Some studies have reported that proinflammatory polymorphisms in interleukin-1B (IL-1B) and IL-1 receptor antagonist (IL-1RN) genes are associated with increased gastric cancer risk. However, other studies have shown null or inverse associations. This meta-analysis reviews and summarizes published evidence for these associations. Searching the PubMed Database yielded 35 studies that reported on the association between IL-1B −511 C>T, IL-1B −31 T>C, or IL-1RN variable number tandem repeat polymorphisms and gastric cancer risk. Q-statistics and I2 statistics were calculated to examine heterogeneity. Summary odds ratios (OR) and 95% confidence intervals (95% CI) were calculated in the random-effects model using the DerSimonian-Laird method. For all gastric cancers, the overall ORs (95% CIs) for IL-1B −511 CT versus CC and TT versus CC genotypes were 1.07 (0.91-1.25) and 1.16 (0.95-1.42), respectively. ORs (95% CIs) for the association between IL-1B −31 CT versus TT and CC versus TT genotypes were 0.99 (0.83-1.19) and 0.98 (0.78-1.21), respectively. For the associations between IL-1RN and gastric cancer, ORs (95% CIs) for *2/L versus LL and *2/*2 versus L/L were 1.15 (0.96-1.38) and 1.23 (0.79-1.92). For each of the examined associations, there was significant heterogeneity among studies; Pheterogeneity ≤ 0.001 and I2 ranged from 0.54 to 0.71. Noncardia cancers showed stronger associations with IL-1B −511 CT or TT and IL1-RN *2/*2 genotypes, but limiting the analysis to intestinal-type cancers, studies conducted in Western countries, or studies in which polymorphisms were in Hardy-Weinberg equilibrium, made no material difference in the results. The overall associations between IL-1B or IL-1RN proinflammatory polymorphisms and gastric cancer were null but several studies showed an association. The sources of this variation are unclear. (Cancer Epidemiol Biomarkers Prev 2006;15(10):1920–8)

Helicobacter pylori infection is the most important identified risk factor for gastric cancer. However, <3% of individuals infected with H. pylori are ever diagnosed with gastric cancer (1). Variations in cancer risk in H. pylori–infected individuals may, in part, be attributed to genetic predisposition.

A study published in Nature showed for the first time that polymorphisms in interleukin-1B (IL-1B) and IL-1RN genes were associated with gastric cancer risk (2). These two genes, respectively, encode for IL-1β, a strong proinflammatory cytokine, and IL-1 receptor antagonist, an anti-inflammatory cytokine that competes with IL-1 in binding to its receptor. Two linked IL-1B single nucleotide polymorphisms that increase IL-1β expression (−511 C>T) and (−31 T>C) were associated with a 2- to 3-fold increased risk of gastric cancer (2). The IL-1RN gene has a penta-allelic variable number tandem repeat polymorphism and allele 2 (IL-1RN*2), which encodes for only two repeats, was associated with a higher risk of gastric cancer than other alleles, which encode for longer (L) repeats. Several subsequent studies also found an association between IL-1B −511 T and −31 C and IL-1RN*2 and increased gastric cancer risk (3-6). Some of these studies found an association only with certain anatomic subsites (i.e., noncardia; ref. 3) or histologic subtypes (i.e., intestinal type; ref. 6) of gastric cancer. In contrast, several other studies failed to find an association between these polymorphisms and gastric cancer or its anatomic and histologic subtypes.

In this meta-analysis, we review studies that have examined the associations between IL-1B −511, IL-1B −31, and IL-1RN polymorphisms and gastric cancer risk. Where possible, we also review these associations by anatomic or histologic subtypes of gastric cancer.

Selection of Studies

We searched the PubMed Database for all articles that were published by January 19, 2006 on the association between IL-1B polymorphisms and gastric cancer risk. The following terms were used in this search: (IL-1B or IL-1 or interleukin or cytokine) and (gastric cancer or stomach cancer) and (polymorphism or polymorphisms).

Using these terms, a total of 131 articles were retrieved, of which 40 (2-41) reported on studies examining the associations between IL-1B or IL1-RN polymorphisms and gastric adenocarcinoma. Two articles included data from two geographic regions (25, 39). We considered each region a separate study. Therefore, a total of 42 studies were identified. Five studies (4, 6, 10, 15, 34) were excluded from this analysis because their results were repeated in subsequent publications (5, 22, 35, 39). Two more studies (30, 38) were excluded because complete data on genotypes were not presented in the articles. Therefore, a total of 35 studies were used for calculating summary statistics.

Statistical Analysis

All analyses were done using STATA software, version 8.0 (STATA Corp., College Station, TX). Throughout the article, two-sided Ps < 0.05 were considered as statistically significant.

For IL-1B −511, numbers and percentages of CC, CT, and TT genotypes were extracted by case status, and odds ratios (OR) and 95% confidence intervals (95% CI) were calculated for CT and TT (the proinflammatory genotypes) versus CC genotype. The Q-statistics for homogeneity (using Mantel-Haenszel weights) and the I2 statistics (42) were calculated. The Q-statistics were highly significant (P < 0.001) and I2 (60%) showed a high degree of heterogeneity. Therefore, we used random-effects models (DerSimonian-Laird method; ref. 43) to calculate summary ORs and 95% CIs (44, 45). To estimate the sensitivity of the summary OR to the choice of model, we also calculated and report the summary ORs and 95% CI using fixed effects models (Mantel-Haenszel method). Similar procedures were used for IL-1B −31 and IL-1RN. For IL-1B −31, ORs and 95% CIs were calculated for CC and CT (the proinflammatory genotypes) versus TT genotype. For IL-1RN, *2 was the proinflammatory allele, and ORs and 95% CIs were calculated for *2/*2 and *2/L versus L/L.

