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. 2019 Jan 7;32(1):e1415. doi: 10.1590/0102-672020180001e1415

ASSOCIATION OF INTERLEUKIN-10 -592A>C AND -819T>C POLYMORPHISMS WITH GASTRIC CANCER RISK: A SYSTEMATIC REVIEW AND META-ANALYSIS OF 44 CASE-CONTROL STUDIES

ASSOCIAÇÃO DE POLIMORFISMOS DA INTERLEUCINA-10 -592A>C E -819T>C COM RISCO DE CÂNCER GÁSTRICO: REVISÃO SISTEMÁTICA E METANÁLISE DE 44 ESTUDOS DE CASO-CONTROLE

Mansour MOGHMI 1, Amir ARJMANDI 2, Kazem AGHILI 3, Mohammadali JAFARI 4, Masoud ZARE-SHEHNEH 2, Shohreh RASTEGAR 5, Seyed Mojtaba ABOLBAGHAEI 6, Hossein NEAMATZADEH 2
PMCID: PMC6323628  PMID: 30624524

ABSTRACT

Introduction:

A series of studies have evaluated the association between -592A>C and -819T>C polymorphisms in the promoter regions of Interleukin-10 (IL-10) and gastric cancer (GC) risk. However, the results remain inconclusive.

Objective:

To better understand the association of the polymorphisms with GC risk, we performed a comprehensive meta-analysis.

Method:

An electronic search was performed of several databases to identify relevant studies up to April 2018.

Results:

A total of 44 case-control studies, including 26 studies on IL-10 -592A>C (5,332 cases and 8,272 controls) and 18 studies on IL-10 -819T>C (3,431 cases and 6,109 controls) were selected. Overall, -592A>C polymorphism was associated with the risk of GC under the heterozygote model (OR=1.153, 95% CI=1.020-1.305, p=0.023), but not -819T>C polymorphism. When stratified by ethnicity, significant association was only observed in the Asians under the allele model (OR=1.153, 95% CI=1.007-1.320, p=0.040) and the heterozygote model (OR=1.218, 95% CI=1.076-1.379, p=0.002) for -592A>C.

Conclusion:

The current meta-analysis results inconsistent with previous meta-analyses; showed that the IL-10 -592A>C polymorphism, but not -819T>C polymorphism, may be contributed to the susceptibility of GC in overall and Asian populations.

HEADINGS: Stomach neoplasms; Interleukin-10; Polymorphism, genetic; Meta-analysis

INTRODUCTION

Gastric cancer (GC) is the 5th most common cancer and second leading cause of cancer-related deaths globally 21 , 32 , 36 . In 2016 there were an estimated 26,370 new cases of GC in the United States 39. The recent years have brought much progress regarding the genetics of GC and the number of confirmed GC associated SNPs and genes have risen dramatically 4 , 48 . In addition, several studies have supported the concept that environmental factors are critical components of GC pathogenesis 52 . However, genetic factors may modify the propensity for GC development through an alteration of the inflammatory state and may also interact with other risk factors 44 .

Presently the mechanisms of the etiology and progression of GC are far from clear 4 , 38 . Several genes have been identified to be associated with GC risk, including Interleukin-10 (IL-10). IL-10 is a multifunctional cytokine with anti-inflammatory properties, which has been reported involving in the some malignancies progress and development 22 , 48 . The human gene that encodes IL-10 (Gene ID: 3586) maps to the long arm of chromosome 1 (1q31-32), which contains three most common 21082A>G (rs1800896), 2592C>A (rs1800872) and 2829C>T (rs1800871) polymorphisms located within the promoter region. These polymorphisms are associated with low/high amount of IL-10 secretion 31 , 45 .

A series of epidemiological studies have reported the association of -592A>C (rs1800872) and -819T>C (rs3021097) polymorphisms of IL-10 gene with GC risk 22 , 31 , 45 , but the results remain conflicting rather than conclusive. Some meta-analyses previously published regarding the association of -592A>C (rs1800872) and -819T>C (rs3021097) polymorphisms with GC risk 4 , 48 , 55 . A few studies were not included in these meta-analyses and also original studies with larger sample sizes in different ethnicity have been published since then. In addition, some of the previous meta-analyses have reported conflicting conclusions.

