 628 0.31 (0.21‐0.46)*** <.0001 .850 0.31 (0.21‐0.46)*** <.0001 .766 0.24 (0.01‐4.98) .357 NA
rs1800451 2 500 552 0.93 (0.52‐1.67) .802 .416 0.93 (0.52‐1.64) .798 .406 NA NA NA
rs7096206 2 620 529 1.09 (0.88‐1.34) .434 .168 1.12 (0.92‐1.36) .268 .392 0.94 (0.52‐1.71) .836 .130
rs11003125 2 792 714 1.03 (0.94‐1.14) .524 .766 1.03 (0.96‐1.11) .415 .579 1.03 (0.83‐1.28) .760 .985
Overall 10 2940 2979 1.07 (0.98‐1.18)*** .184 <.0001 1.09 (1.00‐1.19) .085 <.0001 1.00 (0.82‐1.23) .981 .510
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Abbreviations: C, represent wild‐type allele; 95%CI, 95% confidence interval; OR, odd ratio; P OR, P value for the test of association; P H, P value for heterogeneity analysis; T, represent minor allele; NA, none.

∗

P OR < .05.

**

P OR < .001.

***

P OR < .0001.

FIGURE 3.

FIGURE 3

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Forest plot for the meta‐analysis of allele model dominant model (CC vs TT + CT). A, MBL gene polymorphisms and RA in Brazilians. B, MBL gene polymorphisms and RA in Caucasians. C,, MBL gene polymorphisms and RA in East Asians. D, MBL gene polymorphisms and RA in Indians

FIGURE 4.

FIGURE 4

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Forest plot for the meta‐analysis of recessive model (TT vs CC + CT). A, MBL gene polymorphisms and RA in Brazilians. B, MBL gene polymorphisms and RA in Caucasians. C, MBL gene polymorphisms and RA in East Asians. D, MBL gene polymorphisms and RA in Indians

3.4. MBL SNPs and RA in East Asians

The significant relationship between rs11003125 (T vs C, OR = 1.16, 95% CI: 1.06‐1.26, P OR < .05) with RA susceptibility was observed in East Asian populations (Table 2, Figure 2C). Meanwhile, significant association was found in the recessive gene model (TT vs TC + CC, OR = 1.56, 95% CI: 1.25‐1.94, P OR < .0001) (Table 2, Figure 4C). The rs5030737 (T vs C, OR = 0.17, 95% CI: 0.04‐0.73, P OR < .05) was reversely associated with RA in East Asians (Table 2, Figure 2C), and the reverse association was maintained in the dominant model (TT + TC vs CC, OR = 0.18, 95% CI: 0.04‐0.78, P OR < .05) (Table 2, Figure 3C). However, pooled associations of rs11003125 and rs5030737 were observed, but the heterogeneity (P H < .01, I 2 > 30%) was also found.

3.5. MBL SNPs and RA in Indians

In this stratification, the heterogeneity was resolved. The rs1800450 (T vs C, OR = 0.31, 95% CI: 0.21‐0.46, P OR < .0001) was reversely associated with RA in an Indian population (Table 2, Figure 2D). Meanwhile, the reverse association was maintained in the dominant model (TT + TC vs CC, OR = 0.31, 95% CI: 0.21‐0.46, P OR < .0001) (Table 2, Figure 3D).

3.6. MBL SNPs and RA in Caucasians

In this meta‐analysis, 5 studies involved rs1800450 and pooled MBL‐A/O polymorphisms to research the association with RA in Caucasians. However, the results showed that no association between any MBL polymorphism with RA susceptibility was confirmed in Caucasian (P OR > .05) (Table 2, Figures 2, 3 and 4B).

3.7. Comparing allele frequency of MBL SNPs to the 1000 genome phase 3 population

We compared allele frequencies of different ethnicities in our meta‐analysis to 1000 genome allele frequencies in Table 3. In view of the sample size and population, the allelic frequencies of MBL polymorphisms in this meta‐analysis were consistent with the allelic frequencies in the 1000 Genome Project East Asian ancestry and Caucasians. However, there was distinction between the allele frequencies in Indians and the 1000 Genomes Project. Meanwhile, allele frequency of rs7096206 was inconsistent in any ethnicity compared to the 1000 Genomes Project.

TABLE 3.

