Persistent Effect of IFNAR-1 Genetic Polymorphism on the Long-Term Pathogenesis of Chronic HBV Infection

Abstract

Genetic polymorphism of IFNAR-1 plays a large role in determining the clearance or chronicity after hepatitis B virus (HBV) exposure. However, it is not clear whether type I interferon receptor-1 (IFNAR-1) variations continuously exert their effects to influence the final outcomes following HBV chronicity, including acute-on-chronic hepatitis B liver failure (ACLF-HBV), chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). Here we report that these four potential outcomes of chronic HBV infection are strongly associated with IFNAR-1 polymorphisms through a hospital-based case-control study of 663 cases. ACLF-HBV and HCC were each compared with CHB+LC. In comparison with the G/G genotype, the C/G and C/C genotypes at both single-nucleotide polymorphism (SNP) sites (rs1012335 and rs2257167) showed significant susceptibility to ACLF-HBV (the highest odds ratio [OR] reached 2.374; 95% CI = 1.488, 3.788; p < 0.001 for the C/G genotype at rs2257167), as well as HCC (OR = 2.475; 95% CI = 1.435, 4.426; p < 0.001 for the C/C genotype at rs1012335). The C allele at both loci was a susceptibility allele for ACLF-HBV and HCC, with the highest ORs reaching 1.653 (95% CI = 1.233, 2.216; p < 0.01 at rs1012335) in the ACLF-HBV group, and 1.659 (95% CI = 1.274, 2.159; p < 0.01 at rs1012335) in the HCC group. A strongly linked disequilibrium was also found within these two alleles (p < 0.001). Our research indicates that genetic polymorphisms of IFNAR-1 not only contribute to the determination of clearance or chronicity in the early stages of HBV exposure, but they also persistently influence pathogenesis over the long-term process of chronic HBV infection.

Introduction

A pproximately 2 billion people worldwide have been exposed to hepatitis B virus (HBV) during their lifetime, with more than 350 million chronically infected (1). Exposure to HBV can lead to different clinical courses, ranging from spontaneous recovery to persistent chronic infection that may progress to liver cirrhosis (LC), hepatocellular carcinoma (HCC), and acute-on-chronic hepatitis B liver failure (ACLF-HBV). Understanding the key factors influencing the clinical outcomes of HBV infection is crucial for early diagnosis and optimal treatment (2).

Epidemiological investigations have confirmed the pivotal role of genetic variations in human susceptibility to infectious diseases (3,4). Single-nucleotide polymorphism (SNP) is the most common genetic variation, and it refers to the stable substitution of a single base in the human genome. Some SNPs have been found to be associated with phenotype changes, while others are not. This may be determined by their locations and the synergistic effects of multiple SNPs. For instance, SNPs in the coding sequence can cause a missense codon, which may change the structure and function of a protein, thereby leading to a phenotype change.

It has been found that the same virus can cause various levels of pathogenicity and severity in different people. Given that HBV is non-cytopathic alone, the immune status of the host and the response to HBV infection appears to be important in determining the outcomes seen after HBV exposure. Cytokines secreted by immune cells under attack by various viruses play an essential role in antiviral effects (5 –7). Among the many cytokines released, interferon-(IFN)-α/β has been proven to be one of the most powerful cytokines in viral eradication, as well as in immune modulation for both the innate and adaptive immune responses (8 –10). IFN-α/β exerts its biological function by activating type I interferon receptor (IFNAR), which is composed of two subunits, IFNAR-1 and IFNAR-2. Both IFNAR-1 and IFNAR-2 are required to form a high-affinity binding ligand for receiving signaling from type I IFNs (11). Nevertheless, some studies have shown that antibodies against human IFNAR-1 can block the binding of all type I IFNs to human cells (12,13), suggesting that IFNAR-1 plays a pivotal role in the binding of type I IFNs. Thanks to these important properties, researchers have tried to reveal the linkage between the genetic variations in IFNAR-1 and the susceptibility to virally-caused chronic inflammatory diseases, such as AIDS (14), chronic infection by HCV and HBV (15 –18), multiple sclerosis (19,20), and systemic lupus erythematosus (21). To date three polymorphisms in IFNAR-1 have been reported to play important roles in the determination of clearance or chronicity of initial HBV infection (18,22). However, during the long-term process of persistent chronic HBV infection, patients present with variable clinical courses, including ACLF-HBV, chronic hepatitis B (CHB), LC, or HCC. Therefore the question arises as to whether genetic variations in IFNAR-1 continuously exert effects that influence the final outcomes of HBV chronic infection. Intriguingly, IFN-α/β as a pleiotropic cytokine has been implicated in the pathogenesis of acute inflammation (23), and the process of carcinogenesis (24,25). Therefore it seems rational to infer that there are associations between the genetic variations of IFNAR-1 and predisposition to various other outcomes, such as ACLF-HBV, which is an acute inflammatory event caused by chronic HBV infection, and HCC, which is a common cancer related to HBV infection. One group reported that two SNPs in IFNAR-1 were associated with various presentations of HBV infection, but the study sample was small (less than 100 cases in several groups), and lacked an ACLF-HBV group; moreover, it only examined these conditions in those of Vietnamese ethnicity (17).

