IL-4 −590C/T Polymorphism and Susceptibility to Liver Disease: A Meta-Analysis and Meta-Regression

Abstract

Interleukin-4 (IL-4) is a pleiotropic cytokine that plays an important role in the immune system. Emerging evidences have shown that the common polymorphism (−590C/T; rs2243250 C>T) in the IL-4 gene may play an important role in the development of various liver diseases, but individually published studies revealed inconclusive results. This meta-analysis aims to derive a more precise estimation of the association between the IL-4 −590C/T polymorphism and susceptibility to liver disease. A literature search of PubMed, Embase, Web of Science and China BioMedicine databases was conducted on articles published before January 1st, 2013. Crude odds ratio with 95% confidence intervals were calculated to assess the strength of this association. Ten case–control studies were assessed with a total 1,140 patients and 1,649 healthy controls. The meta-analysis results indicated that the IL-4 −590T polymorphism might increase the risks of hepatitis B (HBV) and hepatitis C (HCV) infections. Further subgroup analyses showed significant associations between the IL-4 −590T polymorphism and increased risks of liver diseases among Caucasian populations, but similar associations were not found among Asian populations. Univariate and multivariate meta-regression analyses showed that differences in ethnicity and clinical subtype are the major sources of heterogeneity. No publication bias was detected in this meta-analysis. In conclusion, the current meta-analysis indicates that the IL-4 −590T polymorphism may play an important role in increasing HBV and HCV infection risks, especially among Caucasian populations.

Introduction

I nterleukin-4 (IL-4) is a multifunctional pleiotropic cytokine produced mainly by activated Th2 cells, which plays important roles in humoral and cell-mediated immunity (Luzina et al., 2012). IL-4 is involved in the regulation of the immune response of B cells, T cells, and macrophages to fight against infections and malignant cells (Landi et al., 2007). Genetic alterations may influence the expression and function of IL-4, which can lead to a weakened cell-mediated immune response, thereby increasing one's susceptibility to infections and liver diseases, including hepatitis B virus (HBV) and hepatitis C virus (HCV) infections (Warncke et al., 2011). The IL-4 gene is located on chromosome 5q31 and consists of ∼25 kbps (Shalaby et al., 2012). Multiple polymorphic sites within the IL-4 gene have been reported, including −590C/T (rs2243250 C>T), −33C/T (rs2070874 C>T), +3437C/G (rs2227282 C>G), 2979G/T (rs2227284 A>C), and −1098T/G (rs2243248 G>T) (Naslednikova et al., 2007). Genetic mutations in the IL-4 gene may alter its expression and its downstream signaling, which may contribute to an individual's susceptibility to immune-related liver disease (Jiang et al., 2000). Therefore, it was hypothesized that polymorphisms in the IL-4 gene could be functional and be associated with the development of various liver diseases (Donaldson, 2004).

Several studies have indicated that the common promoter polymorphism (−590C/T) in the IL-4 gene might play a critical role in increasing an individual's susceptibility to HBV and HCV infection (Aithal et al., 2004; Zhu et al., 2005; Wang et al., 2006; Gao et al., 2012). However, some previous studies also suggested that the IL-4 polymorphisms were not associated with susceptibility to HBV, HCV, drug-induced liver injury, or hepatocellular carcinoma (Chen et al., 2007; Liu et al., 2007; Naslednikova et al., 2007; Pachkoria et al., 2008; Gao et al., 2009; Ognjanovic et al., 2009). In view of the conflicting results from previous studies, we performed a meta-analysis of all the available data to evaluate the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver diseases.

Materials and Methods

Literature search strategy

Relevant articles published before January 1st, 2013 were identified through a search in Pubmed, Embase, Web of Science and China BioMedicine databases using the following terms: (“genetic polymorphism” or “polymorphism” or “SNP” or “single-nucleotide polymorphism” or “gene mutation” or “genetic variants”) and (“liver diseases” or “hepatitis” or “liver cirrhosis” or “liver injury” or “hepatocellular carcinoma” or “fatty liver” or “hepatocellular carcinoma” or “hepatocellular carcinoma”) and (“interleukin-4” or “B-cell growth factor-1” or “IL4” or “IL-4”). The references from the eligible articles or textbooks were also reviewed to find potential sources of studies. Disagreements were resolved through discussions between the authors.