The allele frequency comparison between the meta‐analysis and 1000 Genomes Project

Polymorphisms Populations Meta‐analysis (alleles frequencies) 1000 genomes (alleles frequencies)
Case Control
C T C T C T
rs5030737 Brazilian NA NA NA NA 1.00 0.00
Caucasian NA NA NA NA 0.94 0.06
East Asian 1.00 0.00 0.98 0.02 1.00 0.00
Indian 0.92 0.08 0.95 0.05 0.97 0.03
All 0.96 0.04 0.97 0.03 0.97 0.03
rs1800450 Brazilian 0.79 0.21 0.84 0.16 0.85 0.15
Caucasian 0.88 0.12 0.86 0.14 0.86 0.14
East Asian 0.82 0.18 0.82 0.18 0.85 0.15
Indian 0.94 0.06 0.81 0.19 0.78 0.22
All 0.84 0.16 0.83 0.17 0.88 0.12
rs1800451 Brazilian NA NA NA NA 0.97 0.03
Caucasian NA NA NA NA 0.99 0.01
East Asian NA NA NA NA 1.00 0.00
Indian 0.96 0.04 0.95 0.05 0.98 0.02
All 0.96 0.04 0.95 0.05 0.92 0.08
rs11003125 Brazilian NA NA NA NA 0.47 0.53
Caucasian NA NA NA NA 0.61 0.39
East Asian 0.49 0.51 0.55 0.45 0.55 0.45
Indian 0.35 0.65 0.37 0.63 0.60 0.40
All 0.45 0.55 0.51 0.49 0.69 0.31
rs7096206 Brazilian 0.82 0.18 0.83 0.18 0.13 0.87
Caucasian NA NA NA NA 0.22 0.78
East Asian 0.79 0.21 0.80 0.20 0.19 0.81
Indian 0.71 0.29 0.73 0.27 0.13 0.87
All 0.78 0.22 0.80 0.20 0.20 0.80
MBL‐A/O Brazilian 0.73 0.27 0.77 0.23 NA NA
Caucasian 0.70 0.30 0.71 0.29 NA NA
All 0.72 0.28 0.74 0.26 NA NA
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Abbreviations: C, represent wild‐type allele; T, represent minor allele.

3.8. Publication bias and sensitivity analysis

Begg's funnel plot and Egger's test were performed to estimate publication bias (Figure 5A‐D). No evidence of publication bias for MBL gene polymorphisms under the allele genetic model was found in any ethnicity. In addition, no significant difference was found in the Egger's test, suggesting no obvious bias of publication in the present meta‐analysis. We also conducted sensitivity analysis to assess the influence of individual studies on the pooled ORs. We found the pooled OR was not substantially altered, when a single study involved in the meta‐analysis was deleted each time (Figure 6A‐D).

FIGURE 5.

FIGURE 5

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Begg's funnel plot of publication bias in the meta‐analysis of the association of MBL gene polymorphisms with RA risk. A, MBL gene polymorphisms and RA in Brazilian. B, MBL gene polymorphisms and RA in Caucasian. C, MBL gene polymorphisms and RA in East Asian. D, MBL gene polymorphisms and RA in Indian

FIGURE 6.

FIGURE 6

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Sensitivity analysis to assess the stability of the meta‐analysis. A, MBL gene polymorphisms and RA in Brazilian. B, MBL gene polymorphisms and RA in Caucasian. C, MBL gene polymorphisms and RA in East Asian. D, MBL gene polymorphisms and RA in Indian

4. DISCUSSION

The comprehensive meta‐analysis confirmed that the biological roles of 5 loci in different ethnicities were distinct. It was verified that the structural polymorphisms in exon 1 of MBL gene may significantly contribute to susceptibility and development of RA in Brazilian and Indian populations, whereas the functional polymorphisms in the promoter region were more likely to associate with RA in East Asians.

MBL was structurally and functionally similar to C1q, and shared the same phagocytic receptor on phagocytes, platelets, and endothelial cells. 54 MBL plays a key role in the innate immune system by activating complements and macrophages, and by inducing opsonization. MBL mediates lectin‐dependent activation of the complement pathway, and resembles C1q in terms of structure and function. 55 Low serum levels of MBL may result in impaired opsonization of complement‐containing immune complexes. 56 The activation of MBL variants could contribute to damage tissue and consequently to disease severity. Inversely, deficiencies of complement proteins may enhance autoimmunity. 15 Considering that, the lectin pathway is involved in the clearance of pathogens and apoptotic bodies that may act as potential autoimmune initiators, deficiencies of components could enhance susceptibility and severity of some rheumatic disorders. 36 , 57 , 58 The functional MBL exon 1 codon 54 (allele B), codon 57 (allele C), and codon 52 (allele D) variants cause structural changes of the MBL basic unit, producing a lower molecular weight protein and reduced serum MBL levels. 16 Besides the exon 1 variant alleles, SNPs at promoter −550 (allele L) and −221 (allele X) have been associated with low serum MBL levels. 48