Hence, we performed this meta-analysis to evaluate whether the IL-10 -592A>C and -819T>C polymorphisms contributed to the susceptibility of GC. Based on our knowledge, this is the most comprehensive and accurate meta-analysis of the association of IL-10 -592A>C and -819T>C polymorphisms with GC risk.

METHOD

Search strategy

The electronic databases of the US National Library of Medicine’s PubMed, EMBASE, Web of Knowledge, Google Scholar, Wanfang, Chinese National Knowledge Infrastructure (CNKI), and Chinese Biomedical Literature Database (CBM) were systematically searched to retrieve potential publications that assessed the association between -592A>C and -819T>C polymorphisms of IL-10 gene and GC risk up to April 10, 2018. Key search terms used were as follows: (gastric cancer OR gastric neoplasm OR stomach neoplasms) AND (Interleukin-10 OR IL-10) AND (-592A>C OR rs1800872) AND (-819T>C OR rs1800871) AND (Polymorphism OR SNP OR single nucleotide polymorphism OR variation OR mutation). This meta-analysis included only publications relating to humans, covering all relevant written in English and Chinese publications with available full-text articles. Reference lists of retrieved articles, review articles, and previous meta-analysis were also manually searched to avoid missing relevant studies.

Inclusion and exclusion criteria

Studies were included in the meta-analysis if they met the following criteria: 1) full text available; 2) case-control or cohort studies; 3) studies focus on the association of -592A>C (rs1800872) and -819T>C (rs3021097) polymorphisms of IL-10 gene with GC risk; 4) sufficient published data for genotype and allele frequencies to calculate the Odds Ratio (OR) and 95% confidence interval (CI).

Major reasons for exclusion of studies were as follows: 1) abstract, review articles, case reports, unpublished data and comments; 2) studies with overlapped or duplicate data; 3) no healthy control group established in the study; 4) studies with unclear or ambiguous data or genotype frequencies. When duplicated studies were published by the same author obtained from the same patient sample, only the one with the largest sample size was included in this meta-analysis.

Data extraction

Data were carefully extracted from all eligible studies independently by two investigators according to the inclusion and exclusion criteria. The following data were collected from each study: first author, year of publication, country origin, ethnicity, total number of cases and controls, the frequencies of genotypes, minor allele frequencies (MAFs), p-value for Hardy-Weinberg equilibrium (HWE). In case of disagreement (in the data extraction), consensus was resolved through consensus, or a third author would assess these articles. In the current meta-analysis, the quality of selected studies was tested by the confirmation of HWE in control groups, and studies without the confirmation of HWE in controls were defined as low-quality studies, while studies with the confirmation of HWE in controls were defined as high-quality studies (Table 1).

TABLE 1. The general characteristics of eligible studies in the meta-analysis of IL-10 -592A>C.