Some of these studies found an association only with certain anatomic subsites (i.e., noncardia; ref. 3) or histologic subtypes (i.e., intestinal type; ref. 6) of gastric cancer. Therefore, we calculated summary ORs and 95% CIs for noncardia cancer, where genotype data were presented by anatomic location, and for intestinal type cancer, where data on histology was available. Seven, nine, and seven studies reported data on IL-1B −511, IL-1B −31, and IL-1RN polymorphisms, respectively, and noncardia cancer. Ten, eight, and seven studies reported data on these same polymorphisms, respectively, and intestinal-type cancer. There is also a suggestion that proinflammatory polymorphisms in interleukins may be associated with higher risk of gastric cancer in Western countries but not in East-Asian countries. Therefore, study populations were classified as Western (Europe, North, and Central America) versus East-Asian (China, Japan, Korea, and Taiwan), and subgroup analyses were done for each group. In all, 17 studies were from Western and 18 studies were from East-Asian countries.

We used three strategies to select studies that were less likely to have had genotyping errors. First, for IL-1B −511 and −31, we examined the presence of Hardy-Weinberg equilibrium (HWE) and calculated summary ORs and 95% CIs for studies, in which these alleles were in HWE among controls. Second, using a χ2 test with 2 degrees of freedom, we examined the consistency of distributions of IL-1B −511 T and IL-1B −31 C among controls (at α = 0.05) and calculated summary ORs and 95% CIs for studies in which these two distributions were consistent. This strategy was adopted because IL-1B −511 T and IL-1B −31 C alleles are in near-perfect linkage disequilibrium (46, 47). Third, ORs and 95% CIs were calculated for studies, which passed both of these criteria (i.e., alleles were in HWE and distributions of IL-1B −511 T and IL-1B −31 C were consistent).

In addition, we examined whether correcting for deviations from HWE affected the overall results. Whereas the analyses discussed in the previous paragraph excluded studies in which genotypes violated HWE at α = 0.05, HWE correction enabled all studies to be included. For this analysis, we calculated expected genotype frequencies under HWE for controls based on observed allele prevalences. We then recalculated the ORs using the observed genotype frequencies in cases and the HWE-expected genotype frequencies in controls (48) and used the Lathrope estimate of variance to estimate 95% CIs (48). These corrections had negligible effects on the results; therefore, the results are not shown in this report.

We also did cumulative meta-analysis to evaluate the trend of summary ORs (95% CIs) by year of publication. Studies were added one at a time according to year of publication and the results were summarized as each new study was added.

Overall, 35 studies with a total number of 5,503 cases and 7,865 controls were included in this analysis. Of these, 28, 22, and 26 studies presented data on IL-1B −511, IL-1B −31, and IL-1RN, respectively. Study characteristics are summarized in Table 1. Most studies used healthy volunteers or blood donors as control subjects. The prevalence of IL-1B −511 T and IL-1B −31 C alleles ranged from 27% to 57%, and 30% to 90% in various studies. Median prevalences of IL-1B −511 T and IL-1B −31 C were 35% and 39% in Western populations, whereas these respective prevalences were 50% and 52% in East-Asian populations.

Table 1.

