A Serum MicroRNA Signature Is Associated with the Immune Control of Chronic Hepatitis B Virus Infection

Background and Aims The virus/host interplay mediates liver pathology in chronic HBV infection. MiRNAs play a pivotal role in virus/host interactions and are detected in both serum and HBsAg-particles, but studies of their dynamics during chronic infection and antiviral therapy are missing. We studied serum miRNAs during different phases of chronic HBV infection and antiviral treatment. Methods MiRNAs were profiled by miRCURY-LNA-Universal-RT-miRNA-PCR (Exiqon-A/S) and qPCR-panels-I/II-739-miRNA-assays and single-RT-q-PCRs. Two cohorts of well-characterized HBsAg-carriers were studied (median follow-up 34–52 months): a) training-panel (141 sera) and HBsAg-particles (32 samples) from 61 HBsAg-carriers and b) validation-panel (136 sera) from 84 carriers. Results Thirty-one miRNAs were differentially expressed in inactive-carriers (IC) and chronic-hepatitis-B (CHB) with the largest difference for miR-122-5p, miR-99a-5p and miR-192-5p (liver-specific-miRNAs), over-expressed in both sera and HBsAg-particles of CHB (ANOVA/U-test p-values: <0.000001/0.000001; <0.000001/0.000003; <0.000001/0.000005, respectively) and significantly down-regulated during- and after-treatment in sustained-virological-responders (SVR). MiRNA-profiles of IC and SVR clustered in the heatmap. Liver-miRNAs were combined with miR-335, miR-126 and miR-320a (internal controls) to build a MiR-B-Index with 100% sensitivity, 83.3% and 92.5% specificity (−1.7 cut-off) in both training and validation cohorts to identify IC. MiR-B-Index (−5.72, −20.43/14.38) correlated with ALT (49, 10/2056 U/l, ρ = −0.497, p<0.001), HBV-DNA (4.58, undetectable/>8.3 Log10 IU/mL, ρ = −0.732, p<0.001) and HBsAg (3.40, 0.11/5.49 Log10 IU/mL, ρ = −0.883, p<0.001). At multivariate analysis HBV-DNA (p = 0.002), HBsAg (p<0.001) and infection-phase (p<0.001), but not ALT (p = 0.360) correlated with MiR-B-Index. In SVR to Peg-IFN/NUCs MiR-B-Index improved during-therapy and post-treatment reaching IC-like values (5.32, −1.65/10.91 vs 6.68, 0.54/9.53, p = 0.324) beckoning sustained HBV-immune-control earlier than HBsAg-decline. Conclusions Serum miRNA profile change dynamically during the different phases of chronic HBV infection. We identified a miRNA signature associated with both natural-occurring and therapy-induced immune control of HBV infection. The MiR-B-Index might be a useful biomarker for the early identification of the sustained switch from CHB to inactive HBV-infection in patients treated with antivirals.


Introduction
Hepatitis B Virus (HBV) is not cytopathic and liver pathology is mediated by the interplay between virus and immune system; accordingly, 3 major phases are identified in chronic HBV infection: immune tolerance, activation and immune control [1][2][3]. High viral load and circulating hepatitis B ''e'' antigen (HBeAg) in absence of virus induced liver disease characterize the immune tolerance phase, that is lost when the antiviral immune reaction tries to taper HBV replication causing liver inflammation, namely HBeAg positive chronic hepatitis B (CHB) [1][2][3]. An effective immune activation leads to the immune control of HBV replication (HBV-DNA,2000 IU/mL) and HBeAg/anti-HBe seroconversion, that identifies the inactive HBeAg-negative, HBsAg carrier (IC). When the control of viral replication is ineffective HBeAg-defective HBV-variants are selected with progression to HBeAg-negative, anti-HBe-positive CHB, the most prevalent form of HBV disease worldwide [4][5][6]. Antiviral therapy is aimed to halt disease progression suppressing viral replication with indefinite nucleos(t)ide analogs (NUCs) treatment or achieving a sustained off-therapy immune control after finite courses of Pegylated-interferon (Peg-IFN) [1][2][3]. In recent years monitoring of HBV-DNA and HBsAg serum levels significantly improved the management of antiviral treatment [7][8][9]. However, the decline of HBV-DNA serum levels during Peg-IFN therapy does not help to distinguish responders (SVR) from relapsers (REL) and early HBsAg kinetics are predictive of response in Peg-IFN, but non in NUC treated patients [8]. In addition the kinetics of constitutive HBV markers are the biological hallmark of viral expression, but not the expression of the host's response to antivirals. Thus, serum biomarkers of the effective control of HBV infection are currently unsatisfactory and remain an unmet need in the clinical management of chronic HBV carriers [1][2][3]. MicroRNAs (miRNAs), are small endogenous single-stranded RNAs that modulate the expression of cellular genes and play key roles in vital biological processes and immunity [10]. Host-and/or virusencoded miRNAs appear to regulate the outcome of both infections and diseases [11][12], as shown for the liver-specific miRNA, miR-122, that is essential for the replication of hepatitis C virus (HCV) [13]. In chronic HBV infection several miRNAs are up-regulated in the serum of HBsAg carriers as compared to controls and circulating HBsAg particles carry specific hepatocellular miRNAs [14][15]. Preliminary reports suggest that serum miRNA profiling may contribute to characterize chronic HBV carriers with or without HCC [16][17][18]. However, studies focused on the relations between serum miRNAs and the different phases of chronic HBV infection and during antiviral therapy are missing: in the present study we analysed the dynamics of miRNA profiles in sera and circulating HBsAg particles of IC and CHB according to treatment response.

Study population
Training cohort. Serum samples (141) were obtained from 61 (40 males, median age 50 years, 21-79) well characterized HBsAg carriers, 57 infected with HBV genotype D and 4 genotype A (Table 1). In case of low HBV-DNA levels (,20000 IU/mL) and normal transaminases (ALT) at presentation, they were followed for at least 1 year with monthly blood tests for classification [1,6], thereafter every 3/6 months (m) as all the other HBV carriers. The HBV carriers were followed-up (median follow-up 34, 18-144 m) at the Hepatology Unit of the University Hospital of Pisa. The study was approved by the local Ethic Committee of the University Hospital of Pisa. All patients provided informed written consent.
HBsAg carriers were classified according to their biochemical and viral profiles [1,6] Thirty-two HBeAg negative CHB patients underwent to antiviral treatment: 21 received Peg-IFN 180 mg/week 6 NUCs for 12-36 m and 11 NUCs for a median period of 60 m (36-114 m); in 2 patients who cleared HBsAg, NUCs were discontinued after 36 and 112 m, respectively. Response to Peg-IFN was defined as: a) end of treatment (EOT) response if HBV-DNA was ,2000 IU/mL at EOT (18 cases); b) non response (NR) if HBV-DNA was .2000 IU/mL at EOT (3 cases); c) relapse (REL) when florid viral replication recurred after an EOT response (5 cases); d) sustained virologic response (SVR) if viral load persisted ,2000 IU/mL at every 3 month controls for at least 12 months after EOT (13 cases). Sera were obtained at baseline (BL) and week 24 post-treatment (post-T-FU) in all Peg-IFN treated patients; additional sampling (week 12 and 24 during treatment, EOT) were obtained in 14 patients. In NUCs treated patients (all achieved undetectable on treatment serum HBV-DNA) serum samples were obtained at BL and at their last available on treatment follow-up (EOF) or 24 weeks after NUCs discontinuation (post-T-FU). In 5 HBeAg positive carriers, 16 IC carriers and 4 HBV/HDV patients sera were obtained at a single time point; in 4 HBeAg negative CHB patients with fluctuating disease profiles the sampling was performed during spontaneous remission (ALT range 19-28 U/L; HBV-DNA 3.71-4.57 Log 10 IU/mL) and at the time of HBV reactivation (ALT range 210-550 U/L; HBV-DNA 4.35-7.18 Log 10 IU/mL). MiRNA profiling was obtained from whole serum in all samples; in addition, to target specifically hepatocellular miRNAs, the profiling was performed in HBsAg immune precipitated (IP) particle from 32 sera [6 from IC and 26 from 13 HBeAg negative CHB patients, with SVR (5), REL (5) or NR (3) to Peg-IFN].

