Mutational analysis of different epitopes in hepatitis B virus small surface protein among blood donors in Guangzhou, China: nonimmune epitope mutations as a nonnegligible factor

Introduction

Hepatitis B virus (HBV) infection represents a major global health concern due to its strong association with chronic liver damage, cirrhosis, and hepatic malignancies (1,2). Globally, the prevalence of chronic HBV infection is about 4.1% (3), while in China, recent estimates place the general population prevalence between 3% and 5.9% (4-7). Despite the positive impact of the vaccination program in reducing the HBV infection rate over the last four decades, the prevalence of HBV continues to be alarmingly elevated among high-risk populations. Therefore, China still bears the world’s largest burden of chronic HBV infection (4,5).

Hepatitis B surface antigen (HBsAg) is a major target for eliciting humoral immunity (antibody-mediated) and cellular immunity (T cell-mediated) against HBV infection. Structurally, the HBV S protein—the main structural component of HBsAg—has a complex topology featuring four transmembrane helices (TM1–4), one large internal loop, and the major hydrophilic region (MHR); the latter is a well-characterized segment that overlaps with key B-cell epitopes (e.g., the “a” determinant) and is closely associated with humoral immune recognition (8-10). Mutations in HBV may be prompted by immune pressure, antiviral therapy or may arise naturally and accumulate during chronic infection. Of particular clinical significance are immune escape mutants that arise under active and/or passive immunization and contribute to vaccine breakthrough infections (11-13). Mutations in the HBV S protein represent a key mechanism by which the virus evades both B- and T-cell-mediated immune responses; additionally, these mutations are closely associated with vaccine breakthroughs and may promote HBV reactivation. Mutations disrupting B- and T-cell epitopes can profoundly affect the immunoreactivity of HBsAg, weakening the capacity of MHC and MHC class II-restricted Th to recognize B- and T-cell. Moreover, these mutations decrease the binding capacity of MHC class I-mediated antigen presentation complexes and modified oligopeptides, which consequently impairs antigen presentation on the surface of hepatocytes, thereby enabling HBV to circumvent immune detection and elimination (7,14,15).

This study was designed to systematically analyze the surface protein variations in voluntary blood donors in Guangzhou, China. Additionally, the study focused on mutations in nonimmune and immune epitopes including B-cell epitopes, Th-cell epitopes and cytotoxic T lymphocyte (CTL) epitopes.

Methods

Samples

Plasma samples were collected from voluntary blood donors with HBV infection at the Guangzhou Blood Center between June 2018 and January 2019. Donors were defined as “HBV-infected” if they tested positive for both HBsAg and HBV DNA; those with occult HBV infection (OBI), characterized by HBsAg negativity and HBV DNA positivity, were excluded as they did not meet this predefined diagnostic criterion. During the study period, a total of 320 HBV-infected blood donors were initially identified through routine screening, and DNA amplification was performed on samples from these 320 donors. HBsAg was examined by enzyme-linked immunosorbent assay (ELISA) kits (Kehua Diagnostics, Shanghai, China; Wantai Diagnostics, Beijing, China) and HBV DNA was detected via transcription-mediated amplification (TMA) (Ultrio Plus HBV Discriminatory Assay, Grifols Diagnostic Solutions, Inc., Emeryville, USA). Alanine aminotransferase (ALT) levels were examined by kinetic assay (Kehua Diagnostics and Wantai Diagnostics, Hitachi 7180 Automatic Biochemical Analyzer). To rule out co-infection, all samples were negative for HCV antibodies, HIV antibodies, T. pallidum antibodies, as well as HCV and HIV nucleic acids. Ultimately, DNA amplification was successful for 107 samples, and only these 107 qualified samples were included in the subsequent study analyses; all plasma samples were stored at −20 ℃ prior to testing to ensure stability.

HBV DNA amplification and sequencing

HBV DNA was extracted from plasma using the High Pure Viral Nucleic Acid Kit (Roche Diagnostic, Indianapolis, USA). Viral load quantification was performed via real-time polymerase chain reaction (PCR) (DaAn Gene) with a limit of detection (LOD) of 20 IU/mL, and the S region was amplified via nested PCR and sequenced by bidirectional Sanger sequencing (Invitrogen, Guangzhou, China) as previously described (16,17).