In this study we explored the genetic effects of IFNAR-1 on the risk of various outcomes after HBV chronicity with a hospital-based case-control study. To this end, we genotyped two tag SNPs of the IFNAR-1 gene that have been investigated in a cohort of Plasmodium falciparum malaria in the Gambia (26). One is a C/G SNP (rs1012335) located in intron 3 at nt17470, and the other is also a C/G SNP (rs2257167) located in exon 4, causing a missense codon from Val (GTT) to Leu (CTT). We show that these two polymorphisms are associated with clinical outcomes of chronic HBV infection.

Materials and Methods

Study subjects

We used 663 HBV-infected patients in this study, including 136 with ACLF-HBV, 201 with CHB, 102 with HBV-related LC, and 224 with HBV-related HCC. All peripheral blood samples were collected from Tongji Hospital and Union Hospital, Wuhan, China, from July 2007 to September 2009. All study subjects were unrelated ethnic Han Chinese who lived in Wuhan or the surrounding region. Informed consent was obtained from each participant for study enrollment. The study was approved by the local Research Ethics Committee at the Tongji Hospital of Huazhong University of Science and Technology.

The Xi'an standard issued by the Chinese Society of Infectious Diseases was adopted as the diagnostic criteria for ACLF-HBV, which was described in a previous publication (27). The main criteria included a history of CHB or liver cirrhosis with serum HBsAg positivity for 6 mo, serum total bilirubin >10 times the upper limit of normal (>171μM/L), and prothrombin time activity ≤40%. The diagnostic standards for CHB, LC, and HCC were in accordance with a previously published description (28) with minor modifications (Supplementary Table 1; see online supplementary material at http://www.liebertonline.com). The clinical profiles of the study subjects are shown in Table 1.

Table 1.

Clinical Profiles of the Study Subjects

		ACLF-HBV		CHB	LC	HCC
Age (y), mean (range)		41.9 (20–70)		38.4 (20–73)	46.1 (21–73)	47.7 (23–79)
Sex (male/female)		106/30		144/57	89/13	186/38
HBsAg	+	+	+	+	+	+
Anti-HBsAb	−	−	−	−	−	−
HBeAg	+	−	−	+/−	+/−	+/−
Anti-HBeAb	−	+	−	+/−	+/−	+/−
Anti-HBcAb	+	+	+	+/−	+/−	+/−
	22	90	24
Total Number		136		201	102	224

Abbreviations: HBsAg, hepatitis B surface antigen; HBsAb, hepatitis B surface antibody; HBeAg, hepatitis B early antigen; HBcAb, hepatitis B core antibody; ACLF-HBV, acute-on-chronic hepatitis B liver failure; CHB, chronic hepatitis B; LC, liver cirrhosis; HCC, hepatocellular carcinoma.