Validation cohort
A second well characterized cohort of 84 HBV carriers (59 males, median age 54 years, 17-79) followed-up for 52 m (18-159 m) and classified according to the above defined criteria was used to generate the validation serum panel (overall 136 sera) of the MiR-B-Index (Table 1). Serum samples were obtained at a single point in 23 IC, 5 IT and 4 untreated HBeAg negative CHB patients. In 52 (16 HBeAg positive) treated patients, samples were collected at BL and 24 week Post-T-FU in the 15 Peg-IFN 6 NUC treated patients [9 HBeAg positive: 5 with SVR (HBeAg/ anti-HBe seroconversion and HBV-DNA,2000 IU/mL at EOT and in post-T-FU); 6 HBeAg negative: 1 SVR, 4 REL, 1 NR] and at BL and EOF in the 37 patients (7 HBeAg positive) treated with NUCs (all achieved undetectable on treatment HBV-DNA, none cleared HBsAg). In addition, 15 serum samples of the study cohort were retested together with the validation cohort.

Serological tests
HBsAg qualitative and quantitative, anti-HBs, anti-HBc, IgM anti-HBc HBeAg and anti-HBe, anti-HCV, anti-HDV and anti-HIV were detected by commercially available immunoassays (Abbott laboratories, N. Chicago, IL, USA). Serum HBV DNA levels were quantified by COBAS TaqMan assay, sensitivity 6 IU/ mL, dynamic range 6-1.70610 8 IU/mL (Roche Diagnostic Systems Inc, Mannheim, Germany). HBV genotyping was performed by direct sequencing of the small HBs region. Serum ALT levels were tested by routine biochemistry (normal range: , 45 U/L and ,33 U/L for male and female respectively). Circulating HBsAg particles were obtained by immunoprecipitation as previously reported [14]. RNA-isolation, cDNA-synthesis and RT-q-PCR Total RNA was extracted from 200 mL serum or HBsAg-IP (resuspended in PBS) using miRNeasy-Mini-kit (Qiagen-Inc.) as described [19]. RNA (16 mL) was reverse-transcribed and profiled on q-PCR panels in 80 mL reactions using the miRCURY-LNA Universal-RT-cDNA-Synthesis and RT-miRNA-PCR (Exiqon-A/S). The cDNA was diluted 1:50 and assayed in 10 mL PCR reactions; each miRNA was assayed once by qPCR on the Readyto-use microRNA-PCR panels I/II containing 739-miRNAassays. The amplification was performed in a LightCycler 480-System (Roche-Applied-Science) in 384-well-plates.

Data analysis and statistics
The amplification curves of miRNAs were analyzed using the Roche LC software for the quantification of cycles (Cq), by the second derivative max method, according to the recommendations of the Minimum Information for Publication of Quantitative Realtime PCR Experiments (MIQE) [20] and for the melting curve analysis. The amplification efficiency was calculated using the LinReg algorithm with criteria between 0.8-1.1 [21][22]. All assays were inspected for distinct melting curves and the Tm was checked to be within known specifications for each particular assay. Furthermore any sample assay data point to be included in the data analysis had to be detected with 5 Cq less than the corresponding negative control assay data point and with a Cq, 37 for serum samples, but 3 Cq less than the corresponding negative control assay data point and with a Cq,37 for IP HBsAg samples due to lower signal. Data that did not pass these criteria were omitted from any further analysis. Normfinder was used to find the best normalizer candidates which in this study was the Global Mean of all assays expressed in all samples tested [23][24]. By this approach we normalised all miRNAs Cq, obtaining for each miRNA the DCq. In all statistical comparison we used a number of assays based on the criteria that the smallest groups of analysed cases needed data present in all samples. We subtracted the microRNAs value from the sample average (global mean), thus the larger the value, the higher is the miRNA expression in reported results. For example when we obtain a positive DDCq value after subtraction, a control group mean value from an affected group mean value 2 (DCq(affected)2DCq(Ctrl)) then a value of one means 2 (1) , namely double as much expression for the given miRNA, on average, in the affected group. Statistics and data presentation were performed in Microsoft Excel, GraphPad Prism 6.03 and TIGR's Multiple Experiment Viewer (MEV) version 4.8 [25][26]. Correlations of miRNA profiling, MiR-B-Index and their variation over time in the different groups of HBsAg carriers were analysed by Spearman test, Mann-Whitney U-Test, Kruskal-Wallis test, Student t test, analysis of variance (ANOVA) and ANOVA for repeated measures, when appropriate. When values per group were few for ANOVA or other statistics we used the fold-change-method to evaluate up-or down-regulations using a 2fold-change as threshold [27]. Linear regression analysis was performed to evaluate the independent variables associated with MiR-B-Index and its D-variation. The diagnostic performance of Mir-B-Index for the identification of IC versus CHB patients was evaluated by ROC curve analysis; the selection of cut-off value was aimed to maximize the sensitivity (100% of IC). The statistical analyses were performed using SPSS version 19.0 (IBM Corp., Armonk, NY). The statistical significance was defined as p,0.05, after Bonferroni correction when required.