A low MBL level caused by MBL variant alleles has been associated with human immunodeficiency virus and hepatitis C virus infections, and with SLE. 13 , 15 , 59 Since MBL2 variants are the major determinants of MBL circulating levels, various studies demonstrated that variations on MBL serum levels seem to influence RA development and prognosis in different ways. 60 Although MBL2 low‐producing polymorphisms were associated with increased susceptibility to RA, disease progression and clinical manifestations, the B variant was reported to confer protection against RA in an Indian population. 8 High producing genotype YA/YA conferred an increased risk of myocardial infarction and death in RA patients with ischemic heart disease. 61 , 62 Similarly, high producing MBL2 genotypes enhanced the risk of cardiovascular disease in patients with rheumatic fever. 54 , 63 Nevertheless, no association between RA and MBL2 polymorphisms was reported by others. 64

In addition, a meta‐analysis was conducted with 8 researches by others and this found \ a significant association between the MBL D allele and RA in the overall population (OR = 1.708, P = .023). 42 An association was also found between the MBL L allele and RA in the overall group (OR = 1.936, P = .005), as well as between the MBL X allele and RA in the overall group (OR = 1.582, P = .001). Their meta‐analysis demonstrated an association between the MBL D, L, and X alleles and the risk of RA. However, the mixed ethnic population and limited sample size may make their results unreliable, or serious deviation from the real situation. Moreover, Stefanie et al. 35 also conducted a meta‐analysis and the results showed that MBL2 low‐producing OO and XX genotypes do not confer higher risk to RA, even when data were analyzed according to the cohort's ethnicity. Due to the diversity of MBL2 alleles and divergent concepts about high and low‐producing genotypes, they analyzed first only exon 1 polymorphisms and classified the data according to the presence of AA, AO and OO genotypes. Of course, so far, some research had reported that there was no association found between rs1800450 and RA, which was contradictory with our findings. 43 It is normal that such distinct consequences were obtained in separated studies. RA is considered to be a common multifactor autoimmune disease due to its complicated pathogenesis. It was validated that body mass index (BMI) and smoking will significantly contribute to susceptibility and development of RA. In addition, the gender difference was the key role in RA morbidity. However, lack of BMI level in participants might lead to inconsistent results. These phenomena and discrepancies need further investigation on the basis of large sample size. Moreover, the concentration of MBL may be regulated by other mechanisms than by variants on the MBL2 gene; additional studies including both polymorphisms and functional assays could give a better insight into the relationship between MBL and RA.

Although we revealed some new discoveries in this study, there were still several limitations which should be taken into consideration. In our study, the overall sample size is large, but the size of each study is relatively small; the smallest sample is 50 cases and 48 controls, and we need numerous data to validate the relationship between MBL SNPs and RA for further study in Caucasian populations. Second, in stratification analysis, the number of studies included in each ethnicity was unbalanced, some just for one study. Additionally, we are unable to analyze the actual impact of immanent factors on RA because of the incomplete data. Meanwhile, how the interaction of genes with environmental factors and genes with dietary models relate to the risk of RA is unclear. Further efforts should be put on investigating the association of the functional mutations in the MBL gene with RA, and the interactions of potential gene‐gene and gene‐environment factors should be comprehensively analyzed.

5. CONCLUSIONS

We conducted a meta‐analysis to evaluate the effects of MBL polymorphisms (rs1800450, rs1800541, rs5030737, rs11003125, rs7096206) on the risk of RA. The structural polymorphisms in exon 1 of MBL gene may significantly contribute to susceptibility and development of RA in Brazilian and Indian populations, whereas the functional polymorphisms in the promoter region were more likely to associate with RA in East Asians. Meanwhile, the reverse association between rs5030737 with RA in East Asians was displayed. However, the polymorphisms in exon 1 of MBL gene lacked the connection with RA.

CONFLICT OF INTERESTS

The authors declare they have no competing interests.

AUTHOR CONTRIBUTIONS

KQL and JJX made substantial contributions to the conception; JJX designed the work; GC, ZY and MCQ interpreted data; WTT for the main data analysis; XBZ created new software used in the work. LZ and YMZ drafted the work or substantively revised it. All authors reviewed and approved the final manuscript.

Xu J, Chen G, Yan Z, et al. Effect of mannose‐binding lectin gene polymorphisms on the risk of rheumatoid arthritis: Evidence from a meta‐analysis. Int J Rheum Dis. 2021;24:300–313. 10.1111/1756-185X.14060

Funding information

This study was supported by the National Natural Science Foundation of China (81871831), the Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars of China (LR17H070001). The funding agencies had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

DATA AVAILABILITY STATEMENT

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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