First Author Country (Ethnicity) Case Control Cases Controls MAFs HWE
Genotypes Allele Genotypes Allele
AA CA CC A C AA CA CC A C
Wu 2003 46 China (Asian) 220 230 88 105 27 281 159 127 83 20 337 123 0.267 0.231
El-Omar 2003 10 USA(Caucasian) 314 210 35 101 178 171 457 13 70 127 96 324 0.771 =0.001
Savage 2004 37 China (Asian) 84 386 9 39 36 57 111 49 166 171 205 567 0.734 0.382
Zambon 2005 53 Italy (Caucasian) 129 644 17 42 70 76 182 46 245 353 337 951 0.738 0.696
Alpizar-Alpizar 2005 1 Costa Rica(Latinos) 45 45 3 20 21 27 63 5 21 18 32 58 0.647 0.761
Lee 2005 25 Korea (Asian) 122 120 52 62 8 166 78 53 60 7 166 74 0.308 0.059
Kamangar 2006 19 Finland (Caucasian) 112 237 6 38 68 50 174 17 82 109 132 342 0.721 0.775
Sicinschi 2006 39 Mexico (Latinos) 181 369 40 90 51 170 192 95 176 98 366 372 0.504 0.376
Sugimoto 2007 43 Japan (Asian) 105 168 43 54 8 140 70 88 70 10 246 90 0.267 0.419
Garcia 2008 11 Spain (Caucasian) 404 404 24 143 237 191 617 28 131 245 187 621 0.768 0.075
Crusius 2008 5 Netherland (Caucasian) 237 1122 11 78 148 100 374 83 397 642 563 1681 0.749 0.049
Deng 2008 8 China (Asian) 125 110 30 39 56 99 151 39 25 46 103 117 0.531 =0.001
Xiao 2009 47 China (Asian) 220 624 100 100 20 300 140 272 283 69 1038 210 0.337 0.718
Kang 2009 20 Korea (Asian) 333 332 142 157 34 441 225 146 145 41 437 227 0.341 0.591
Con 2009 3 Costa Rica(Latinos) 52 191 10 26 16 44 60 23 65 103 111 271 0.709 0.015
Oh 2010 33 China (Asian) 178 362 77 81 20 235 121 167 159 36 493 231 0.319 0.861
Liu 2011 27 China (Asian) 234 243 99 96 39 294 174 109 106 28 324 162 0.333 0.772
He 2012 14 China (Asian) 196 248 82 96 18 260 132 92 128 28 312 184 0.371 0.095
Zeng 2012 54 China (Asian) 151 153 59 77 15 195 107 80 66 7 226 80 0.261 0.147
Kim 2012 22 Korea (Asian) 495 495 231 214 50 676 314 248 191 56 687 303 0.306 0.041
Pan 2013 34 China (Asian) 308 308 144 128 36 416 200 142 135 31 419 197 0.319 0.895
Kuo 2014 24 China (Asian) 358 358 186 134 38 506 210 358 180 141 501 215 0.340 =0.001
Hormazabal 2014 31 Chile (Latinos) 147 172 19 73 55 111 183 11 83 78 105 239 0.694 0.070
Yin 2015 50 China (Asian) 228 461 112 96 20 320 136 235 184 42 654 268 0.290 0.490
de Oliveira 2015 6 Brazil (Latinos) 207 240 104 82 21 290 124 169 64 7 402 78 0.162 0.753
Ma 2016 28 China (Asian) 147 150 67 63 17 197 97 71 67 12 208 92 0.303 0.486
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Statistical analysis

All meta-analyses were conducted using Comprehensive Meta-Analysis (CMA) software (USA, version 2.2.064) and a p value below 0.05 was considered statistically significant. The strength of the association of -592A>C and -819T>C polymorphisms of IL-10 gene with GC risk was estimated by crude odds ratios (ORs) with corresponding 95% confidence intervals (CIs). The significance of the pooled OR was determined by the Z-test. An allele contrast model (C vs. T), homozygote model (CC vs. TT), heterozygote model (CT vs. TT), dominant (CC+CT vs. TT), and recessive (CC vs. CT+TT) model were used for IL-10 -819T>C polymorphism. An allele contrast model (C vs. A), homozygote model (CC vs. AA), heterozygote model (CA vs. AA), dominant (CC+CA vs. AA), and recessive (CC vs. CA+AA) model were used for -592A>C polymorphism. The Cochran chi-square-based Q statistical test was used to evaluate statistical between-study heterogeneity (with p<0.05 for statistical significance). In addition, a quantitative measure of between-study heterogeneity was also investigated using the I 2 statistic, and which the between-study heterogeneity was considered low, moderate, and high based on I 2 values of 25%, 50%, and 75%, respectively 18 . If the between-study heterogeneity was statistically significant the random effects model 7 was applied; otherwise, the fixed effects model 29 was used. The sensitivity analysis was performed to assess the contribution of individual studies to pooled effect estimate by sequentially removing each study one at a time and computing differential estimates for rest. In addition, sensitivity analysis was performed by excluding the low quality studies to test the stability of the results. Publication bias was examined using the Begg’s funnel plot and Egger’s test 2 , 9 . If publication bias existed, the Duval and Tweedie non-parametric ‘’trim and fill’’ method was used to adjust for it. Subgroup analyses by ethnicity and studies quality (by HWE status) were performed subsequently. The distribution of genotypes in control groups was evaluated for a departure from HWE using chi-square test.