HBsAg particles miRNA profiling
A 44 miRNAs average yield was obtained from each HBsAgpellet with an overall mean Cq of 34 after quality control (QC) and background filtering. No miRNA was expressed in all samples, therefore, normalization was performed adding the UniSp4 spikein (RNA-spike-in-kit, Exiqon-AS) in the RNA purification process to monitor small RNA yields. When comparing the different groups (IC, untreated and treated HBeAg-negative CHB patients), we analyzed 32 miRNAs with 15 or more values across the 32 samples (37 Cq background filter value was given for missing or filtered values). Differences in the miRNAs expression (DCq) were observed comparing IC samples with that of BL-CHB (SVR, REL, NR) and REL/NR-post-T-FU, but not between IC and SVR-post-T-FU ones, that showed major difference with the other groups ( Table 2 (Table 2). An unsupervised two-way hierarchical clustering of miRNAs and samples showed the clustering of IC with SVR-post-T-FU ( Figure 1). Finally, we compared the most differentially expressed miRNAs (32) in ours and in the study of Novellino et al. [14] (31 miRNAs): in spite of the different platforms which were used, 9 miRNAs were consistently detected in both series, miR-19b, miR-24, miR-26a, miR-27a, miR-30b, miR-30c, miR-106b, miR-122, miR-223.

Serum miRNA profiling
In total we profiled 141 whole sera from 61 chronic carriers in different phases of HBV infection and at different time points during antiviral therapy. The overall miRNA yields were good, 152 of the 739 tested miRNAs passed background filtering and QC and 26 miRNAs were expressed in all samples after excluding only two samples because of low yields (,50 miRNAs passing filtering and QC). Of those 26 microRNAs 7, 14 and 5 assays show standard deviation ,0.5, 0.5-1.0 and .1.0 respectively, after normalization. Sixty-six of the 152 miRNAs that passed the QC criteria were expressed in all samples of the smallest groups (HDV, n = 4 and HBeAg Positive, n = 5), were used in the analysis.  The dataset was normalized using the global mean (n = 26 assays) method [24].
Untreated HBV Carriers. One way ANOVA (after Bonferroni correction, cut-off p = 0.000758) revealed 31 miRNAs with significantly different expression: the largest differences were primarily observed between IC and both HBeAg positive and negative CHB, secondly between HBeAg-positive and HBeAgnegative CHB (Table 3). Among HBeAg positive carriers the miRNA profiling of one immune tolerant carrier was comparable to those of the other 4 patients with CHB. The statistical power of comparisons between HBeAg-positive CHB and HDV/CHB was weakened by the small sample size. Since several miRNAs from HBeAg-negative-CHB failed the Shapiro-Wilk normality test (data not shown), we used individual Wilcoxon, Mann-Whitney U tests yielding very similar results (Table 3). Significant differences were found between IC and CHB patients and the most significant ones affected the same miRNAs showing the largest difference in HBsAg particles of CHB patients and IC, namely miRNA-122-5p (ANOVA and U test p-values: ,0.000001 and 0.000001 respectively); miRNA-192-5p (ANOVA and U test p-values: , 0.000001 and 0.000005); miRNA-99a-5p (ANOVA and U test pvalues: ,0.000001 and 0.000003). Other miRNAs with the largest differences were miR-148a-3p (ANOVA and U test p-values: , 0.000001 and 0.000009) and miR-126-3p (ANOVA and U test pvalues: ,0.000001 and 0.003751). Overall CHB patients showed significantly more liver specific miRNAs than IC. The IC miRNA profile correlated with that of subjects without liver disease of Wang et al. [28] who used the miRCURY qPCR platform [correlations between (n = 47 assays) mean un-normalized-DCq values (40-Cq) Pearson-r = .9470, r 2 = .8968, p,0.000000001; Spearman-r = 0.9373, p,0.000000001, data not shown].