Study characteristics

First authorStudy location*YearNo. cases/controlsSource of control selection% IL-1B −511 T% IL-1B −31 C§HWE −511, PHWE −31, Pχ2, P**
1. El-Omar Poland (W) 2000 366/429 Population based 30 30 0.10 0.07 0.99 
2. Kato Japan (E) 2001 127/335 Clinic based 49  0.70   
3. He China (E) 2002 50/50 Healthy volunteers  75  0.92  
4. Zambon Italy (W) 2002 23/219 Clinic based  34  1.00  
5. El-Omar United States (W) 2003 314/210 Population based 27  0.02   
6. Lee SG Korea (E) 2003 190/172 Healthy volunteers  51  0.22  
7. Machado Portugal (W) 2003 287/306 Healthy volunteers 34  0.27   
8. Zeng-Guandong China (E) 2003 84/192 Healthy volunteers 34 90 0.17 0.52 0.001 
9. Zeng-Shanxi China (E) 2003 86/169 Healthy volunteers 51 86 0.05 0.02 0.001 
10. zur Hausen Netherlands (W) 2003 69/153 Healthy volunteers 34  0.90   
11. Chen Taiwan (E) 2004 142/164 Healthy volunteers 51  0.08   
12. Gatti Brazil (W) 2004 56/56 Healthy volunteers 57 48 0.001 0.11 0.10 
13. Glas Gemany (W) 2004 88/145 Healthy volunteers 35 35 0.14 0.14 1.00 
14. Hartland United Kingdom (W) 2004 59/287 Healthy volunteers 41  0.002   
15. Kang Korea (E) 2004 242/97 Healthy volunteers 48 51 0.76 0.25 0.69 
16. Lee KA Korea (E) 2004 331/433 Clinic based 54 55 0.49 0.79 0.94 
17. Wu Taiwan (E) 2004 204/210 Clinic-based 45 45 0.10 0.17 0.98 
18. Yang China (E) 2004 280/258 Population based 52 52 0.37 0.73 0.68 
19. Alpizar-Alprizar Costa Rica (W) 2005 50/50 Clinic-based 57 59 0.66 0.73 0.96 
20. Chang Korea (E) 2005 234/434 Clinic-based 52 52 0.007 0.005 0.99 
21. Garza-Gonzalez Mexico (W) 2005 63/215 Clinic based  56  0.60  
22. Lu China (E) 2005 250/300 Population based 51 54 0.13 0.99 0.28 
23. Muramatsu Japan (E) 2005 89/96 Healthy volunteers 41  0.60   
24. Palli Italy (W) 2005 185/546 Population based  34  0.44  
25. Perri-North Italy (W) 2005 98/216 Healthy volunteers 36  0.95   
26. Perri-South Italy (W) 2005 86/146 Healthy volunteers 32  0.85   
27. Rocha Brazil (W) 2005 166/536 Healthy volunteers  45  0.82  
28. Ruzzo Italy (W) 2005 138/100 Healthy volunteers 31 37 0.22 0.32 0.45 
29. Sakuma Japan (E) 2005 140/103 Healthy volunteers 49  0.37   
30. Sicinschi Mexico (W) 2005 158/317 Clinic based  65  0.006  
31. Taguchi Japan (E) 2005 373/250 Healthy volunteers  46 0.27   
32. Tatemichi Japan (E) 2005 156/176 Healthy volunteers  49 0.99   
33. Vilaichione Thailand (E) 2005 39/91 Clinic based  52 0.001   
34. Zhang China (E) 2005 154/166 Healthy volunteers 53 43 0.07 0.58 0.05 
35. Kamangar Finland (W) 2006 112/207 Healthy cohort subjects 38 39 0.01 0.07 0.81 
First authorStudy location*YearNo. cases/controlsSource of control selection% IL-1B −511 T% IL-1B −31 C§HWE −511, PHWE −31, Pχ2, P**
1. El-Omar Poland (W) 2000 366/429 Population based 30 30 0.10 0.07 0.99 
2. Kato Japan (E) 2001 127/335 Clinic based 49  0.70   
3. He China (E) 2002 50/50 Healthy volunteers  75  0.92  
4. Zambon Italy (W) 2002 23/219 Clinic based  34  1.00  
5. El-Omar United States (W) 2003 314/210 Population based 27  0.02   
6. Lee SG Korea (E) 2003 190/172 Healthy volunteers  51  0.22  
7. Machado Portugal (W) 2003 287/306 Healthy volunteers 34  0.27   
8. Zeng-Guandong China (E) 2003 84/192 Healthy volunteers 34 90 0.17 0.52 0.001 
9. Zeng-Shanxi China (E) 2003 86/169 Healthy volunteers 51 86 0.05 0.02 0.001 
10. zur Hausen Netherlands (W) 2003 69/153 Healthy volunteers 34  0.90   
11. Chen Taiwan (E) 2004 142/164 Healthy volunteers 51  0.08   
12. Gatti Brazil (W) 2004 56/56 Healthy volunteers 57 48 0.001 0.11 0.10 
13. Glas Gemany (W) 2004 88/145 Healthy volunteers 35 35 0.14 0.14 1.00 
14. Hartland United Kingdom (W) 2004 59/287 Healthy volunteers 41  0.002   
15. Kang Korea (E) 2004 242/97 Healthy volunteers 48 51 0.76 0.25 0.69 
16. Lee KA Korea (E) 2004 331/433 Clinic based 54 55 0.49 0.79 0.94 
17. Wu Taiwan (E) 2004 204/210 Clinic-based 45 45 0.10 0.17 0.98 
18. Yang China (E) 2004 280/258 Population based 52 52 0.37 0.73 0.68 
19. Alpizar-Alprizar Costa Rica (W) 2005 50/50 Clinic-based 57 59 0.66 0.73 0.96 
20. Chang Korea (E) 2005 234/434 Clinic-based 52 52 0.007 0.005 0.99 
21. Garza-Gonzalez Mexico (W) 2005 63/215 Clinic based  56  0.60  
22. Lu China (E) 2005 250/300 Population based 51 54 0.13 0.99 0.28 
23. Muramatsu Japan (E) 2005 89/96 Healthy volunteers 41  0.60   
24. Palli Italy (W) 2005 185/546 Population based  34  0.44  
25. Perri-North Italy (W) 2005 98/216 Healthy volunteers 36  0.95   
26. Perri-South Italy (W) 2005 86/146 Healthy volunteers 32  0.85   
27. Rocha Brazil (W) 2005 166/536 Healthy volunteers  45  0.82  
28. Ruzzo Italy (W) 2005 138/100 Healthy volunteers 31 37 0.22 0.32 0.45 
29. Sakuma Japan (E) 2005 140/103 Healthy volunteers 49  0.37   
30. Sicinschi Mexico (W) 2005 158/317 Clinic based  65  0.006  
31. Taguchi Japan (E) 2005 373/250 Healthy volunteers  46 0.27   
32. Tatemichi Japan (E) 2005 156/176 Healthy volunteers  49 0.99   
33. Vilaichione Thailand (E) 2005 39/91 Clinic based  52 0.001   
34. Zhang China (E) 2005 154/166 Healthy volunteers 53 43 0.07 0.58 0.05 
35. Kamangar Finland (W) 2006 112/207 Healthy cohort subjects 38 39 0.01 0.07 0.81 
*

W, Western country; E, East-Asian country.

Publication year.

Percent IL-1B −511 T allele in controls.

§

Percent IL-1B −31 C allele in controls.

P for HWE for IL-1B −511 polymorphism among controls.

P for HWE for IL-1B −31 polymorphism among controls.

**

P for consistency of the association of IL-1B −511 T and IL-1B −31 C polymorphisms.