DNA isolation and genotyping

Genomic DNA was isolated from peripheral whole blood with the QuickGene DNA whole blood kit S (DB-S) with QuickGene-Mini 80 equipment (Fujifilm, Tokyo, Japan). The concentration and purity of the DNA were determined with a NanoDrop spectrophotometer. To detect the SNP locus (rs1012335) in intron 3, we customized the TaqMan probes with VIC (probe: 5′-AACAAAACTCTGTGTCAAAA-3′) and FAM (5′-AACAAAACTCTGTCTCAAAA-3′) dye, as well as the primers for PCR amplification (forward primer: 5′-AGGTTTATCATTGTTATTTCTTTCTTTTTT-3′; reverse primer: 5′-TCCAGCCTGGGCAACAAG-3′) from Applied Biosystems (Foster City, CA). The Taqman probes for the SNP locus (rs2257167) have been commercialized (Applied Biosystems). The genotyping of genetic polymorphisms was performed via the TaqMan method according to the protocol of TaqMan^® SNP Genotyping Assays (Applied Biosystems). Briefly, two probes were labeled with FAM dye and VIC dye to denote the two different alleles. PCR samples were prepared in TaqMan Universal Master Mix (Applied Biosystems), with PCR primer concentrations at 900 nm and TaqMan probe concentrations at 200 nm. Reactions were conducted in a 384-well format, in a total reaction volume of 5 μL, using 20 ng of each genomic DNA. The 384-well plates were then positioned in a thermal cycler (Applied Biosystems 7900HT Fast Real-Time PCR System) and heated for 2 min at 50°C and 10 min at 95°C, followed by 40 cycles at 95°C for 15 sec, and 60°C for 1 min. After PCR amplification, an end-point plate reading was performed to determine the fluorescence intensity in each well. According to the intensity of the VIC and FAM dye, we could categorize each sample into a certain genotype, with VIC or FAM fluorescence alone indicating one of two homozygote genotypes, and a VIC and FAM mixed signal indicating a heterozygote genotype.

Statistical analysis

Statistical analysis was conducted by using Arlequin 3.1 and SPPS 17.0 software. Genotype frequencies in each group were evaluated for Hardy-Weinberg equilibrium. Population pairwise comparisons were conducted by FST test using Arlequin 3.1. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated on the basis of the binary logistic regression models with stratification by gender and age. A p value <0.05 was regarded as significant. The (Bayesian) ELB algorithm was used to infer haplotypes using Arlequin 3.1 software.

Results

Hardy-Weinberg equilibrium test

All samples were collected from the Han Chinese ethnic group. Hardy-Weinberg equilibrium was estimated by Fisher's exact test using Arlequin 3.1 software. There was no significant difference between the observed and expected number of frequencies of each genotype in each group (p > 0.05). This indicates that these populations had a relatively stable genetic background and were suitable for further genetic statistical analysis.

Established categories by population pairwise comparisons

To explore whether there are differences in genotype or haplotype among the groups with various outcomes, we first needed to determine which groups should be compared with each other, and whether there were groups that could be lumped together to simplify statistical analysis. To this end, we performed population pairwise comparisons FST testing between each group using Arlequin 3.1 software. The principle of population pairwise comparisons states that: if there is no difference between two populations, the data permuting of genotypes or haplotypes between two populations should not cause a significant difference, which can be evaluated by FST value. The p value of the test is the proportion of permutations leading to an FST value larger than or equal to the observed one. According to the results shown in Table 2, as well as clinical considerations, we could infer that CHB and LC could be lumped together, as the permutational data for these two groups taken together would not significantly influence the FST value (p > 0.05), and they both were chronic HBV carriers. In contrast, the ACLF-HBV and HCC groups were compared with CHB and LC separately, for they were substantially different outcomes.

Table 2.

Matrix of Significant FST p Values

Group	ACLF-HBV	CHB	LC
ACLF-HBV
CHB	0.01802
LC	0.04505	0.63063
HCC	0.51351	0.02703	0.04505

Population pairwise comparisons FST tests were performed between pairs of groups using Arlequin 3.1 software. Statistically significant values are in shown in bold.

Abbreviations: ACLF-HBV, acute-on-chronic hepatitis B liver failure; CHB, chronic hepatitis B; LC, liver cirrhosis; HCC, hepatocellular carcinoma.