Phylogenetic analysis

Phylogenetic trees were constructed with molecular evolutionary genetics analysis (MEGA) 11.0 using the maximum likelihood method. The Kimura 2-parameter (K2P) model was selected as the nucleotide substitution model, and the analysis was performed with 1,000 bootstrap replicates for branch support. Sequences obtained were aligned with reference sequences of the S region from National Center for Biotechnology Information (NCBI; 87 genotype B, 80 genotype C, and 5 genotype D sequences), which are labeled with their respective GenBank accession numbers.

Mutation analysis

Consensus sequences of the HBV genotype B and C S regions were synthesized by comprehensive alignment and comparison of 81 genotype B and 25 genotype C S gene sequences, respectively. Nucleotide sequences and consensus sequences were aligned and manually edited using BioEdit 7.0 software. The analysis was conducted based on the documented distribution patterns of immune epitopes within HBV surface proteins, including Th-cell epitopes (aa 19–28, 80–98, 186–197, 215–223), CTL cell epitopes (aa 28–51, 171–179, 175–184, 206–215), and B-cell epitopes (aa 100–160) (18-21). Nonimmune epitopes were explicitly defined as regions of HBV surface proteins (aa 1–226) that do not overlap with immune epitopes, with their specific coordinates as follows: aa 1–18, 52–79, 99, 161–170, 185, 198–205, 224–226. For HBV S protein amino acid variations, positions 122, 126, and 127 were considered subtype-specific polymorphisms and excluded from the mutation count, in line with the convention in HBV molecular epidemiology studies (22,23). Mutation rates were calculated as the number of mutations divided by the total number of amino acids in the target regions.

Statistical analysis

The statistical analysis was conducted using MEGA 11.0 and GraphPad Prism 9.5.1 software. The Mann-Whitney U-test (for two groups) and Kruskal-Wallis test (for three groups) were used to compare continuous variables among different genotypes and differences in mutation rates between different regions. The Spearman method was used to analyze the correlations between the number of mutations in different regions and HBV DNA levels, as well as between the number of mutations in different regions and ALT levels. For HBV DNA data that were not detectable (i.e., < LOD), they were imputed with LOD/2. Statistical significance was defined as P<0.05 (two-tailed).

Ethical consideration

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of Guangzhou Blood Center (No. Guangzhou Blood Center [2023] No. 017) and informed consent was obtained from all individual participants.

Results

Baseline characteristics of the blood donors

The study included 107 HBV-infected blood donors (positive for both HBsAg and HBV DNA), consisting of 72 males (67.29%) and 35 females (32.71%) with a mean age of 37.63±9.99 years. The mean ALT levels were 16.21±12.07 U/L, with only 4 out of the total donors showing elevated ALT levels (defined as ALT >40 U/L); the average HBV viral load of the blood donors was 3.31±1.79 logIU/mL (Table 1).

Genotyping and phylogenetic trees

The variation analysis of the S gene in 107 HBV-infected voluntary blood donors demonstrated that the viral genotypes were B: 75.70% (n=81), C: 23.36% (n=25) and D: 0.93% (n=1) (Figure 1).

Figure 1 Phylogenetic analysis of HBV genotype distribution in blood donors. Maximum likelihood phylogenetic inference was conducted using MEGA with 1,000 bootstrap replicates. S gene sequences of 107 HBV (samples in this study, shown in green) were aligned against reference sequences from 87 genotype B, 80 genotype C and 5 genotype D HBV indicated by different colors. Reference HBV sequences used for tree construction are labeled with their respective NCBI GenBank accession numbers. HBV, hepatitis B virus; MEGA, molecular evolutionary genetics analysis; NCBI, National Center for Biotechnology Information.

Mutations within HBV S protein

Among 107 HBV-infected voluntary blood donors, 79 individuals (73.83%) exhibited at least one amino acid mutation, whereas 6 cases (5.61%) showed no nucleotide or amino acid substitutions. A total of 683 nucleotide substitutions were identified, of which 329 (48.17%) were missense mutations (causing amino acid alterations) and 354 (51.83%) were silent mutations (without amino acid changes) (Table 2). The mean ratio of missense substitutions to silent substitutions was 0.93. At the amino acid level, 384 substitutions were identified, which affected 102 distinct amino acid positions. Regarding genetic variations in the HBV S gene, no novel start codons, stop codons, insertions, or deletions were identified (result not shown).