RESULTS

Characteristics of studies

Tables 1 and 2 showed the characteristics of all the eligible studies selected in the meta-analysis. The study selection processes were presented in Figure 1 (PRISMA 2009 Flow Diagram). We evaluated all the retrieved studies by examining titles, abstracts and conclusions. According to the criteria eligibility, 44 studies in 29 publications was identified regarding the association between the IL-10 -592A>C and -819T>C polymorphisms with susceptibility to the GC. All of these 44 case-control studies provided sufficient data to calculate the association between the IL-10 -592A>C 1 , 3 , 5 , 6 , 8 , 10 , 11 , 14 , 19 , 20 , 22 , 24 , 25 , 27 , 28 , 31 , 33 , 34 , 43 , 46 , 47 , 37 , 39 , 50 , 53 , 54 and -819T>C 1 , 5 , 14 , 19 , 22 - 24 , 26 , 27 , 33 , 37 , 43 , 42 , 46 , 47 , 51 , 53 , 54 polymorphisms with risk of GC. The characteristics of the selected studies are summarized in Tables 1 and 3. Among these studies, 26 case-control studies evaluated the association of the -592A>C polymorphism with GC with 5,332 cases and 8,272 controls, included five groups of Caucasians 5 , 10 , 11 , 19 , 53 , 16 groups of Asians 8 , 14 , 20 , 22 , 24 , 25 , 27 , 28 , 33 , 34 , 37 , 43 , 47 , 46 , 50 , 54 , and five Latinos populations 1 , 3 , 6 , 31 , 39 (Table 1). While, 18 case-control studies evaluated the association between the -819T>C polymorphisms and GC risk, with 3,431 cases and 6,109 controls, included three groups of Caucasians 5 , 19 , 53 , 14 groups of Asians 14 , 22 - 24 , 26 , 27 , 33 , 37 , 42 , 43 , 46 , 47 , 51 , 54 , and one Latinos populations 1 (Table 2). The countries of these studies included China, Korea, Japan, India, USA, Italy, Finland, Spain, Netherland, Costa Rica, Brazil, Mexico and Chile. All the genotype distributions of controls were in agreement with HWE for IL-10 -592A>C and -819T>C polymorphisms except for nine studies in five publications 11 , 21 , 30 , 31 , 40 . Therefore, 35 of 44 case-control studies were defined as high-quality studies (Tables 1 and 2).

FIGURE 1. Flow chart of studies selection in this meta-analysis (IL-10 -592A>C and -819T>C Polymorphisms).

FIGURE 1

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TABLE 2. The general characteristics of eligible studies in the meta-analysis of IL-10 -819T>C.