Peg-IFN treated patients. The effect of Peg-IFN on the circulating miRNA profile of HBeAg-negative-CHB was studied comparing BL and week 12 sera in 14 cases [6 SVR, 5 REL and 3 NR]: 8 miRNAs were differentially expressed, but only miR-30e-3p was significantly up-regulated in all patients' sera after Bonferroni adjustment (DDCq 1.7, p = 0.000354, Table 4). Otherwise, only minor differences were seen, indicating that the overall whole serum miRNA profiling did not change significantly after 12 weeks of IFN treatment. Next we looked at the dynamic variation of miRNA profiles during (BL, week 12, 24 and EOT) and after therapy (week 24 post-T-FU) according to treatment response (Table 5). NR did not show, by ANOVA analysis, any significant changes throughout the entire observation period. REL revealed one miRNA, let-7b-5p, with significant differential expression over the 5 time-points. SVR during treatment had significant changes in 5 miRNAs, namely miR-122-5p, miR-21-5p, miR-99a-5p, miR-23a-3p and miR-192-5p. MiR-99a-5p and miR-192-5p were always down-regulated on treatment; miR-21-5p was up-regulated at weeks 12 and 24 and EOT, returning to baseline values at Post-T-FU. MiR-23a-3p was up-regulated over the course of treatment and subsequent follow-up. Comparing NR and REL to SVR, at the different time-points, by one-way ANOVA a total of 21 miRNA resulted significantly differentially expressed, after Bonferroni correction (Table 6): miR-320a and miR-320b and miR-335-5p at week 24 during treatment, but not at other time points; miR-99a-5p at EOT and at 24 week post-T-FU. At EOT additional miRNAs, like miR-122-3p and -5p, miR-192-5p and miR-194, were differentially expressed between the groups as compared to post-T-FU, but the differences did not achieve statistical significance after Bonferroni correction.
NUCs treated patients. All HBeAg negative CHB patients treated with NUCs had undetectable HBV-DNA and ALT within the normal range at EOF/post-T-FU evaluation, that was done 59 Table 2. Cont.   MiR-B-Index, miRNA calculator. We exploited the 3 hepatocellular miRNAs (miR-122-5p+miR-99a-5p+miR-192-5p) with the most significant differential expression in IC versus CHB to build a miRNA calculator. Three additional miRNAs: miR-335 (detected in all serum samples regardless of grouping, and not detected in IP-HBsAg samples), miRNA-126 (down-regulated in serum samples, CHB versus IC, and not detected in IP HBsAg samples) and miR-320a (stable across groups in both serum samples and IP HBsAg) were selected as endogenous controls to account for RNA input variation and other technical variations within the profiling platform. We define this miRNA panel calculator [(Cq miR-122-5p+Cq miR-99a-5p+Cq miR-192-5p) 2(Cq miR-126-3p+Cq miR-335-5p+Cq miR-320a)] as MiR-B-Index.

Discussion
The study of serum miRNA of well characterized HBsAg carriers shows important variations of their profiles across the different phases of chronic HBV infection: the major difference is observed between inactive carriers and chronic hepatitis patients, who show a highly significant over-expression of miR-122-5p, miR-99a-5p and miR-192-5p (Table 3). The same miRNAs reveal a consonant profile in circulating HBsAg-particles, where major differences in the expression of the 32 most commonly detected miRNAs, were observed when comparing IC to untreated CHB patients. In patients with SVR to Peg-IFN the post-T-FU sera presented miRNA profiles highly similar to IC (Table 2) and the heatmap demonstrated the clustering of these 2 groups (IC and SVR-post-T-FU samples; Figure 1). On the contrary, in Relapsers and Non Responders the post-T-FU miRNAs patterns matched those of BL. These findings support the hypothesis that consistent changes in circulating miRNA profiles parallel the immune control of HBV infection. Accordingly, CHB patients with SVR to Peg-IFN, at variance with REL and NR, experienced the largest difference in their serum miRNA signature overtime, with major variations of the miRNA average signal (DCq) when comparing post-T-FU with BL samples (Table 2; Figure 1). In 14 patients whose miRNA profiles could be studied across their whole treatment course we observed that serum miRNA patterns did not change significantly during the first 12 weeks of Peg-IFN, with the exception of miR-30e-3p, that was up-regulated in all patients (Table 4; p = 0.000354). Our finding is in agreement with a previous report suggesting an early induction of the miRs-30 cluster by IFN independently