Inclusion and exclusion criteria

Studies included in our meta-analysis have to meet the following criteria: (1) case–control studies focused on the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver diseases; (2) all patients diagnosed with various liver diseases should have serological or histopathological confirmations or evidences; (3) published data about the frequencies of alleles or genotypes must be sufficient. Studies were excluded when they were (1) not a case–control study on the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver diseases; (2) duplicates of previous publications; (3) publications with incomplete data; (4) meta-analyses, letters, reviews, or editorial articles. If more than one study by the same author using the same case series were published, either the study with the largest sample size or the most publication date was included.

Data extraction

Data from the published studies were extracted independently by two authors into a standardized form. For each study, the following characteristics and numbers were collected: the first author, year of publication, country, language, study design, ethnicity of subjects, numbers of subjects, gender ratio, mean age, detecting sample, genotype method, allele and genotype frequencies of SNP, and evidence of Hardy–Weinberg equilibrium (HWE). In cases of conflicting evaluations, disagreements were resolved through discussions between the authors.

Quality assessment of included studies

Two authors independently assessed the quality of the included studies according to the modified STROBE quality score systems (da Costa et al., 2011). Forty assessment items related to quality appraisal were used in this meta-analysis with scores ranging from 0 to 40. Scores of 0–20, 20–30, and 30–40 were defined as low, moderate, and high quality, respectively. Disagreements were also resolved through discussions between the authors.

Statistical analysis

Crude odds ratios (ORs) with 95% confidence intervals (CIs) were calculated under five genetic models: the allele model (T allele versus C allele), the dominant model (TT+CT versus CC), the recessive model (TT versus CT+CC), the homozygous model (TT versus CC), and the heterozygous model (TT versus CT). The statistical significance of the pooled ORs was examined using the Z test. Between-study variations and heterogeneities were estimated using Cochran's Q-statistic with a p-value<0.05 as statistically significant heterogeneity (Jackson et al., 2012). We also quantified the effects of heterogeneity using the I² test (ranges from 0% to 100%), which represents the proportion of interstudy variability that can be contributed to heterogeneity rather than to chance (Peters et al., 2006). When a significant Q-test, with p<0.05 or I² >50% indicated that heterogeneity among the studies existed, the random-effects model (the DerSimonian Laird method) was conducted for the meta-analysis; otherwise, the fixed-effects model (the Mantel-Haenszel method) was used. To explore sources of heterogeneity, univariate and multivariate meta-regression analyses were used. Subgroup analyses were performed based on the clinical subtype, ethnicity, and genotype method. Sensitivity analysis was performed through omitting each study in turn to assess the quality and consistency of the results. Funnel plots were used to detect publication bias. The Egger's linear regression test was also used to evaluate the publication bias (Zintzaras and Ioannidis, 2005). We tested whether genotype frequencies were in HWE using the χ² test. All the p values were two-sided. All analyses were calculated using the STATA Version 12.0 software (Stata Corp, College Station, TX).

Results

Characteristics of included studies

In accordance with the inclusion criteria, 10 case–control studies (Aithal et al., 2004; Zhu et al., 2005; Wang et al., 2006; Chen et al., 2007; Liu et al., 2007; Naslednikova et al., 2007; Pachkoria et al., 2008; Gao et al., 2009; Ognjanovic et al., 2009; Gao et al., 2012) were included in this meta-analysis and 148 were excluded. The flow chart of the study selection process is shown in Figure 1. A total of 2,789 subjects were involved in this meta-analysis, including 453 patients with HBV infection, 183 patients with HCV infection, 96 patients with HBV-HCV coinfection, 124 patients with liver cirrhosis, 164 patients with drug-induced liver injury, 120 patients with hepatocellular carcinoma, and 1,649 healthy controls. The publication years of the involved studies ranged from 2004 to 2012. Six of the 10 studies were conducted in Asian populations and the other four studies in Caucasian populations. All included studies used blood samples for genotyping. A classical polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) method was performed in seven studies and the TaqMan assay used in the other three studies. The HWE test was conducted on the genotype distribution of the controls in all 10 studies. None of the studies deviated from the HWE (all p>0.05). All quality scores of the included studies were higher than 20, indicating moderate high quality. The characteristics and methodological quality of the included studies are summarized in Table 1.

FIG. 1.

Flowchart of literature search and study selection process.

Table 1.