IL-1B −511

Study-specific ORs (95% CIs) are shown in Fig. 1. For all gastric cancers, the overall ORs (95% CIs) associated with CT versus CC and TT versus CC genotypes were 1.07 (0.91-1.25) and 1.16 (0.95-1.42), respectively. For noncardia cancers, these ORs (95% CIs) were 1.26 (0.84-1.89) for CT and 1.78 (0.92-3.47) for TT genotypes. For intestinal-type gastric cancers, ORs (95% CIs) were 1.25 (0.98-1.59) and 1.35 (0.87-2.10), respectively. When we limited our analysis to studies from Western countries, ORs (95% CIs) were 1.03 (0.76-1.39) and 1.32 (0.86-2.02), respectively. For East-Asian studies, the corresponding numbers were 1.05 (0.90-1.23) and 1.03 (0.87-1.21), respectively.

Figure 1.

Forest plot for the association between IL-1B −511 CT versus CC and TT versus CC genotypes and gastric cancer risk, in order of publication year. A.IL-1B −511 CT versus CC. B.IL-1B −511 TT versus CC.

Figure 1.

Forest plot for the association between IL-1B −511 CT versus CC and TT versus CC genotypes and gastric cancer risk, in order of publication year. A.IL-1B −511 CT versus CC. B.IL-1B −511 TT versus CC.

Close modal

IL-1B −31

Figure 2 summarizes the ORs and 95% CIs for the associations between IL-1B −31 genotypes and gastric cancer risk. For all gastric cancers, the overall ORs (95% CIs) associated with CT versus TT and CC genotypes versus TT genotypes were 0.99 (0.83-1.19) and 0.98 (0.78-1.21), respectively. For noncardia cancers, ORs (95% CIs) were 0.96 (0.67-1.36) for CT and 0.91 (0.71-1.16) for CC genotypes. Limiting the results to intestinal-type cancers, these ORs (95% CIs) were 1.05 (0.80-1.38) and 0.97 (0.62-1.51), respectively. For studies from Western countries, summary ORs (95% CI) were 1.13 (0.87-1.48) for CT and 1.21 (0.88-1.65) for CC genotypes. For East-Asian studies, the corresponding figures were 0.88 (0.70-1.10) and 0.82 (0.63-1.06), respectively.

Figure 2.

Forest plot for the association between IL-1B −31 CT versus TT and CC versus TT genotypes and gastric cancer risk, in order of publication year. A.IL-1B −31 CT versus TT. B.IL-1B −31 CC versus TT.

Figure 2.

Forest plot for the association between IL-1B −31 CT versus TT and CC versus TT genotypes and gastric cancer risk, in order of publication year. A.IL-1B −31 CT versus TT. B.IL-1B −31 CC versus TT.

Close modal

IL-RN

As shown in Fig. 3, ORs (95% CIs) for the association between IL-1RN L/*2 versus LL and *2/*2 versus L/L were 1.15 (0.96-1.38) and 1.23 (0.79-1.92), respectively. For noncardia cancers, the ORs (95% CIs) were 1.08 (0.69-1.70) and 1.99 (0.69-5.81), respectively. For intestinal-type cancers, these ORs (95% CIs) were 1.13 (0.63-2.01) for L/*2 and 1.53 (0.55-4.25) for *2/*2. Among studies conducted in Western countries, these ORs (95% CIs) were 1.14 (0.93-1.41) and 1.37 (0.84-2.23), respectively. For studies conducted in East-Asian countries, these ORs (95% CIs) were 1.21 (0.85-1.72) and 0.84 (0.29-2.44), respectively.

Figure 3.

Forest plot for the association between IL-1RN L/*2 versus LL and *2/*2 versus L/L genotypes and gastric cancer risk, in order of publication year. A.IL-1RN L/*2 versus LL. B.IL-1RN *2/*2 versus LL.

Figure 3.

Forest plot for the association between IL-1RN L/*2 versus LL and *2/*2 versus L/L genotypes and gastric cancer risk, in order of publication year. A.IL-1RN L/*2 versus LL. B.IL-1RN *2/*2 versus LL.

Close modal

Effect of HWE and Consistency of IL-1B −511 T and −31 C on the Results

With a cut point of P = 0.05, IL-1B −511 and −31 were in HWE among controls in 23 of the 28 (82%) and 20 of the 22 (91%) studies that reported on these polymorphisms. In these studies, the summary ORs (95% CIs) were 1.09 (0.92-1.30) for IL-1B −511 CT, 1.17 (0.97-1.42) for IL-1B −511 TT, 1.03 (0.85-1.25) for IL-1B −31 CT, and 0.98 (0.76-1.27) for IL-1B −31 CC.

In 12 of the 15 (80%) studies that reported on both IL-1B −511 and IL-1B −31, the distribution of IL-1B −511 T was consistent with that of IL-1B −31 C. In these studies, the summary ORs (95% CIs) were 1.00 (0.80-1.25) for IL-1B −511 CT, 1.07 (0.78-1.46) for IL-1B −511 TT, 0.99 (0.79-1.23) for IL-1B −31 CT, and 1.01 (0.76-1.34) for IL-1B −31 CC.

When analysis was limited to the nine studies, in which the polymorphisms were in HWE and the distribution of IL-1B −511 T was consistent with that of IL-1B −31 C, the summary ORs (95% CIs) were 1.05 (0.82-1.34) for IL-1B −511 CT, 1.16 (0.79-1.71) for IL-1B −511 TT, 1.01 (0.80-1.28) for IL-1B −31 CT, and 1.04 (0.76-1.41) for IL-1B −31 CC.