In accordance with the proposed immune epitopes of the HBV surface protein (18-21), 236 (61.46%) out of 384 amino acid alterations were detected within immune epitopes of the surface protein. Specifically, 29 (12.29%) mutations were located in 17 residues of B-cell epitopes, 64 (27.12%) in 26 residues of Th-cell epitopes, and 144 (61.02%) in 24 residues of CTL epitopes (Table 2).

Analysis of B-cell epitopes (aa 100–160) revealed that 15 (3.91%) of the total 384 amino acid substitutions were localized within the “a” determinant region [124–147]. Notably, four hotspot residues were identified in this domain, contributing to 13 substitutions: 4, 3, 3 and 3 at amino acid positions 133, 101, 129 and 159, respectively (Figure 2, blue highlights). In contrast, 14 (3.65%) mutation events were detected in the MHR outside the “a” determinant.

Figure 2 Heatmap depicting amino acid substitution profiles across distinct immune epitope domains in the surface protein. Green denotes Th-cell epitopes, red indicates CTL epitopes, blue represents B-cell epitopes, and white signifies nonimmune epitopes. The topological elements of the S protein are schematically labeled at the top of the sequence: four transmembrane helices (TM1–4), the large internal loop, and the MHR are marked with different colors for clear identification. Note that amino acid changes at positions 122, 126, and 127 are not classified as mutations; these alterations are represented by the original substituted amino acids to distinguish them from true mutations. (A) Amino acid substitutions of genotype B. (B) Amino acid substitutions of genotype C. CTL, cytotoxic T lymphocyte; MHR, major hydrophilic region.

Within the studied proteins, 64 mutations across 26 amino acid residues were identified within four Th epitope domains (comprising a total of 50 residues). Specifically, mutations were distributed as follows: 23 (35.94%) in domains 19–28, 15 (23.44%) in domains 80–98, 8 (12.50%) in domains 186–197, and 18 (28.13%) in domains 215-223 (Figure 2, green highlights). Notably, amino acid positions 21, 189, 217, and 220 exhibited 15, 5, 5, and 7 substitutions, respectively (Table 3).

Among 144 mutations across 24 positions in CTL epitopes, 95 (65.97%), 4 (2.78%), 6 (4.17%), and 41 (28.47%) substitutions were identified in epitopes 28–51, 171–179, 175–184, and 206–215, respectively (Figure 2, red highlights). Amino acid substitutions at positions 40, 44, 45, 47, 206, 210, and 213 contributed to 26, 25, 10, 14, 7, 9, and 19 mutations, respectively (Table 3).

Among 148 mutations identified across 36 positions within nonimmune epitopes, substitutions were observed at the following frequencies: 34 (22.97%) in epitopes 1–18, 48 (32.43%) in epitopes 52–79, 10 (6.76%) in epitopes 161–170, 46 (31.08%) in epitopes 198–205, and 10 (6.76%) in epitopes 224–226 (Figure 2, white color). Notably, substitutions at positions 3, 5, 53, 76, 200, and 204 led to 8, 8, 9, 8, 23 and 16 amino acid changes, respectively (Table 3).

Surface protein variations with different genotypes

Between the two genotypes under investigation, no statistical significance was observed in either nucleotide mutation comparisons or amino acid mutation comparisons (classified into immune, B-cell, Th-cell, CTL and nonimmune epitopes), with all P-values ranging from 0.18 to 0.81 (Table 4).

Surface protein variations and clinical status

Correlation analysis between the HBsAg substitution levels and HBV DNA levels showed significant correlations for the following mutation indices: nucleotide mutations (P=0.004), amino acid mutations (P=0.004), immune epitope mutations (P<0.001), and CTL epitope mutations (P<0.001). In contrast, correlation analysis between the number of HBsAg mutations and ALT levels revealed significant correlations only for immune epitope mutations (P=0.007) and CTL epitope mutations (P=0.007).

Mutation rates of different epitope domains

Comparison of the mutation rates of different immune epitopes showed that the mutation rate of the nonimmune epitope was significantly higher than that of the immune epitope (P=0.003; Figure 3A). Additionally, the mutation rates of CTL epitope and Th-cell epitope were significantly higher than that of B-cell epitope (P<0.001; Figure 3B). Meanwhile, the mutation rate of CTL epitope was also significantly higher than that of Th-cell epitope (P=0.002).