First Author Country (Ethnicity) Case Control Cases Controls MAFs HWE
Genotypes Allele Genotypes Allele
TT CT CC T C TT CT CC T C
Wu 2003 46 China (Asian) 220 230 88 105 27 281 159 127 83 20 337 123 0.267 0.231
Savage 2004 37 China (Asian) 84 382 37 38 9 112 56 170 163 49 503 261 0.341 0.314
Zambon 2005 53 Italy (Caucasian) 129 644 17 42 70 76 182 46 245 353 337 951 0.738 0.696
Alpizar-Alpizar 2005 1 Costa Rica (Latinos) 45 45 4 16 25 24 66 3 24 18 30 60 0.666 0.179
Kamangar 2006 19 Finland (Caucasian) 98 152 5 35 58 45 151 10 62 80 114 222 0.730 0.662
Sugimoto 2007 43 Japan (Asian) 105 168 42 57 6 141 69 86 73 9 245 91 0.270 0.194
Crusius 2008 5 European (Caucasian) 229 1094 12 72 145 96 362 80 378 636 538 1650 0.754 0.023
Xiao 2009 47 China (Asian) 220 624 100 100 20 300 140 272 283 69 827 421 0.337 0.718
Oh 2010 33 China (Asian) 188 379 81 87 20 249 127 179 158 42 516 242 0.319 0.425
Su 2010 42 China (Asian) 43 100 18 21 4 57 29 51 43 6 145 55 0.275 0.433
Liu 2011 27 China (Asian) 234 243 99 96 39 294 174 109 106 28 324 162 0.333 0.772
He 2012 14 China (Asian) 196 248 82 96 18 260 132 92 128 28 312 184 0.371 0.095
Yuan 2012 51 China (Asian) 279 296 108 129 42 345 213 142 120 34 404 188 0.317 0.265
Zeng 2012 54 China (Asian) 151 153 60 80 11 200 102 78 65 10 221 85 0.277 0.466
Kim 2012 22 Korea (Asian) 495 495 231 214 50 676 314 248 191 56 687 303 0.306 0.041
Kuo 2014 24 China (Asian) 358 358 190 132 36 512 204 186 132 40 504 212 0.296 0.028
Kumar 2015 23 India (Asian) 200 250 36 103 61 175 225 30 119 101 179 321 0.642 0.574
Li 2016 26 China (Asian) 157 248 36 83 38 155 159 36 127 85 199 297 0.598 0.300
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Meta-analysis

IL-10 -592A>C Polymorphism

Table 3 listed the main results of the meta-analysis of IL-10 -592A>C polymorphism and GC risk. When all the eligible studies were pooled into the meta-analysis of IL-10 -592A>C polymorphism, a significant association was found only under the heterozygote model (CA vs. AA: OR=1.153, 95% CI=1.020-1.305, p=0.023, Figure 2A). In addition, significant between-study heterogeneity was detected in all genetic models. When stratified by ethnicity, a significant association between of IL-10 -592A>C polymorphism and increased GC risk among Asians was detected under the allele model (C vs. A: OR=1.153, 95% CI=1.007-1.320, p=0.040) and the heterozygote model (CA vs. AA: OR=1.218, 95% CI=1.076-1.379, p= 0.002), but not among Caucasian and Latinos populations. Subgroup analysis of studies with high quality showed that there was a significant association between IL-10 -1082 A>G polymorphism and increased risk of GC only under the allele model (OR=1.154, 95% CI=1.004-1.326, p=0.044, Table 2).