Cumulative Meta-analysis

In cumulative meta-analysis, for each polymorphic site, the associations were initially strong, but they tended toward null associations with accumulation of more data over time. As one example, the cumulative meta-analysis graph for the association between IL-1B −511 CT versus CC and TT versus CC genotypes is shown in Fig. 4.

Figure 4.

Cumulative meta-analysis graph for IL-1B −511 CT versus CC and TT versus CC genotypes and risk of gastric cancer. A.IL-1B −511 CT versus CC. B.IL-1B −511 TT versus CC. Horizontal line, the summary of all results as each study is added rather than the results of a single study.

Figure 4.

Cumulative meta-analysis graph for IL-1B −511 CT versus CC and TT versus CC genotypes and risk of gastric cancer. A.IL-1B −511 CT versus CC. B.IL-1B −511 TT versus CC. Horizontal line, the summary of all results as each study is added rather than the results of a single study.

Close modal

Sensitivity of the Results to the Choice of Model

Table 2 shows the Q-statistics and I2 statistics for the overall analyses and compares the results of random effects with fixed effects models. The Q-statistics were highly significant (≤0.001) and I2 showed a moderate to strong variation in all meta-analyses. Because of the high degree of variation, 95% CIs were narrower using the fixed effects method. However, using the fixed effects method had little effect on the ORs, except for IL1-RN *2/*2, which showed a significant association with gastric cancer (OR, 1.70; 95% CI, 1.14-2.02).

Table 2.

Comparing summary statistics using random and fixed models

Q-statistic (degrees of freedom)*PI2Random effects, OR (95% CI)Fixed effects, OR (95% CI)
IL-1B −511      
    C/C — — — Baseline Baseline 
    C/T 70.76 (27) <0.001 0.62 1.07 (0.91-1.25) 1.12 (1.02-1.23) 
    T/T 68.11 (27) <0.001 0.60 1.16 (0.95-1.42) 1.17 (1.04-1.32) 
IL-1B −31      
    T/T — — — Baseline Baseline 
    T/C 48.07 (21) 0.001 0.56 0.99 (0.83-1.19) 1.05 (0.94-1.17) 
    C/C 46.14 (21) 0.001 0.54 0.98 (0.78-1.21) 0.99 (0.87-1.14) 
IL-1RN      
    L/L — — — Baseline Baseline 
    L/*2 61.62 (25) <0.001 0.59 1.15 (0.96-1.38) 1.14 (1.03-1.27) 
    *2/*2 87.40 (25) <0.001 0.71 1.23 (0.79-1.92) 1.70 (1.14-2.02) 
Q-statistic (degrees of freedom)*PI2Random effects, OR (95% CI)Fixed effects, OR (95% CI)
IL-1B −511      
    C/C — — — Baseline Baseline 
    C/T 70.76 (27) <0.001 0.62 1.07 (0.91-1.25) 1.12 (1.02-1.23) 
    T/T 68.11 (27) <0.001 0.60 1.16 (0.95-1.42) 1.17 (1.04-1.32) 
IL-1B −31      
    T/T — — — Baseline Baseline 
    T/C 48.07 (21) 0.001 0.56 0.99 (0.83-1.19) 1.05 (0.94-1.17) 
    C/C 46.14 (21) 0.001 0.54 0.98 (0.78-1.21) 0.99 (0.87-1.14) 
IL-1RN      
    L/L — — — Baseline Baseline 
    L/*2 61.62 (25) <0.001 0.59 1.15 (0.96-1.38) 1.14 (1.03-1.27) 
    *2/*2 87.40 (25) <0.001 0.71 1.23 (0.79-1.92) 1.70 (1.14-2.02) 
*

χ2 Q-statistic for homogeneity.

P for the Q-statistic.

Higgins I2 statistic for heterogeneity.

Inflammation in the form of chronic superficial gastritis is thought to be one of the early phases in the development of intestinal-type gastric cancer (49), the predominant histologic type of gastric cancer. Therefore, a stronger inflammatory response by the host could theoretically modify gastric cancer risk. The first published epidemiologic study examining such associations found that proinflammatory polymorphisms in IL-1B and IL-1RN were strongly associated with both gastric cancer and chronic atrophic gastritis (2), a precursor of gastric cancer. Further evidence came from a subsequent study that showed >20-fold increased risk of gastric cancer associated with the presence of three or more proinflammatory polymorphisms in IL-1B, IL-1RN, IL-10, and TNF-A (3). However, as shown in this systematic review, subsequent studies found mostly null results, and cumulative meta-analysis showed a trend toward a null association.

Because this systematic review did not find a statistically significant association between proinflammatory polymorphisms in IL-1B −31, IL-1B −511, or IL-1RN with gastric cancer risk, one might argue that the initial findings were due to chance. The pattern observed with these polymorphisms is similar to associations between many other polymorphisms that have been studied in relation to cancer. Polymorphisms in other inflammation-related genes (e.g., IL-10 and TNF-A) have shown variable associations with gastric cancer (16). More broadly, there is no single polymorphism that has been consistently associated with gastric cancer (50), and recent large multicenter studies investigating the associations between promising polymorphisms with risks of other cancers have yielded null results (51). Cumulative meta-analyses of several gene-disease associations have shown that initially promising associations often gravitate toward null over time (52). Indeed, Ioannidis (53) has commented recently that journals should be cautious about publishing positive results on the associations between genetic polymorphisms and cancer.