Figure 3 Comparison of mutation rates of different epitope domains of HBV surface protein. Boxplots depict the distribution of mutation rates. Whiskers represent the full range of values, and boxes indicate the interquartile range: the lower bound corresponds to the 25th percentile, the middle line to the 50th percentile (median), and the upper bound to the 75th percentile. *, for the B cell epitopes group, the 25th, 50th, and 75th percentiles are all 0% due to the sparse mutation distribution (most samples had no mutations in B cell epitopes). The first non-zero value emerges at approximately the 82nd percentile, thus resulting in a boxplot with only visible whiskers (no distinct box). (A) Comparison of mutation rates between immune and nonimmune epitopes. (B) Comparison of mutation rates among B-cell, Th-cell and CTL epitopes. CTL, cytotoxic T lymphocyte; HBV, hepatitis B virus.

Discussion

HBV genotype distributions exhibit distinct geographic and ethnic differences. For example, genotype D predominates in Southern Europe, North Africa, and entire Western, Northern, and Central Asia (including Mongolia), whereas genotypes B and C are endemic to Asia (24-29). In China, HBV genotypes also present geographical and ethnic distributions. Genotypes B, C and D are predominant in China, with genotype C dominating the north and east, genotype B more common in the central and southwest, and genotype D and C/D recombinants prevalent in the northwest (26,30). Several studies have demonstrated that HBV genotypes can influence HBV formation through distinct virological characteristics and pathogenic potentials. For example, genotype C isolates have been documented to exhibit significantly higher infectivity compared to genotype B, and genotypes B2 and F1b demonstrate increased covalently closed circular DNA (cccDNA) levels, a critical biomarker of viral persistence (31,32). Additionally, the expression and secretion of viral antigens like HBsAg and HBeAg differ markedly among genotypes, which may contribute to variations in disease progression and immune response (31). Genotype-specific mutations, such as those in the precore and basal core promoter regions, also influence viral replication and antigen expression, further affecting clinical outcomes (33,34). The incidence of clinically relevant mutations—including those linked to immune evasion, antiviral drug resistance, and hepatocellular carcinoma—exhibits strong genotype dependency and varies significantly across geographic regions (34,35). In this study, phylogenetic analysis (Figure 1) classified 81 (75.70%) strains as genotype B, 25 (23.36%) as genotype C, and 1 (0.93%) as genotype D; it also showed that the HBV strains in this study are most closely related to those from China and Japan, accounting for more than 70% of the total. Specifically, among genotype B strains, the majority of our samples cluster closely with two reference strains of Chinese origin, namely B-AY217370-China and B-AY217365-China. However, no statistically significant differences were observed in mutations of surface protein different immune between genotype B and genotype C (P=0.18–0.81) (Table 4).

This study aimed to characterize HBV S protein mutations in voluntary blood donors. The majority of amino acid alterations detected in different epitopes were localized to four distinct regions: CTL domains at positions 28–51 and 206–215, and nonimmune domains at positions 52–79 and 198–205. Among 384 mutations within HBsAg immune epitopes, 207 (53.91%) were located within T-cell domains, which contain CTL domains (37.50%) (Table 2). Notably, the mutation rate within the CTL epitope domain was markedly elevated compared to the B-cell (P<0.001) and Th-cell (P=0.002) epitope domains (Figure 3B), suggesting concentrated immune selection pressure at hotspot residues. Theoretically, mutations within T-cell epitopes could potentially modulate the antiHBs profile via modified interplay between CD4⁺ Th-cells and B-cells (36,37). A robust T-cell response is fundamentally essential for the generation of sufficient antibodies subsequent to HBV infection and immunization. Zhang’s experiments have proved the fact that adaptive immune response, facilitated by MHC class I-restricted CTL, plays a critical role in controlling HBV infection (38). Furthermore, a German study has shown that immune escape mutations (IEMs) within CD8⁺ T-cell epitopes are widespread in HBV and constitute a critical determinant of immune control failure (39). Studies have discovered new amino acid substitutions in class I/II–restricted T cell epitopes of HBsAg, including C48G, V96A, L175S, G185E, and V190A, demonstrating that HBV can evade T cell-mediated responses, particularly in patients with HBV reactivation under immunosuppression (40). Three novel mutations (S171F, S174N and Q181R) at the site of the MHC class-restricted CTL epitopes of HBsAg in patients suffering from chronic hepatitis B were found in China, implying that these mutations could potentially CTL dysfunction, contributing to chronic infections (41). In conclusion, numerous mutations both upstream and downstream of MHR were identified to be situated within the recognized T cell epitopes of HBsAg. These mutations result in amino acid modifications, which could potentially lead to T-cell non-responsiveness or dysregulated T-cell activation, and could be accountable for vaccine breakthrough infection and HBsAg undetectability.