TABLE 3. The meta-analysis of IL-10 -592A>C polymorphism and risk of GC.
Subgroup Study number Genetic model Type of model Heterogeneity Odds ratio Publication Bias
I2 (%) PH OR 95% CI Ztest POR PBeggs PEggers
Overall 26 C vs. A Random 76.40 =0.001 1.104 0.982-1.241 1.657 0.097 0.724 0.974
26 CC vs. AA Random 63.55 =0.001 1.081 0.868-1.345 0.694 0.488 0.427 0.401
26 CA vs. AA Random 44.34 0.009 1.153 1.020-1.305 2.268 0.023 0.860 0.569
26 CC+CA vs. AA Random 89.63 =0.001 1.085 0.828-1.422 0.589 0.556 0.964 0.559
26 CC vs. CA+ AA Random 77.34 =0.001 1.003 0.815-1.235 0.030 0.976 0.171 0.254
By Ethnicity
Caucasian 5 C vs. A Random 67.19 0.016 0.992 0.797-1.235 -0.007 0.944 0.806 0.953
5 CC vs. AA Random 65.33 0.021 0.959 0.572-1.608 -0.157 0.875 0.806 0.601
5 CA vs. AA Random 60.26 0.039 0.891 0.540-1.470 -0.452 0.651 1.000 0.869
5 CC+CA vs. AA Random 81.47 =0.001 1.125 0.569-2.223 0.339 0.735 0.462 0.252
5 CC vs. CA+ AA Random 55.56 0.061 1.071 0.922-1.245 0.895 0.371 0.462 0.456
Asian 17 C vs. A Random 73.59 0.001 1.153 1.007-1.320 2.057 0.040 0.224 0.664
17 CC vs. AA Random 59.74 0.001 1.193 0.937-1.519 1.429 0.153 0.029 0.003
17 CA vs. AA Random 40.21 0.044 1.218 1.076-1.379 3.111 0.002 0.536 0.356
17 CC+CA vs. AA Random 92.39 =0.001 1.133 0.810-1.585 0.728 0.467 0.483 0.648
17 CC vs. CA+ AA Random 81.80 =0.001 1.050 0.755-1.461 0.290 0.771 0.052 0.013
Latinos 5 C vs. A Random 87.97 =0.001 1.053 0.660-1.681 0.216 0.829 0.806 0.759
5 CC vs. AA Random 80.95 0.001 0.518 0.151-1.776 -1.047 0.295 0.308 0.373
5 CA vs. AA Fixed 20.76 0.286 1.001 0.707-1.418 0.007 0.995 1.000 0.737
5 CC+CA vs. AA Fixed 55.11 0.083 0.925 0.667-1.283 -0.469 0.639 1.000 0.591
5 CC vs. CA+ AA Random 65.75 0.033 0.787 0.491-1.261 -0.997 0.319 0.734 0.757
High Quality Studies        
20 C vs. A Random 77.22 =0.001 1.154 1.004-1.326 2.012 0.044 0.417 0.791
20 CC vs. AA Random 54.37 0.002 1.191 0.989-1.342 1.820 0.069 0.381 0.717
20 CA vs. AA Random 45.14 0.015 1.131 0.982-1.304 1.710 0.087 0.721 0.873
20 CC+CA vs. AA Random 63.33 =0.001 1.176 0.997-1.387 1.930 0.054 0.256 0.630
20 CC vs. CA+ AA Fixed 31.81 0.086 1.079 0.961-1.211 1.285 0.199 0.040 0.029
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FIGURE 2. Forest plot of the association of IL-10 -592A>C and -819T>C Polymorphisms with GC: A) -592A>C (homozygote model: C vs. A); B) -819T>C (dominant model: CC+CT vs. TT).

FIGURE 2

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IL-10 -819T>C Polymorphism

Table 4 and Figure 2B showed the main results of the meta-analysis of IL-10 -819T>C polymorphism and GC risk. When all the eligible studies were pooled into the meta-analysis of IL-10 -819T>C polymorphism, no significant association was observed in any genetic model. In the stratified analyses based on ethnicity and studies quality, there was not still significant association between IL-10 -819T>C polymorphism and risk of GC.

TABLE 4. The meta-analysis of IL-10 -819T>C polymorphism and risk of GC.
Subgroup Study number Genetic model Type of model Heterogeneity Odds ratio Publication Bias
I2 (%) PH OR 95% CI Ztest POR PBeggs PEggers
Overall 18 C vs. T Random 58.48 0.001 1.057 0.950-1.177 1.017 0.309 0.820 0.381
18 CC vs. TT Random 46.47 0.016 0.987 0.795-1.225 -0.120 0.905 0.544 0.469
18 CT vs. TT Random 44.86 0.021 1.092 0.943-1.264 1.171 0.242 0.324 0.376
18 CC+CT vs. TT Random 55.29 0.002 1.078 0.923-1.259 0.948 0.343 0.404 0.621
18 CC vs. CT+ TT Fixed 25.96 0.150 1.003 0.890-1.131 0.056 0.955 0.448 0.492
By Ethnicity
Caucasian 3 C vs. T Fixed 50.64 0.132 1.086 0.914-1.289 0.937 0.349 1.000 0.982
3 CC vs. TT Random 66.66 0.050 1.008 0.474-2.144 0.021 0.983 1.000 0.753
3 CT vs. TT Fixed 59.86 0.083 0.803 0.524-1.232 -1.004 0.315 1.000 0.799
3 CC+CT vs. TT Random 67.42 0.046 0.938 0.445-1.980 -0.167 0.867 1.000 0.744
3 CC vs. CT+ TT Fixed 0.00 0.552 1.163 0.941-1.438 1.398 0.162 1.000 0.979
Asian 14 C vs. T Random 63.82 0.001 1.046 0.924-1.184 0.708 0.479 0.742 0.499
14 CC vs. TT Random 49.48 0.018 0.987 0.778-1.254 -0.104 0.917 0.661 0.545
14 CT vs. TT Random 42.40 0.047 1.132 0.980-1.307 1.684 0.092 0.742 0.879
14 CC+CT vs. TT Random 57.22 0.004 1.105 0.942-1.295 1.224 0.221 0.584 0.826
14 CC vs. CT+ TT Fixed 20.33 0.232 0.917 0.792-1.062 -1.157 0.247 0.125 0.170
High Quality Studies
15 C vs. T Random 54.22 0.006 1.085 0.966-1.219 1.377 0.169 0.552 0.391
15 CC vs. TT Random 52.77 0.009 0.974 0.742-1.278 -0.191 0.848 0.620 0.488
15 CT vs. TT Random 52.86 0.008 1.077 0.894-1.297 0.779 0.436 0.276 0.326
15 CC+CT vs. TT Random 61.51 0.001 1.063 0.874-1.294 0.611 0.541 0.198 0.460
15 CC vs. CT+ TT Fixed 30.61 0.125 0.980 0.848-1.132 -0.275 0.784 0.322 0.150
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Heterogeneity and sensitivity analysis