One may alternatively argue that some of the studies that found positive associations were well designed and had large sample sizes and narrow 95% CIs, and their findings are unlikely to have been due to chance. The finding of significant heterogeneity among results in the current meta-analysis, as shown by the Q-statistics and I2, may indicate true heterogeneity and is consistent with this view. Large Q and I2 may alternatively indicate bias in the design of some of the published studies or certain forms of publication bias (54). Studies that find strong positive or inverse associations are more likely to be published and contribute to overall heterogeneity. However, for the association between IL-1B and IL-1RN polymorphisms and gastric cancer, the first published studies had valid designs and large sample sizes. Therefore, their positive findings do not seem to imply publication bias. We investigated several possible sources of heterogeneity, including tumor location, histology, geography, and genotyping error, but were not able to find a clear reason for this variation.

Results of a previous study showed that these polymorphisms were more strongly associated with cancers arising from the noncardiac region of the stomach (3). The majority of gastric cancers worldwide (especially in East-Asian countries) are noncardia cancers. Therefore, the overall results of this study, which are mostly null, are probably applicable to noncardia cancers. However, when we limited our analysis to a few studies that included only noncardia cancer cases or reported data by tumor location, the associations became stronger for IL-1B −511 CT and CC and for IL-1RN *2/*2 but not for other polymorphisms. IL-1B −511 T and IL-1B −31 C are strongly linked. The differences observed between IL-1B −511 and IL-1B −31 in this latter analysis mainly reflect interstudy variation; of 11 studies that reported on these polymorphisms and noncardia cancer, only five reported on both, and six others reported on only IL-1B −511 or IL-1B −31. Other studies have found an association only with intestinal-type, but not with-diffuse type, gastric cancer (6). Our analysis of intestinal-type cancers found an overall null association. The subgroup analyses according to anatomic subsite and histologic subtype were limited by selective availability of data from only some of the studies. Because significant subgroup results may be preferentially reported in individual studies, any significant subgroup results reported in meta-analyses need to be interpreted with caution.

An analysis of results from Western versus East-Asian studies also did not find a significant difference. Indeed, few gene-disease associations have shown heterogeneity in genetic effects (in terms of ORs) among races (55). Finally, we restricted our analysis to studies in HWE and/or with consistent distributions of IL-1B −511 T and IL-1B −31 C polymorphisms to reduce the likelihood of genotyping error. When the analysis was limited to these studies, the results remained largely unchanged.

Biological evidence for and against the above-mentioned associations are also mixed. El-Omar (56) has given a comprehensive review of the biological effects of IL-1β. On the one hand, proinflammatory polymorphisms in IL-1B and IL-1RN may reduce gastric cancer risk by mounting a stronger inflammatory reaction against H. pylori, reducing gastric injury in response to a wide variety of noxious stimuli, and increasing apoptosis of gastric epithelial cells. On the other hand, stronger inflammatory reaction may increase cancer risk by causing genomic damage to gastric cells, mucosal atrophy, and secondary hypochlorhydria and bacterial overgrowth (56).

Strengths of this meta-analysis include the large number of studies included, the large number of cases and controls examined, presentation of data on several aspects of the listed studies, and subgroup analyses according to predefined criteria. This meta-analysis also has limitations. Combining studies with various qualities of design is not always optimal, and summary ORs and 95% CIs should be interpreted with caution. Nevertheless, most of the studies included in this meta-analysis have used healthy volunteers donating blood as control subjects, and interleukin polymorphisms are unlikely to be associated with their participation. Furthermore, the patterns shown in the graphs, rather than just the summary estimates, convey valuable information.

In summary, this systematic review did not find an overall association of IL-1B −511 T, IL-1B −31 C, or IL-1RN *2 alleles with risk of gastric cancer, but there was significant heterogeneity among study results. Few studies reported data by anatomic subsite (cardia versus noncardia). Analysis of other study subgroups (intestinal versus diffuse histology), Western versus East-Asian studies, and studies that passed certain quality criteria also found no consistent association. Thus, the heterogeneity of these associations among published studies remains unexplained.