Genetic variations significantly correlated with increased risk of ACLF-HBV

Using population pairwise comparison FST testing, we had determined which groups should be compared with each other. Then, to investigate which genotypes were associated increased susceptibility to the various outcomes, we conducted comparisons of genotype frequencies between the groups using binary logistic regression with sex and age as covariates. As shown in Table 3, the C/G and the C/C genotypes at both SNP sites were associated with a higher risk of acquiring ACLF-HBV than the G/G genotype. The ORs of the C/G genotype were 1.746 (95% CI = 1.101, 2.770; p = 0.018) for rs1012335 and 2.374 (95% CI = 1.488, 3.788; p < 0.001) for rs2257167, while those of the C/C genotype were 2.072 (95% CI = 1.131, 3.795; p = 0.0180) for rs1012335 and 2.348 (95% CI = 1.251, 4.405; p = 0.008) for rs2257167. Allele frequencies also exhibited significant differences, as the C allele in both loci was associated with a greater risk of ACLF-HBV (OR = 1.506; 95% CI = 1.123l, 2.020; p = 0.006 for rs1012335, and OR = 1.653; 95% CI = 1.233, 2.216; p = 0.001 for rs2257167). We concluded that the germline genotypes at the SNPs affect the predisposition to developing ACLF-HBV.

Table 3.

Logistic Analysis of the IFNAR-1 Polymorphisms with Respect to ACLF-HBV

Locus (dbSNP)	Allele/genotype	ACLF-HBV (n = 136) no. (%)	CHB+LC (n = 303) no. (%)	OR (95% CI)	p Value
rs1012335	G	150 (55.15)	262 + 134 (65.40)	1 (referent)
	C	122 (44.85)	140 + 70 (34.60)	1.506 (1.123, 2.020)	0.006
	G/G	42 (30.88)	87 + 47 (44.22)	1 (referent)
	C/G	68 (50.00)	88 + 40 (42.24)	1.746 (1.101, 2.770)	0.018
	C/C	26 (19.12)	26 + 15 (13.53)	2.072 (1.131, 3.795)	0.018
rs2257167	G	148 (54.41)	270 + 131 (66.17)	1 (referent)
	C	124 (45.59)	132 + 73 (33.83)	1.653 (1.233, 2.216)	0.001
	G/G	36 (26.47)	93 + 45 (45.54)	1 (referent)
	C/G	76 (55.88)	84 + 41 (41.25)	2.374 (1.488, 3.788)	<0.001
	C/C	24 (17.65)	24 + 16 (13.20)	2.348 (1.251, 4.405)	0.008

dbSNP refers to the SNP database accessible at the website http://www.ncbi.nlm.nih.gov/projects/SNP/.

Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated on the basis of the binary logistic regression models with stratification by gender and age. Statistically significant values are shown in bold.

Abbreviations: ACLF-HBV, acute-on-chronic hepatitis B liver failure; CHB+LC, chronic hepatitis B + liver cirrhosis.

Genetic variations of IFNAR-1 are associated with susceptibility to HCC

Interestingly, the results of the comparison between HCC and CHB+LC are quite similar to those between ACLF-HBV and CHB+LC. As Table 4 shows, the C/G and C/C genotypes in both SNP sites were also associated with a higher risk of HCC than the GG genotype. The highest OR was 2.475 (95% CI = 1.435, 4.268; p = 0.001), for the C/C genotype for rs1012335. As for the rs2257167 site, both the C/G and C/C genotypes exhibited a tendency toward susceptibility to HCC (OR = 1.347; 95% CI = 0.903, 2.007; p = 0.144 for the C/G genotype, and OR = 2.098; 95% CI = 1.226, 3.592; p = 0.007 for the C/C genotype), but the p value for the C/G genotype was 0.144, and thus did not reach statistical significance. Analysis of allele frequencies confirmed the result that the C allele was a susceptibility allele (OR = 1.659; 95% CI = 1.274, 2.949; p = 0.006 for rs1012335;, and OR = 1.465; 95% CI = 1.124, 1.909; p = 0.005 for rs2257167), and the G allele was a protective allele, at both loci in terms of HCC susceptibility. We concluded that the germline genotype at the SNPs affects predisposition to HCC.