As shown in Tables 3 and 4, there was a significant between-study heterogeneity for IL-10 -592A>C polymorphism under all genetic models (C vs. A: Ph=0.001; CC vs. AA: Ph=0.001; CA vs. AA: Ph=0.009; CC+CA vs. AA: Ph=0.001; CC vs. CA+ AA: Ph=0.001), and for of IL-10 -819T>C (rs3021097) polymorphism under four genetic models (C vs. A: Ph=0.001; CC vs. TT: Ph=0.0160.001; CT vs. TT: Ph=021; and CC+CT vs. TT: Ph=0.002), except the recessive genetic model (CC vs. CT+ TT: Ph=0.150). We performed sensitivity analysis by omitting one study at a time and calculating the pooled ORs again. However, the results did not show any significant statistical differences when studies were omitted. Therefore, the stability of the study was not influenced by any individual study.

Publication bias

Both Begg’s funnel plot and Egger’s test were carried out to evaluate the publication bias of the studies. Tables 3 and 4 presents the results of Begg’s funnel plot and Egger’s test under the five genetic models. As shown in Figure 3A, the shapes of the Begg’s funnel plots under the allele model of IL-10 -592A>C polymorphism shown approximately symmetrical and significant evidence of publication bias was not observed by the Egger’s test. As for the IL-10 -819T>C polymorphism, the shapes of the Begg’s funnel plots under the heterozygote comparison model seemed symmetrical (Figure 3B). In addition, the Egger’s tests (all p values for Egger’s test>0.05) also showed that there was no evidence of publication bias for both polymorphisms.

FIGURE 3. Funnel plot for publication bias in the meta-analysis of the IL-10 -592A>C and -819T>C Polymorphisms with GC: A) -592A>C (heterozygote model: CA vs. AA); B) -819T>C (allele model: C vs. T).

FIGURE 3

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DISCUSSION

A meta-analysis can combine results from individual studies to overcome the limitation of small sample sizes and inadequate statistical power, produce a single estimate of the major effect, answer questions not resolved by the individual studies, resolve controversial debates arising from conflicting studies and cite limitations of current knowledge 12 , 15 . To date, several meta-analyses have been performed to evaluate the association of the IL-10 gene promoter -592A>C and -819T>C polymorphisms with GC. However, due to lack of ability to obtain overall reliable conclusions because of limited sample sizes, a consensus has not been reached. Therefore, to better elucidate the association of the IL-10 -592A>C and -819T>C polymorphisms with GC, we performed an updated and more comprehensive meta-analysis by collecting 44 relevant case-control studies in 29 publications.