Grant support: Intramural Research Program of the NIH, National Cancer Institute.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1
Peek RM, Jr., Blaser MJ. Helicobacter pylori and gastrointestinal tract adenocarcinomas.
Nat Rev Cancer
2002
;
2
:
28
–37.
2
El Omar EM, Carrington M, Chow WH, et al. Interleukin-1 polymorphisms associated with increased risk of gastric cancer.
Nature
2000
;
404
:
398
–402.
3
El Omar EM, Rabkin CS, Gammon MD, et al. Increased risk of noncardia gastric cancer associated with proinflammatory cytokine gene polymorphisms.
Gastroenterology
2003
;
124
:
1193
–201.
4
Figueiredo C, Machado JC, Pharoah P, et al. Helicobacter pylori and interleukin 1 genotyping: an opportunity to identify high-risk individuals for gastric carcinoma.
J Natl Cancer Inst
2002
;
94
:
1680
–7.
5
Garza-Gonzalez E, Bosques-Padilla FJ, El Omar E, et al. Role of the polymorphic IL-1B, IL-1RN, and TNF-A genes in distal gastric cancer in Mexico.
Int J Cancer
2005
;
114
:
237
–41.
6
Machado JC, Pharoah P, Sousa S, et al. Interleukin 1B and interleukin 1RN polymorphisms are associated with increased risk of gastric carcinoma.
Gastroenterology
2001
;
121
:
823
–9.
7
Alpizar-Alpizar W, Perez-Perez GI, Une C, Cuenca P, Sierra R. Association of interleukin-1B and interleukin-1RN polymorphisms with gastric cancer in a high-risk population of Costa Rica.
Clin Exp Med
2005
;
5
:
169
–76.
8
Chang YW, Jang JY, Kim NH, et al. Interleukin-1B (IL-1B) polymorphisms and gastric mucosal levels of IL-1β cytokine in Korean patients with gastric cancer.
Int J Cancer
2005
;
114
:
465
–71.
9
Chen A, Li CN, Hsu PI, et al. Risks of interleukin-1 genetic polymorphisms and Helicobacter pylori infection in the development of gastric cancer.
Aliment Pharmacol Ther
2004
;
20
:
203
–11.
10
Garza-Gonzalez E, Hold G, Perez-Perez GI, et al. [Role of polymorphism of certain cytokines in gastric cancer in Mexico. Preliminary results].
Rev Gastroenterol Mex
2003
;
68
:
107
–12.
11
Gatti LL, Burbano RR, de Assumpcao PP, Smith MA, Payao SL. Interleukin-1β polymorphisms, Helicobacter pylori infection in individuals from Northern Brazil with gastric adenocarcinoma.
Clin Exp Med
2004
;
4
:
93
–8.
12
Glas J, Torok HP, Schneider A, et al. Allele 2 of the interleukin-1 receptor antagonist gene is associated with early gastric cancer.
J Clin Oncol
2004
;
22
:
4746
–52.
13
Hartland S, Newton JL, Griffin SM, Donaldson PT. A functional polymorphism in the interleukin-1 receptor-1 gene is associated with increased risk of Helicobacter pylori infection but not with gastric cancer.
Dig Dis Sci
2004
;
49
:
1545
–50.
14
He X, Jiang L, Fu B, Zhang X. [Relationship between interleukin-1B and interleukin-1 receptor antagonist gene polymorphisms and susceptibility to gastric cancer].
Zhonghua Yi Xue Za Zhi
2002
;
82
:
685
–8.
15
Hu S, Song QB, Yu D, Ke YH, Hu PJ, Zeng ZR. [Association of interleukin-1 gene polymorphism with gastric cancer in a high-risk area of China].
Di Yi Jun Yi Da Xue Xue Bao
2004
;
24
:
1171
–3.
16
Kamangar F, Abnet CC, Hutchinson AA, et al. Polymorphisms in inflammation-related genes and risk of gastric cancer (Finland).
Cancer Causes Control
2006
;
17
:
117
–25.
17
Kang WK, Park WS, Chin HM, Park CH. [The role of interleukin-1β gene polymorphism in the gastric carcinogenesis].
Korean J Gastroenterol
2004
;
44
:
25
–33.
18
Kato S, Onda M, Yamada S, Matsuda N, Tokunaga A, Matsukura N. Association of the interleukin-1β genetic polymorphism and gastric cancer risk in Japanese.
J Gastroenterol
2001
;
36
:
696
–9.
19
Lee KA, Ki CS, Kim HJ, et al. Novel interleukin 1β polymorphism increased the risk of gastric cancer in a Korean population.
J Gastroenterol
2004
;
39
:
429
–33.
20
Lee SG, Kim B, Choi W, Lee I, Choi J, Song K. Lack of association between pro-inflammatory genotypes of the interleukin-1 (IL-1B -31 C/+ and IL-1RN *2/*2) and gastric cancer/duodenal ulcer in Korean population.
Cytokine
2003
;
21
:
167
–71.
21
Lu W, Pan K, Zhang L, Lin D, Miao X, You W. Genetic polymorphisms of interleukin (IL)-1B, IL-1RN, IL-8, IL-10, and tumor necrosis factor α and risk of gastric cancer in a Chinese population.
Carcinogenesis
2005
;
26
:
631
–6.
22
Machado JC, Figueiredo C, Canedo P, et al. A proinflammatory genetic profile increases the risk for chronic atrophic gastritis and gastric carcinoma.
Gastroenterology
2003
;
125
:
364
–71.
23
Muramatsu A, Azuma T, Okuda T, et al. Association between interleukin-1-511C/T polymorphism and reflux esophagitis in Japan.
J Gastroenterol
2005
;
40
:
873
–7.
24
Palli D, Saieva C, Luzzi I, et al. Interleukin-1 gene polymorphisms and gastric cancer risk in a high-risk Italian population.
Am J Gastroenterol
2005
;
100
:
1941
–8.
25
Perri F, Piepoli A, Bonvinci C, et al. Cytokine gene polymorphisms in gastric cancer patients from two Italian areas at high and low cancer prevalence.
Cytokine
2005
;
30
:
293
–302.
26
Rocha GA, Guerra JB, Rocha AM, et al. IL1RN polymorphic gene and cagA-positive status independently increase the risk of noncardia gastric carcinoma.
Int J Cancer
2005
;
115
:
678
–83.
27