Characteristics and Methodological Quality of the Included Studies in This Meta-Analysis

					Number		Gender (M/F)		Age (years)
First author	Year	Country	Ethnicity	Clinical subtype	Case	Control	Case	Control	Case	Control	Genotype method	HWE test (p-value)	STROBE score
Gao et al.	2012	China	Asian	HBV	69	74	39/30	34/40	52.7±13.2	48.6±9.4	PCR-RFLP	0.693	33/40
				HCV	55		28/27		49.4±10.0
				HBV-HCV	79		36/43		48.6±9.4
Ognjanovic et al.	2009	USA	Caucasian	HCC	120	230	82/38	139/91	60.5±10.3	59.5±10.7	TaqMan assay	NR	35/40
Gao et al.	2009	China	Asian	Liver cirrhosis	24	74	NR	34/40	NR	48.6±9.4	PCR-RFLP	0.693	33/40
Pachkoria et al.	2008	Spain	Caucasian	Drug-induced liver injury	140	268	70/70	–	51 (13–82)	NR	TaqMan assay	0.546	28/40
Liu et al.	2007	China	Asian	Liver cirrhosis	100	124	82/18	101/23	57 (36–81)	NR	PCR-RFLP	0.500	26/40
Chen et al.	2007	Taiwan	Asian	HCV	72	180	46/26	72/108	54.0±1.9	54.3±2.7	PCR-RFLP	0.953	32/40
Naslednikova et al.	2007	Russia	Caucasian	HBV	25	48	89/69	NR	31.0±3.0	NR	PCR-RFLP	0.767	29/40
				HCV	56
				HBV-HCV	17
Wang et al.	2006	China	Asian	HBV	313	203	209/104	121/82	38.3±6.0	38.1±6.1	PCR-RFLP	0.552	31/40
Zhu et al.	2005	China	Asian	HBV	46	127	26/20	73/54	NR	NR	TaqMan assay	0.240	27/40
Aithal et al.	2004	UK	Caucasian	Drug-induced liver injury	24	321	19/5	NR	51 (24–70)	NR	PCR-RFLP	0.073	25/40

HBV, hepatitis B; HCV, hepatitis C; HCC, hepatocellular carcinoma; M, male; F, female; PCR-RFLP, polymerase chain reaction–restriction fragment length polymorphism; HWE, Hardy–Weinberg equilibrium; NR, not reported.

Quantitative data synthesis

A summary of the meta-analysis findings of the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver disease is provided in Table 2. The heterogeneity is not obvious under all five genetic models (all p>0.05 and I² <50%), so the fixed-effects model was used. The meta-analysis results showed that the IL-4 −590T polymorphism may be associated with increased susceptibility to liver disease (T allele versus C allele: OR=1.20, 95%CI=1.01–1.41, p=0.035; TT+CT versus CC: OR=1.53, 95%CI=1.22–1.92, p<0.001). Further subgroup analysis by a clinical subtype showed significant associations between the IL-4 −590T polymorphism and increased risks of HBV and HCV infection under the dominant model (HBV: OR=1.54, 95%CI=1.07–2.21, p=0.019; HCV: OR=3.32, 95%CI=1.60–6.86, p=0.001) (Fig. 2). Results from subgroup analysis based on ethnicity indicated that the IL-4 −590T polymorphism may increase the risk of liver disease among Caucasian populations (T allele versus C allele: OR=1.54, 95%CI=1.09–2.18, p=0.015; TT+CT versus CC: OR=1.55, 95%CI=1.15–2.10, p=0.004), but similar associations were not found among Asian populations (Fig. 3). In the subgroup analysis by the genotype method, we also found significant associations between the IL-4 −590T polymorphism and increased risks of liver disease in the PCR-RFLP subgroup; however, we did not find similar associations in the TaqMan subgroup.

FIG. 2.

Forest plot for the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver disease under the dominant model.

FIG. 3.

Subgroup analysis by ethnicity for the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver disease under the allele model.

Table 2.

Meta-Analysis of the Association Between IL-4 −590C/T Polymorphism and Susceptibility to Liver Disease