In 2014, Qi et al., in a meta-analysis of twelve studies, with 2,116 GC cases and 4,077 controls, reported that there was no significant association between the IL-10 -592C>A polymorphism and GC risk in overall population 35 . Since then, a series of better designed case-control studies on the association between IL-10 -592C>A polymorphism and GC were performed. Therefore, their results as a meta-analysis essentially remain an open field. In the current meta-analysis, 26 eligible case-control studies with 5,332 cases and 8,272 controls were identified and analyzed. Our results showed that there was a significant association between the IL-10 -592C>A polymorphism and susceptibility to GC in total population. Moreover, compared with Qi et al meta-analysis the allele genetic model and subgroup analysis among Latinos were also carried out. In this meta-analysis we found that the IL-10 -592C>A polymorphism was associated with GC risk in Asians under the allele model (C vs. A: OR=1.153, 95% CI=1.007-1.320, p=0.040) and the heterozygote model (CA vs. AA: OR=1.218, 95% CI=1.076-1.379, p=0.002). In addition, it is worth noting that the association between IL-10 -592C>A polymorphism and GC risk was significant by studies quality under the allele model (OR=1.154, 95% CI=1.004-1.326, p=0.044).

In 2016, Cui et al., performed a meta-analysis to assess the susceptibility of the IL-10 -819T>C polymorphism to GC including eleven articles with 1,960 cases and 3,705 controls 4. Their results suggested that L-10 -819T>C polymorphism has a protective role in susceptibility to GC. Although their results suggested that the IL-10 -819T>C polymorphism might not contribute to the risk of GC; however, these studies were with small number of cases and controls. In the current meta-analysis, we included a total of 18 case-control studies with 3,431 cases and 6,109 controls. The pooled results indicated that there was no obvious association between IL-10 -819T>C polymorphism to GC. Therefore, our meta-analysis not only confirmed Cui et al results, but also provided most reliable statistical results by including more seven case-control studies 4 .

Heterogeneity between studies is common in the meta-analysis of genetic association studies 41 , 49 . In each case, the heterogeneity could be a result of different covariates such as ethnicity, sources of controls, sample size, HWE and methods used and so on 16 , 17 , 30 . In the current meta-analysis, significant between-study heterogeneity was detected across studies under all genetic models and thus we selected the random-effects model to summarize the ORs. Therefore, we performed meta-regression analysis to find the source of between-study heterogeneity. The results showed that ethnicity and studies quality did not contribute to substantial between-study heterogeneity in the current meta-analysis. Moreover, we have performed sensitivity analysis according to sample size and leave-one-out analysis to determine whether modification of the inclusion criteria by removing one study each time affected the results. However, for both IL-10 -592A>C and -819T>C polymorphisms, the sensitivity analyses did not materially affected the original results.

The present meta-analysis has some advantages compared to the previous meta-analyses. However, it does have some limitations that should be taken into account. First, we have included only studies published in the English and Chinese language in this meta-analysis; therefore, publication bias may have occurred. Second, in this meta-analysis the great proportion of statistical power was contributed by the Asian ethnicity. There were not enough studies in Caucasians and Latinos, which limited the statistical power. Moreover, African was one of the three largest ethnics, but we have not found any study on Africans. Third, the current meta-analysis was performed to analyze these polymorphisms separately; however, a haplotype analysis may have been more powerful for finding significant associations with GC. Forth, the ORs extracted from each eligible study were based on unadjusted estimates, while a more precise analysis should be performed in all individual data available, which would allow for the adjustment by other co-variants including age, environmental exposures, smoking status, and other lifestyle factors. Finally, gene-gene and gene-environment interactions which may modulate the GC susceptibility were not addressed in this meta-analysis for the lack of sufficient data.

CONCLUSION

The current meta-analysis results inconsistent with the previous meta-analyses showed that the IL-10 -592A>C polymorphism contributed to the susceptibility of GC in overall population, particularly in Asian populations. However, the IL-10 -819T>C polymorphism was not associated with an increased risk of GC. Further large well-designed studies are still needed to determine the effects of the IL-10 -592A>C and -819T>C polymorphisms on GC.

Footnotes

Financial source:none

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