Table 4.

Logistic Analysis of the IFNAR-1 Polymorphisms with Respect to HCC

Locus (dbSNP)	Alleles/genotype	HCC (n = 224) no. (%)	CHB+LC (n = 303) no. (%)	OR (95% CI)	p Value
rs1012335	G	246 (54.91)	262 + 134 (65.40)	1 (referent)
	C	202 (45.29)	140 + 70 (34.60)	1.659 (1.274, 2.159)	0.006
	GG	66 (29.46)	87 + 47 (44.22)	1 (referent)
	CG	114 (50.89)	88 + 40 (42.24)	1.959 (1.302, 2.949)	0.001
	CC	44 (19.64)	26 + 15 (13.53)	2.475 (1.435, 4.268)	0.001
rs2257167	G	260 (58.04)	270 + 131 (66.17)	1 (referent)
	C	188 (41.96)	132 + 73 (33.83)	1.465 (1.124, 1.909)	0.005
	GG	80 (35.71)	93 + 45 (45.54)	1 (referent)
	CG	100 (44.64)	84 + 41 (41.25)	1.347 (0.903, 2.007)	0.144
	CC	44 (19.62)	24 + 16 (13.20)	2.098 (1.226, 3.592)	0.007

dbSNP refers to the SNP database accessible at the website http://www.ncbi.nlm.nih.gov/projects/SNP/.

Abbreviations: ACLF-HBV, acute-on-chronic hepatitis B liver failure; CHB+LC, chronic hepatitis B + liver cirrhosis.

Haplotype analysis showed strong linkage disequilibrium within the two loci

The (Bayesian) ELB algorithm was used to infer the haplotypes of the two loci using Arlequin 3.1 software (29), and the results are shown in Table 5. The protective G–G haplotype made up 50% of each group. The C–G and G–C haplotypes showed a very low level of linkage, under 5% in all groups. Given that these two SNPs showed similar results in their association with susceptibility to ACLF-HBV and HCC, we inferred that there was a linkage disequilibrium between the pair of loci. To verify our inference, a likelihood-ratio test was conducted to test the linkage disequilibrium between the pair of loci with genotypic data using Arlequin 3.1, as previously described by Slatkin and Excoffier (30). In accordance with our expectation, the results indicated that there was a strong linkage disequilibrium in these two loci (Chi-square test value = 931.71; p < 0.001).

Table 5.

The Results of the Haplotype Inference and Linkage Disequilibrium Analysis

Haplotype	All (%)	ACLF-HBV (%)	CHB (%)	LC (%)	HCC (%)
C–C	496 (37.41)	116 (42.65)	131 (32.59)	65 (31.86)	184 (41.07)
G–G	773 (58.30)	144 (52.94)	261 (64.93)	126 (61.76)	242 (54.02)
C–G	36 (2.71)^a	4 (1.47)	9 (2.24)	5 (2.45)	18 (4.02)
G–C	21 (1.58)^a	8 (2.94)	1 (0.25)	8 (3.92)	4 (0.89)
Total	1326	272	402	204	448

Significant linkage disequilibrium (significance level = 0.0500).

The test procedure for linkage disequilibrium was analogous to Fisher's exact test on a two-by-two contingency table, but was extended to a contingency table of arbitrary size.

Abbreviations: CHB, chronic hepatitis B; LC, liver cirrhosis; HCC, hepatocellular carcinoma; ACLF-HBV, acute-on-chronic hepatitis B liver failure.

Discussion

Single-nucleotide polymorphism (SNP) analysis has been widely used in association studies to map genetic variations, determine the frequencies of given SNPs, and to verify their associations with various diseases (31 –33). It is generally accepted that genetic variations in human immune-related genes play a large role in determining chronicity or clearance at the early stages of HBV infection. However, with continuing chronicity, patients may present with various clinical courses, including ACLF-HBV, CHB, LC, and HCC. Thus it appears that genetic factors may exert effects during the long-term process of chronic HBV infection.