In the present study, distinct characteristics regarding the distribution and mutational profiles of S protein were revealed. Mutations within HBsAg immune epitopes accounted for a higher proportion of the total mutation count compared to those within nonimmune epitope domains (61.46% to 38.54%); however, their mutation rate remained significantly lower than that in nonimmune epitope (P=0.003; Figure 3A). This observation suggests that the potential impact of mutations in nonimmune epitopes on HBV infection may have been previously underestimated, possibly through interactions with immune epitopes. Previous literature has indicated that mutations in the N-terminal region (aa 1–98) and the C-terminal region (aa 170–226) could influence T-cell epitopes and facilitate immune evasion, although the underlying mechanism of this process remains unclear. Notably, many reported mutations in patients with OBI occur in nonimmune regions. Previous studies by our research group have demonstrated that the E2G/A/V/D mutation can result in the production of a truncated N-terminal S protein, leading to impaired HBsAg secretion (42,43). These mutations allow HBV to evade serological testing and sustain persistent infection, thereby supporting our hypothesis that mutations in nonimmune epitopes are not merely meaningless variations. OBI—characterized by undetectable HBsAg but ongoing HBV DNA replication—involves mutations in nonimmune epitopes as a viral adaptation to the host environment, and this phenomenon occurs in both dominant and recessive infections. Variations in the final phenotype may stem from diverse evolutionary adaptation mechanisms. However, a majority of recent studies on HBV mutations have focused on the MHR, particularly the “a” determinant, among which mutations such as G145R, D144A/N/S/H, and T116N have been the most frequently reported (10). In contrast, there is a paucity of reports regarding mutations in nonimmune epitopes. This lack of data underscores the necessity for more comprehensive research to elucidate the functional significance of mutations in nonimmune regions.

The mutation distribution of immune epitopes in the HBV S protein displayed a notable pattern: the median number of mutations was 0 or 1 (Table 4). This observation suggests that the vast majority of HBV blood donors exhibit no more than one mutation in these immune epitopes, with only a minute fraction displaying substantially elevated mutation rates. Our analysis attributes the limited mutations in the immune epitopes of the HBV S protein among most blood donors to strong purifying selection. Specifically, these epitopes are functionally conserved to preserve viral antigenicity, replication capability, and structural stability—findings that align with previous research (44,45). Conversely, a distinct subset of blood donors exhibits notably elevated mutation frequencies, possibly stemming from HBV’s immune evasion tactics and mutation accumulation over prolonged infection periods. This phenomenon may also be influenced by the host’s HLA genotype polymorphism. Consistent observations across studies in diverse populations (East Asian, Greek, Turkish, Han Chinese) have shown that specific HLA alleles correlate with elevated risks of chronic HBV infection and greater viral sequence diversity. In contrast, other HLA alleles exhibit protective properties or aid in viral clearance (46-49). Exploring the relationship between blood donors’ HLA genotypes and epitope mutation counts can enhance our comprehension of how an individual’s immune background influences viral mutation selection, warranting further investigation. Additionally, a noteworthy discovery reveals a significant association between HBV DNA and ALT levels and the mutation pattern (mostly low mutations, with a minority of high mutations in immune epitopes). This finding reinforces that immune epitope mutations in HBV regulate viral replication (reflected by HBV DNA levels) and hepatic inflammation (indicated by ALT levels).