	Allele model (T allele versus C allele)				Dominant model (CT+TT versus CC)				Recessive model (TT versus CC+CT)				Homozygous model (TT versus CC)				Heterozygous model (TT versus CT)
Subgroups	OR	95%CI	p	p_h	OR	95%CI	p	p_h	OR	95%CI	p	p_h	OR	95%CI	p	p_h	OR	95%CI	p	p_h
Clinical subtype
HBV	1.28	(0.99, 1.64)	0.056	0.963	1.54	(1.07, 2.21)	0.019	0.687	1.09	(0.74, 1.62)	0.666	0.857	1.47	(0.85, 2.54)	0.168	0.639	0.88	(0.57, 1.36)	0.556	0.856
HCV	1.10	(0.80, 1.51)	0.578†	0.010	3.32	(1.60, 6.86)	0.001	0.791	0.73	(0.47, 1.12)	0.148	0.376	2.34	(0.70, 7.79)	0.166	0.809	0.65	(0.42, 1.01)	0.055	0.556
HBV-HCV	1.11	(0.71, 1.74)	0.639	0.672	1.52	(0.60, 3.83)	0.379	0.365	1.02	(0.56, 1.87)	0.952	0.272	2.68	(0.71, 10.09)	0.144	0.927	0.93	(0.50, 1.74)	0.824	0.232
Liver cirrhosis	1.13	(0.79, 1.63)	0.509	0.778	1.44	(0.60, 3.46)	0.410	0.460	1.08	(0.68, 1.71)	0.739	0.464	1.48	(0.60, 3.66)	0.393	0.561	1.01	(0.63, 1.64)	0.954	0.345
Drug-induced liver injury	1.39	(0.90, 2.13)	0.137	0.266	1.58	(0.97, 2.57)	0.067	0.205	0.92	(0.23, 3.59)	0.901	0.853	1.03	(0.26, 4.08)	0.967	0.787	0.63	(0.16, 2.50)	0.508	0.854
Ethnicity
Caucasian	1.54	(1.09, 2.18)	0.015	0.413	1.55	(1.15, 2.10)	0.004	0.268	0.97	(0.34, 2.76)	0.948	0.948	1.30	(0.45, 3.75)	0.623	0.850	0.66	(0.22, 1.94)	0.447	0.978
Asian	1.11	(0.92, 1.34)	0.288	0.346	1.51	(0.97, 2.13)	0.059	0.795	1.05	(0.82, 1.36)	0.699	0.403	1.54	(0.97, 2.42)	0.065	0.867	0.84	(0.64, 1.10)	0.193	0.536
Genotype method
PCR-RFLP	1.18	(0.99, 1.42)	0.070	0.115	1.72	(1.27, 2.33)	<0.001	0.573	1.07	(0.82, 1.39)	0.626	0.554	1.54	(0.97, 2.44)	0.068	0.930	0.81	(0.62, 1.08)	0.149	0.667
TaqMan assay	1.25	(0.84, 1.85)	0.269	0.903	1.32	(0.94, 1.86)	0.113	0.915	0.91	(0.45, 1.84)	0.787	0.719	1.34	(0.50, 3.58)	0.558	0.572	0.90	(0.41, 1.99)	0.799	0.689
Overall	1.20	(1.01, 1.41)	0.035	0.243	1.53	(1.22, 1.92)	<0.001	0.705	1.05	(0.82, 1.33)	0.718	0.732	1.50	(0.99, 2.28)	0.058	0.97	0.82	(0.63, 1.07)	0.148	0.830

OR, odds ratios; p_h _, p value of heterogeneity test; †, estimates for random-effects model.

Meta-regression and sensitivity analyses

Univariate and multivariate meta-regression analyses were used to explore possible sources of heterogeneity among the studies. The results showed that differences in ethnicity and clinical subtype may be the major sources of heterogeneity (p<0.05) (as shown in Table 3). Sensitivity analysis was performed to assess the influence of each individual study on the pooled ORs by omitting individual studies. The analysis results suggested that no individual studies significantly affected the pooled OR of the association between the IL-4 −590C/T polymorphism and susceptibility to liver disease under the dominant model (Fig. 4).

FIG. 4.

Sensitivity analysis of the summary OR of the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver disease under the dominant model. Results were computed by omitting each study in turn. Meta-analysis random-effects estimates (exponential form) were used. The two ends of the dotted lines represent the 95%CI.

Table 3.

Univariate and Multivariate Meta-Regression Analyses of Potential Source of Heterogeneity

					95%CI
Heterogeneity factors	Coefficient	SE	z	p	UL	LL
Publication year
Univariate	−0.02	0.07	−0.32	0.753	−0.16	0.12
Multivariate	0.12	0.11	1.12	0.262	−0.09	0.334
Country
Univariate	0.11	0.07	1.47	0.142	−0.04	0.25
Multivariate	0.29	0.26	1.15	0.251	−0.21	0.79
Ethnicity
Univariate	0.34	0.23	0.18	0.032	0.12	0.50
Multivariate	0.63	0.95	−0.66	0.016	0.38	1.23
Clinical subtype
Univariate	0.07	0.09	−0.18	0.047	0.02	0.17
Multivariate	0.19	0.15	−0.45	0.043	0.16	0.22
Genotype method
Univariate	−0.28	0.23	−1.18	0.237	−0.73	0.18
Multivariate	−0.04	0.63	−0.06	0.952	−1.27	1.19
STROBE score
Univariate	−0.03	0.04	−0.85	0.397	−0.10	0.04
Multivariate	−0.01	0.07	−0.09	0.931	−0.14	0.13

SE, standard error; 95%CI, 95% confidence interval; UL, upper limit; LL, lower limit.