of therapy response [26]. During the course of treatment, NR patients did not show any significant variation of additional miRNAs, whereas REL had significant differential expression over the 5 time-points of miRNA let-7b-5p ( Table 5). The implications of such miRNA modulation deserve further investigation since the up-regulation of let-7 family during IFN therapy was reported to inhibit hepatitis C virus replication [29]. The comparison of NR/REL and SVR at every time point (Table 6) showed that 21 miRNAs were differentially expressed and 5 of them, miR-122-5p, miR-21-5p, miR-23a-3p, miR-99a-5p and miR-192-5p had the most significant changes during treatment in SVR. MiRNA-99a-5p and miRNA-192-5p were down-regulated throughout treatment and post-T-FU, whereas miRNA-21-5p was up-regulated at week 12, 24 and EOT and returned to BL-values at post-T-FU. Interestingly miR-122-5p, miR-99a-5p and miR-192-5p showed parallel differential patterns in whole serum and HBsAg-particles of IC and CHB patients once they achieved SVR as compared to untreated CHB and REL/ NR. These 3 miRNAs are the 1 st , 2 nd and 6 th most represented miRNAs of human liver [16,28]: serum miR-122 and miR-99 levels had been shown to be higher in HBsAg carriers than healthy controls [16] and miR-122 and miR-192 associated with liver necro-inflammation [30][31][32][33][34].
The findings prompted us to evaluate a combination of the most significant miRNAs to produce a MiR-B-Index to identify the sustained switch from active to inactive HBV infection in treated NUCs treatment even though all the patients normalized ALT, only a proportion of them experienced a significant improvement of MiR-B Index. These findings do not support the hypothesis that the MiR-B-Index results from the amount of liver damage, but suggest that it could indeed mirror the extent of HBV infection control. Indeed in untreated HBV carriers its values showed a very high correlation (r = 20.904, p,0.001) with HBsAg serum levels, that are inversely correlated with the extent of the immune control [6,8]. All NUC treated patients with HBsAg/anti-HBs seroconversion or decline of HBsAg serum levels ,400 IU/mL showed a consistent MiR-B-Index improvement with values above the 21.7 cut-off. Overall, MiR-B-Index variations during NUC therapy appear closely linked with those of HBsAg, however our findings suggest that its variations beckon the effective achievement of sustained immune control of HBV with faster kinetics than HBsAg [5][6]. Accordingly, in SVR to Peg-IFN the correlation between MiR-B-Index and HBsAg serum levels at post-T-FU was not significant (r = 20.423, p = 0.08) and among the 6 patients with SVR in whom we tested EOT samples the MiR-B-Index was already improved with IC like values in 4 (66%). Thus, it appears that, during antiviral therapy, MiR-B-Index provides complementary information to HBsAg monitoring. Furthermore, a few HBeAg negative CHB patients with SVR to Peg-IFN showed MiR-B-Index values comparable to IC already at baseline with further improvement during treatment, whereas this never occurred in NR and REL; during NUC therapy, the improvement of MiR-B-Index was influenced by baseline MiR-B-Index values. Both evidences suggest that MiR-B-Index could help to identify patients susceptible to respond to Peg-IFN and to achieve a sustained control of HBV infection during a time limited NUC treatment. Altogether these findings propose the MiR-B-Index as candidate biomarker to predict and to identify either spontaneous or therapy induced transition from active to inactive phase of chronic HBV infection. MiR-B-Index might be helpful to tailor antiviral treatment at the individual level, identifying NUCs treated patients who could stop therapy safely without risk of hepatitis B relapse once they achieve a sustained immune control of HBV infection or IFN treated patients who could benefit from prolonged treatment.
In conclusion our study shows for the 1 st time that the dynamic change of a miRNA signature may identify both natural occurring and therapy induced immune control of HBV infection. The same signature qualifies as new diagnostic biomarker to satisfy the unmet need of the early identification of the sustained switch from chronic active hepatitis B to the inactive HBV infection in patients treated with antivirals. MiR-B-Index is worth being tested in larger cohorts of patients infected with different HBV genotypes, treated with different antivirals and with different therapy outcomes.