Khedive’s research on the Iranian population with chronic HBV infection revealed that amino acid mutations were predominantly concentrated on the T-cell epitopes of surface proteins, accounting for 76.23%, among which CTL epitopes contributed 48.76% (21). In Sayad’s study, 94.9% of amino acid mutations were detected on T-cell epitopes, and 63.1% on CTL epitopes (46). These percentages were numerically higher than the corresponding results obtained in our study (Table 2). We hypothesized that this inconsistency could be attributed to two key aspects. First, the study populations differed significantly. Iranian and Chinese populations manifest contrasting characteristics concerning HBV infection, with differing predominant genotypes. While genotypes B and C are prevalent in our study, genotype D dominates in Iran (21). These demographic, genetic, and environmental factors associated with HBV exposure could influence the outcomes observed. Second, the research focuses varied substantially. The Iranian study exclusively concentrated on chronic hepatitis B (CHB) patients undergoing prolonged antiviral treatment. In contrast, our study encompassed HBsAg⁺/HBV⁺ blood donors, a heterogeneous group that potentially included individuals beyond those with CHB, such as asymptomatic carriers who have never been treated. Research reports indicated that a high prevalence of both drug resistance mutations (DRMs) (up to 38%) and IEMs (up to 43%) in patients with chronic hepatitis B who have undergone antiviral therapy (47,48). These mutations were predominantly located within immune epitopes. Meanwhile, a study in Korea founded that amino acid substitutions within the CTL epitope (P<0.020), CD4⁺ T-cell epitope (P<0.027), and B-cell epitope (P<0.029) were significantly more frequent in liver cirrhosis patients than in chronic hepatitis patients, but not in hepatocellular carcinoma patients, indicating that mutations within immune epitopes were also significantly correlated with disease progression (49). Thus, we will incorporate long-term follow-up and comprehensively acquire the clinical data of HBV-infected blood donors in the future, so as to clarify their infection status.

Beyond this, it should also be noted that our study is not without certain limitations. First, our sample size may not be sufficiently large. Future research should involve collaboration with multiple centers to expand the sample size, thereby enhancing statistical power and further validating our current findings. Second, we utilized a consensus synthesized from our own sequences as the reference sequence for analyzing mutation patterns, rather than directly comparing it to publicly available, genotype-standardized reference sequences. This approach offers the advantage of representing the most common nucleotides at each position, minimizing the influence of rare or sample-specific mutations and providing a standardized baseline for mutation analysis, functional studies, and molecular epidemiology. Consequently, this method allows us to more accurately capture region-specific mutation patterns within the local HBV population under investigation, thereby minimizing the introduction of additional mutations associated with a broader geographical or epidemiological HBV reference strain. Although sample comparison with sample-specific consensus sequences is a widely adopted approach in current sequence comparison studies (42,45,50-54), direct comparison with publicly available genotype-standardized reference sequences also holds significant value. In future studies, we may consider adopting a dual-reference strategy. This strategy involves conducting comparisons not only with consensus sequences derived from our own sequences but also with standardized, genotype-specific reference sequences (e.g., reference sequences from the NCBI GenBank). This approach can facilitate the comprehensive identification of potential differences and enhance our understanding of HBV mutations.

Conclusions

In conclusion, HBV genotypes B and C predominated among blood donors in Guangzhou, China. Among HBV-infected donors, the mutations in HBV S protein immune epitopes accounted for a higher proportion of the total mutation count than those in nonimmune epitopes, especially in the CTL epitopes, indicating that there might be narrow and concentrated immune selection pressure at hot spots. Nonetheless, our findings also revealed a higher mutation rate in the nonimmune epitopes than in the immune epitopes, underscoring the significance of mutations in the nonimmune epitopes, which may play a non-negligible role in the process of HBV adapting to the host. Our findings further suggest that broadening the detection range of HBV mutations to encompass nonimmune epitopes in blood screening, coupled with designing future vaccines targeting conserved nonimmune regions, may offer a practical approach to address the growing threat of immune escape variants.

While our research has limitations and areas for enhancement, it represents the first comprehensive analysis of HBV surface protein mutations at the immune epitope and nonimmune epitope domain levels in blood donors from Guangzhou. These findings establish a critical foundation for molecular biology research on HBV evolution and immune evasion in this geographic region and provide important guidance for managing transfusion-mediated HBV transmission.

Acknowledgments

None.

Footnote

Data Sharing Statement: Available at https://aob.amegroups.com/article/view/10.21037/aob-25-34/dss

Peer Review File: Available at https://aob.amegroups.com/article/view/10.21037/aob-25-34/prf