Publication bias

The funnel plot and Egger's linear regression test were performed to assess publication bias in the included studies. The shapes of the funnel plots of the association between IL-4 −590C/T polymorphism and susceptibility to liver disease did not reveal any evidence of obvious asymmetry (Fig. 5). The Egger's test also did not indicate any strong statistical evidence of publication bias under the dominant model (t=0.57, p=0.587).

FIG. 5.

Funnel plot of the associations between the IL-4 −590C/T promoter polymorphism and susceptibility to liver disease under the dominant model. Each point represents a separate study for the indicated association. Log[OR], natural logarithm of OR. Horizontal line, mean magnitude of the effect.

Discussion

IL-4 is an immunomodulatory cytokine secreted by activated Th2 lymphocytes, basophils, and mast cells (Hou et al., 1994). It plays a critical role in the modulation of effector B and T cells and has been implicated in susceptibility to several human immune-related diseases (Dejaco et al., 2006; Huang et al., 2006). Thus, genetic mutations in the IL-4 gene may contribute to its abnormal expression and are probably linked to liver disease risks (Bataller et al., 2003). Many previous studies have suggested that the most common polymorphism (−590C/T) in the promoter region of the IL-4 gene may play an important role in the risk of liver disease (Aithal et al., 2004; Zhu et al., 2005; Wang et al., 2006; Gao et al., 2012), while other studies found no convincing evidence of these polymorphisms in increasing liver disease risks (Chen et al., 2007; Liu et al., 2007; Naslednikova et al., 2007; Pachkoria et al., 2008; Gao et al., 2009). This controversy could be explained with several reasons, such as the differences in study designs, sample size, ethnicity of the subjects, source of the subjects, and genotype methods (Rosenthal and DiMatteo, 2001; Chung et al., 2006). Therefore, we performed a meta-analysis to provide a comprehensive and reliable conclusion on the association between the IL-4 −590C/T promoter polymorphism and susceptibility to liver disease.

In this meta-analysis, 10 case–control studies were included with a total of 1,140 liver disease patients and 1,649 healthy controls. When all the eligible studies were pooled into the meta-analysis, the results indicated that the IL-4 −590T polymorphism may increase the risks of HBV and HCV infections, especially among Caucasian populations, while similar associations were not observed among Asian populations. Although the exact functions of the IL-4 genetic polymorphisms in HBV or HCV infections are not yet clear, a possible explanation could be that inherited mutations in IL-4 might be associated with the changes in expression and function of cytokines and thereby could possibly explain interindividual differences in susceptibility to HBV or HCV (Ganem and Prince, 2004; Nieters et al., 2005). These findings are consistent with the previous hypothesis that variability in the IL-4 gene may increase risks of HBV and HCV infections, suggesting that they may be useful as biomarkers in predicting an individual's susceptibility to HBV and HCV infections (Jiang et al., 2000; Donaldson, 2004).

Some limitations of this meta-analysis should be acknowledged. First, there were only 10 articles included in the present meta-analysis, so the sample size was relatively small and may not provide sufficient statistical power. Therefore, more studies with a larger sample size are still needed to accurately provide a more representative statistical analysis. Second, as a type of a retrospective study, a meta-analysis may encounter recall or selection bias, which could possibly influence the reliability of our study results (Ioannidis and Lau, 1999, Juni and Egger, 2009). Third, our lack of access to the original data from the studies limited further evaluations of potential interactions between other factors and liver disease risks, such as gene–environment and gene–gene interactions (Dennis et al., 2011). In spite of these limitations, however, this is the first meta-analysis of the relationship between the IL-4 −590C/T promoter polymorphism and susceptibility to liver disease.

In conclusion, our meta-analysis suggests that the IL-4 −590T polymorphism may play an important role in increasing HBV and HCV infection risks, especially among Caucasian populations. These relationships have the potential to provide a functional profiling of the IL-4 gene involved in humoral and cell-mediated immunity, and it may also help us understand the biological processes associated with the development of liver diseases, especially for HBV and HCV infections. However, detailed studies are still needed to confirm our findings. Further studies investigating the effects of gene–environment and gene–gene interactions on susceptibility to liver diseases are also essential.

Footnotes

Acknowledgments

This study is funded by the Science Foundation of Science and Technology Bureau of Liaoning Province of China (No. 2008225008-8).

Author Disclosure Statement

No competing financial interests exist.

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