In this study we showed that two polymorphisms on the IFNAR-1 gene are associated with susceptibility to ACLF-HBV and HCC. One (rs1012335) is located in intron 3 of the IFNAR-1 gene, and the other (rs2257167) is in exon 4, leading to a Val-to-Leu missense mutation. IFNAR-1 is one of the subunits of the type 1 interferon receptor that can be mediated by IFN-α/β. Polymorphisms in IFNAR-1 have been reported to be associated with HBV chronicity (22). Our results indicate that the IFN-α/β-induced signaling pathway can not only participate in the early-stage pathogenesis of HBV infection, affecting clearance or chronicity, but it also persistently exhibits biological effects during the long-term course of chronic HBV infection, and influences final outcomes. This observation can be explained by the versatile role IFN-α/β plays in different biological processes. For instance, Zhang et al. found that type I IFNs could restrict acute inflammation via downregulation of neonatal B cells in early life (23). Inglefield et al. and Currie et al. separately found that the IFN-α/β signaling pathway was implicated in the anti-tumor process mediated by the toll-like receptor signaling pathway (24,25).

We also found another interesting phenomenon, namely that the C/C and C/G genotypes in the two loci were associated with increased susceptibility to both ACLF-HBV and HCC. In other words, patients susceptible to ACLF-HBV have similar genetic backgrounds in terms of the IFNAR-1 gene, and are thus predisposed to acquire HBV-related HCC. Given the age difference between the onset of ACLF-HBV and HCC, we propose a hypothesis, namely that if a person who has the susceptibility genotype for ACLF-HBV does not develop ACLF-HBV at an early age, they might acquire HBV-related HCC at a later age. This is an interesting hypothesis, but it needs to be borne out by larger case-control studies. Since the genetic basis of these types of diseases is complex, differences in one or even several loci of a gene are usually not enough to affect clinical outcomes. Therefore, although ACLF-HBV and HCC have similar genetic variations with regard to the IFNAR-1 gene, there are likely to be other genetic factors affecting final outcomes, such as polymorphisms in other genes [e.g., TNF-α/β (34), estrogen receptor α (35), N-acetyltransferase (36), mannose-binding lectin (37), chemokine receptor 5 (34,38), and other cytokine genes (39 –41)]. Thus the final outcome of HBV infection is not determined by a single gene variation, but likely results from the effects of many types of genetic variations.

Finally, the results of the haplotype analysis revealed a strong linkage disequilibrium in these two loci in the Chinese Han cohort we studied. Although four haplotypes could be detected in all groups, the C–C and G–G haplotypes in both loci were obviously the major pattern of linkage, making up over 90% of the haplotypes, while the C–G and G–C haplotypes made up only 7%. This result is quite different from that of another group of researchers, whose study involved 458 Vietnamese patients and 160 healthy controls (17). In that study, the C–G and G–C haplotypes made up over 60% in the HBV-carrier group, as well as in the healthy controls. This difference indicates that the overall distribution of haplotypes is significantly different in those of Chinese Han ethnicity and those of Vietnamese ethnicity. The C–C and G–G haplotypes were dominant in the Chinese Han group, whereas all four haplotypes were relatively evenly distributed in the Vietnamese group (17). This divergence indicates that Chinese Han people and Vietnamese people may have different genetic backgrounds with regard to IFNAR-1.

More recently, the anti-tumor effect of IFN has been highlighted by the discovery that the IFN-associated cytotoxic cellular immune response is implicated in the eradication of established solid tumors (25,42). Thus the association between the polymorphisms of IFNAR-1 and the susceptibility to various types of cancer is another interesting avenue of exploration.

Conclusion

Here we revealed the important role of genetic variations in the IFNAR-1 gene and their contribution to final outcomes of chronic HBV infection. Our research indicates that the genetic background of hosts not only affects chronic HBV clearance or chronicity at early stages, but it also persistently influences the long-term course of HBV infection. These findings offer new insights into the effects of genetic variations in IFNAR-1 on outcomes of chronic HBV infection.

Footnotes

Acknowledgments

This study was funded by the National Natural Science Foundation of China (grant no. 30872237), and the National Basic Research Program of China (grant no. 2007CB512900).

Author Disclosure Statement

No competing financial interests exist.

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