Funding: This work was supported by the Medical Scientific Research Foundation of Guangdong Province, China (No. A2024391), Science and Technology Planning Project of Guangzhou, China (No. 2024A03J0447), and the Key Medical Disciplines and Specialties Program of Guangzhou (No. 2025-2027).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://aob.amegroups.com/article/view/10.21037/aob-25-34/coif). H.L. serves as the Editor-in-Chief of Annals of Blood from August 2024 to July 2029. W.G. and H.W. report a patent of “A Method for Nucleic Acid Extraction with Large Volume and High Sensitivity” [Patent No. ZL202111372169.6, China; Issued on (10/27/2023)]. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of Guangzhou Blood Center (No. Guangzhou Blood Center [2023] No. 017) and informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Asandem DA, Segbefia SP, Kusi KA, et al. Hepatitis B Virus Infection: A Mini Review. Viruses 2024;16:724. [Crossref] [PubMed]
2. Vallet-Pichard A, Pol S. Review article: immunisation against hepatitis B virus infection and the prevention of hepatocellular carcinoma. Aliment Pharmacol Ther 2021;53:1166-82. [Crossref] [PubMed]
3. GBD 2019 Hepatitis B Collaborators. Global, regional, and national burden of hepatitis B, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Gastroenterol Hepatol 2022;7:796-829. [Crossref] [PubMed]
4. Liu Z, Lin C, Mao X, et al. Changing prevalence of chronic hepatitis B virus infection in China between 1973 and 2021: a systematic literature review and meta-analysis of 3740 studies and 231 million people. Gut 2023;72:2354-63. [Crossref] [PubMed]
5. Yan R, Sun M, Yang H, et al. 2024 latest report on hepatitis B virus epidemiology in China: current status, changing trajectory, and challenges. Hepatobiliary Surg Nutr 2025;14:66-77. [Crossref] [PubMed]
6. Shan S, Zhao X, Jia J. Comprehensive approach to controlling chronic hepatitis B in China. Clin Mol Hepatol 2024;30:135-43. [Crossref] [PubMed]
7. Xu Y, Xia C, Li H, et al. Survey of hepatitis B virus infection for liver cancer screening in China: A population-based, cross-sectional study. Chin Med J (Engl) 2024;137:1414-20. [Crossref] [PubMed]
8. Venkatakrishnan B, Zlotnick A. The Structural Biology of Hepatitis B Virus: Form and Function. Annu Rev Virol 2016;3:429-51. [Crossref] [PubMed]
9. Chen P, Gan Y, Han N, et al. Computational evolutionary analysis of the overlapped surface (S) and polymerase (P) region in hepatitis B virus indicates the spacer domain in P is crucial for survival. PLoS One 2013;8:e60098. [Crossref] [PubMed]
10. Lazarevic I, Banko A, Miljanovic D, et al. Immune-Escape Hepatitis B Virus Mutations Associated with Viral Reactivation upon Immunosuppression. Viruses 2019;11:778. [Crossref] [PubMed]
11. Sobajo OA, Oguzie JU, Adegboyega B, et al. Detection of Immune Escape and Basal Core Promoter/Precore Gene Mutations in Hepatitis B Virus Isolated from Asymptomatic Hospital Attendees in Two Southwestern States in Nigeria. Viruses 2023;15:2188. [Crossref] [PubMed]
12. Piermatteo L, D'Anna S, Bertoli A, et al. Unexpected rise in the circulation of complex HBV variants enriched of HBsAg vaccine-escape mutations in HBV genotype-D: potential impact on HBsAg detection/quantification and vaccination strategies. Emerg Microbes Infect 2023;12:2219347. [Crossref] [PubMed]
13. El-Mowafy M, Elegezy M, El-Mesery M, et al. Characterization of a breakthrough vaccine escape strain associated with overt hepatitis B virus infection. Virus Genes 2024;60:235-9. [Crossref] [PubMed]
14. Shoukry NH, Walker CM. T cell responses during HBV and HCV infections: similar but not quite the same? Curr Opin Virol 2021;51:80-6. [Crossref] [PubMed]
15. Naderi M, Hosseini SM, Behnampour N, et al. Mutations in the S gene of hepatitis B virus in three generations of patients with chronic hepatitis B. Virus Genes 2023;59:662-9. [Crossref] [PubMed]
16. Candotti D, Grabarczyk P, Ghiazza P, et al. Characterization of occult hepatitis B virus from blood donors carrying genotype A2 or genotype D strains. J Hepatol 2008;49:537-47. [Crossref] [PubMed]
