Meta-Analysis
Copyright ©The Author(s) 2015.
World J Gastroenterol. Jul 28, 2015; 21(28): 8711-8722
Published online Jul 28, 2015. doi: 10.3748/wjg.v21.i28.8711
Table 1 Main characteristics and methodological quality of all eligible studies of the relationship between interleukin-18 genetic polymorphisms and the risk of developing Crohn’s disease
Ref.YearCountryEthnicityNumber
Gender (M/F)
Age (yr)
Genotyping methodSNP typeHWE test (Pvalue)NOS score
CDControlCDControlCDControl
Ben Aleya et al[21]2011TunisiaAfrican10510050/5552/4823-60-PCR-SSPrs1946518 A>C0.0516
rs187238 G>C0.284
Dema et al[27]2009SpainCaucasian722794274/448---TaqManrs917997 C>T0.6095
Haas et al[29]2005GermanyCaucasian470347139/331122/225--TaqManrs187238 G>C0.6376
Glas et al[28]2005GermanyCaucasian21026583/127141/12439.1 ± 13.643.2 ± 12.5PCR-RFLPrs1946518 A>C0.5928
rs187238 G>C0.123
codon 35 A>C0.774
Tamura et al[31]2008JapanAsian134110102/3255/5515-6515-75Direct sequencingcodon 35 A>C0.6068
Takagawa et al[30]2005JapanAsian210212150/6097/11532.4 ± 9.838.2 ± 13.7PCR-SSPrs1946518 A>C0.2988
rs187238 G>C0.197
Aizawa et al[26]2005JapanAsian7910261/1850/5236.8 ± 9.237.6 ± 6.9Direct sequencingrs1946519 G>T0.9478
rs1946518 A>C0.840
rs187238 G>C0.586
rs360718 A> C0.327
Table 2 Meta-analysis of subgroups for the relationships between IL-18 genetic polymorphisms and Crohn’s disease risk
W allele vs M allele (Allele model)
WW + WM vs MM (Dominant model)
WW vs WM + MM (Recessive model)
WW vs MM (Homozygous model)
WW vs WM (Heterozygous model)
OR95%CIPvalueOR95%CIPvalueOR95%CIPvalueOR95%CIPvalueOR95%CIPvalue
SNP type
rs1946518 A>C1.451.22-1.720.0001.621.22-2.140.0011.591.26-2.010.0001.981.45-2.720.0001.431.12-1.840.005
rs187238 G>C1.691.39-2.060.0002.041.48-2.810.0001.811.42-2.310.0002.531.82-3.520.0001.661.29-2.130.000
rs360718 A>C2.031.20-3.430.0082.330.46-11.880.3082.391.29-4.430.0063.170.61-16.400.1692.311.22-4.380.010
rs917997 C>T0.910.77-1.060.2290.800.55-1.180.2670.910.74-1.110.3490.780.52-1.160.2200.930.76-1.150.525
codon 35 A>C1.150.91-1.450.2561.300.75-2.260.3551.150.85-1.550.3601.410.79-2.520.2501.110.81-1.520.523
rs1946519 G>T1.140.74-1.770.5451.240.51-3.030.6411.170.64-2.130.6041.320.51-3.430.5661.130.60-2.130.697
Ethnicity
Asians1.541.28-1.850.0001.811.29-2.530.0011.651.28-2.120.0002.251.56-3.240.0001.541.18-2.000.001
Africans1.991.42-2.790.0002.691.55-4.670.0002.111.38-3.220.0013.551.67-7.530.0011.661.07-2.590.025
Caucasians1.230.97-1.540.0831.270.92-1.770.1481.290.97-1.730.0791.440.94-2.220.0961.250.97-1.610.086
Genotyping method
PCR-SSP1.671.35-2.070.0001.911.37-2.670.0001.841.45-2.340.0002.351.55-3.560.0001.671.30-2.150.000
TaqMan1.200.69-2.100.5211.170.55-2.530.6811.290.64-2.580.4791.320.46-3.800.6031.270.68-2.360.450
PCR-RFLP1.251.07-1.460.0051.361.00-1.850.0531.311.06-1.630.0131.551.11-2.160.0111.250.99-1.560.059
Direct sequencing1.561.16-2.110.0032.461.37-4.430.0031.611.08-2.420.0213.211.72-5.990.0001.460.98-2.180.061
Sample size
Small sample-size (n ≤ 200)1.611.29-2.010.0002.291.60-3.270.0001.661.25-2.200.0012.851.93-4.200.0001.461.12-1.900.005
Large sample-size (n > 200)1.331.08-1.630.0071.331.02-1.740.0381.441.11-1.860.0071.541.07-2.210.0191.381.08-1.760.009
Table 3 Univariate and multivariate meta-regression analyses of potential sources of heterogeneity
Heterogeneity factorsCoefficientSEZPvalue95%CI
LLUL
Publication year
Univariate0.0040.0360.120.908-0.0660.075
Multivariate-0.0520.038-1.390.166-0.1260.022
SNP type
Univariate-0.1880.084-2.250.025-0.353-0.024
Multivariate-0.0770.091-0.840.398-0.2560.102
Ethnicity
Univariate0.2410.0952.550.0110.0560.427
Multivariate0.4760.2501.900.057-0.0140.967
Genotyping method
Univariate-0.0820.066-1.250.211-0.2110.047
Multivariate0.0750.0820.920.360-0.0850.235
Sample size
Univariate0.1940.1481.310.190-0.0960.485
Multivariate-0.2160.244-0.890.376-0.6960.263