Ruzzo A, Graziano F, Pizzagalli F, et al. Interleukin 1B gene (IL-1B) and interleukin 1 receptor antagonist gene (IL-1RN) polymorphisms in Helicobacter pylori-negative gastric cancer of intestinal and diffuse histotype.
Ann Oncol
2005
;
16
:
887
–92.
28
Sakuma K, Uozaki H, Chong JM, et al. Cancer risk to the gastric corpus in Japanese, its correlation with interleukin-1β gene polymorphism (+3953*T) and Epstein-Barr virus infection.
Int J Cancer
2005
;
115
:
93
–7.
29
Sicinschi LA, Lopez-Carrillo L, Camargo MC, et al. Gastric cancer risk in a Mexican population: role of Helicobacter pylori CagA positive infection and polymorphisms in interleukin-1 and -10 genes.
Int J Cancer
2006
;
118
:
649
–57.
30
Sui GP, Pan KF, Zhou T, Zhang L, Li JF, Xu GW. [Correlation between polymorphisms of interleukin-1β and RN genes and risk of gastric carcinoma: a case-control study].
Zhonghua Yi Xue Za Zhi
2003
;
83
:
1479
–83.
31
Taguchi A, Ohmiya N, Shirai K, et al. Interleukin-8 promoter polymorphism increases the risk of atrophic gastritis and gastric cancer in Japan.
Cancer Epidemiol Biomarkers Prev
2005
;
14
:
2487
–93.
32
Tatemichi M, Sawa T, Gilibert I, Tazawa H, Katoh T, Ohshima H. Increased risk of intestinal type of gastric adenocarcinoma in Japanese women associated with long forms of CCTTT pentanucleotide repeat in the inducible nitric oxide synthase promoter.
Cancer Lett
2005
;
217
:
197
–202.
33
Vilaichone RK, Mahachai V, Tumwasorn S, Wu JY, Graham DY, Yamaoka Y. Gastric mucosal cytokine levels in relation to host interleukin-1 polymorphisms and Helicobacter pylori cagA genotype.
Scand J Gastroenterol
2005
;
40
:
530
–9.
34
Wu MS, Wu CY, Chen CJ, Lin MT, Shun CT, Lin JT. Interleukin-10 genotypes associate with the risk of gastric carcinoma in Taiwanese Chinese.
Int J Cancer
2003
;
104
:
617
–23.
35
Wu MS, Chen LT, Shun CT, et al. Promoter polymorphisms of tumor necrosis factor-α are associated with risk of gastric mucosa-associated lymphoid tissue lymphoma.
Int J Cancer
2004
;
110
:
695
–700.
36
Yang J, Hu Z, Xu Y, et al. Interleukin-1B gene promoter variants are associated with an increased risk of gastric cancer in a Chinese population.
Cancer Lett
2004
;
215
:
191
–8.
37
Zambon CF, Basso D, Navaglia F, et al. Helicobacter pylori virulence genes and host IL-1RN and IL-1β genes interplay in favouring the development of peptic ulcer and intestinal metaplasia.
Cytokine
2002
;
18
:
242
–51.
38
Zambon CF, Basso D, Navaglia F, et al. Increased risk of noncardia gastric cancer associated with proinflammatory cytokine gene polymorphisms.
Gastroenterology
2004
;
126
:
382
–4.
39
Zeng ZR, Hu PJ, Hu S, et al. Association of interleukin 1B gene polymorphism and gastric cancers in high and low prevalence regions in China.
Gut
2003
;
52
:
1684
–9.
40
Zhang WH, Wang XL, Zhou J, An LZ, Xie XD. Association of interleukin-1B (IL-1B) gene polymorphisms with risk of gastric cancer in Chinese population.
Cytokine
2005
;
30
:
378
–81.
41
zur Hausen A, Crusius JB, Murillo LS, et al. IL-1B promoter polymorphism and Epstein-Barr virus in Dutch patients with gastric carcinoma.
Int J Cancer
2003
;
107
:
866
–7.
42
Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses.
BMJ
2003
;
327
:
557
–60.
43
DerSimonian R, Laird N. Meta-analysis in clinical trials.
Control Clin Trials
1986
;
7
:
177
–88.
44
Thompson SG, Pocock SJ. Can meta-analyses be trusted?
Lancet
1991
;
338
:
1127
–30.
45
Moayyedi P. Meta-analysis: can we mix apples and oranges?
Am J Gastroenterol
2004
;
99
:
2297
–301.
46
Hamajima N, Matsuo K, Saito T, et al. Interleukin 1 polymorphisms, lifestyle factors, and Helicobacter pylori infection.
Jpn J Cancer Res
2001
;
92
:
383
–9.
47
El Omar EM, Carrington M, Chow WH, et al. The role of interleukin-1 polymorphisms in the pathogenesis of gastric cancer.
Nature
2001
;
412
:
99
.
48
Trikalinos TA, Salanti G, Khoury MJ, Ioannidis JP. Impact of violations and deviations in Hardy-Weinberg equilibrium on postulated gene-disease associations.
Am J Epidemiol
2006
;
163
:
300
–9.
49
Correa P. Human gastric carcinogenesis: a multistep and multifactorial process—First American Cancer Society Award Lecture on Cancer Epidemiology and Prevention.
Cancer Res
1992
;
52
:
6735
–40.
50
Gonzalez CA, Sala N, Capella G. Genetic susceptibility and gastric cancer risk.
Int J Cancer
2002
;
100
:
249
–60.
51
Kraft P, Pharoah P, Chanock SJ, et al. Genetic variation in the HSD17B1 gene and risk of prostate cancer.
PLoS Genet
2005
;
1
:
e68
.
52
Ioannidis JP, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG. Replication validity of genetic association studies.
Nat Genet
2001
;
29
:
306
–9.
53
Ioannidis JP. Journals should publish all “null” results and should sparingly publish “positive” results.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
186
.
54
Pan Z, Trikalinos TA, Kavvoura FK, Lau J, Ioannidis JP. Local literature bias in genetic epidemiology: an empirical evaluation of the Chinese literature.
PLoS Med
2005
;
2
:
e334
.
55
Ioannidis JP, Ntzani EE, Trikalinos TA. Racial differences in genetic effects for complex diseases.
Nat Genet
2004
;
36
:
1312
–8.
56
El Omar EM. The importance of interleukin 1β in Helicobacter pylori associated disease.
Gut
2001
;
48
:
743
–7.