17. Zahn A, Li C, Danso K, et al. Molecular characterization of occult hepatitis B virus in genotype E-infected subjects. J Gen Virol 2008;89:409-18. [Crossref] [PubMed]
18. Ebrahimi F, Oskoee MA, Baghi HB, et al. Phylogenetic and immune epitope analysis of hepatitis B surface antigen in chronic carriers from Tabriz, Northwest of Iran. ImmunoAnalysis 2022;2:7.
19. Tarafdar S, Virata ML, Yan H, et al. Multiple epitopes of hepatitis B virus surface antigen targeted by human plasma-derived immunoglobulins coincide with clinically observed escape mutations. J Med Virol 2022;94:649-58. [Crossref] [PubMed]
20. Mobini S, Chizari M, Mafakher L, et al. Computational Design of a Novel VLP-Based Vaccine for Hepatitis B Virus. Front Immunol 2020;11:2074. [Crossref] [PubMed]
21. Khedive A, Norouzi M, Ramezani F, et al. Hepatitis B virus surface protein mutations clustered mainly in CTL immune epitopes in chronic carriers: results of an Iranian nationwide study. J Viral Hepat 2013;20:494-501. [Crossref] [PubMed]
22. Norder H, Couroucé AM, Magnius LO. Molecular basis of hepatitis B virus serotype variations within the four major subtypes. J Gen Virol 1992;73:3141-5. [Crossref] [PubMed]
23. Purdy MA, Talekar G, Swenson P, et al. A new algorithm for deduction of hepatitis B surface antigen subtype determinants from the amino acid sequence. Intervirology 2007;50:45-51. [Crossref] [PubMed]
24. Trastoy R, Gonzalez-Alba JM, Soriano V, et al. The unexpected high prevalence of HBV subgenotype D4 in patients with chronic hepatitis B in Galicia, a northwestern Spanish region, reflects strong links with Latin America. J Clin Virol 2022;153:105195. [Crossref] [PubMed]
25. Su QD, Zhang S, Wang F, et al. Epidemiological distribution of hepatitis B virus genotypes in 1-29-year-olds in the mainland of China. Vaccine 2020;38:8238-46. [Crossref] [PubMed]
26. Dong Z, Li JR, Zhao ZX, et al. Molecular epidemiology of hepatitis B virus genotypes and subgenotypes in ethnic minority populations, Yunnan province, China. Epidemiol Infect 2021;150:e11. [Crossref] [PubMed]
27. Kafeero HM, Ndagire D, Ocama P, et al. Mapping hepatitis B virus genotypes on the African continent from 1997 to 2021: a systematic review with meta-analysis. Sci Rep 2023;13:5723. [Crossref] [PubMed]
28. Liu Z, Zhang Y, Xu M, et al. Distribution of hepatitis B virus genotypes and subgenotypes: A meta-analysis. Medicine (Baltimore) 2021;100:e27941. [Crossref] [PubMed]
29. Tian Q, Jia J. Hepatitis B virus genotypes: epidemiological and clinical relevance in Asia. Hepatol Int 2016;10:854-60. [Crossref] [PubMed]
30. Zhang N, Zhang S, Wang F, et al. Epidemiological distribution of hepatitis B virus genotypes in acute hepatitis B cases in China, 2015-2017. Zhonghua Liu Xing Bing Xue Za Zhi 2022;43:865-70. [Crossref] [PubMed]
31. Elizalde MM, Tadey L, Mammana L, et al. Biological Characterization of Hepatitis B virus Genotypes: Their Role in Viral Replication and Antigen Expression. Front Microbiol 2021;12:758613. [Crossref] [PubMed]
32. Liu T, Liu A, Liu Y, et al. In vitro investigation of HBV clinical isolates from Chinese patients reveals that genotype C isolates possess higher infectivity than genotype B isolates. Virol Sin 2022;37:398-407. [Crossref] [PubMed]
33. Lau DTY, Ganova-Raeva L, Wang J, et al. Precore and Basal Core Promoter Hepatitis B Virus (HBV) Variants Are Present From a Young Age and Differ Across HBV Genotypes. Hepatology 2021;73:1637-51. [Crossref] [PubMed]
34. Araujo NM, Teles SA, Spitz N. Comprehensive Analysis of Clinically Significant Hepatitis B Virus Mutations in Relation to Genotype, Subgenotype and Geographic Region. Front Microbiol 2020;11:616023. [Crossref] [PubMed]
35. Assefa A, Getie M, Getie B, et al. Molecular epidemiology of hepatitis B virus (HBV) in Ethiopia: A review article. Infect Genet Evol 2024;122:105618. [Crossref] [PubMed]
36. Drost F, Dorigatti E, Straub A, et al. Predicting T cell receptor functionality against mutant epitopes. Cell Genom 2024;4:100634. [Crossref] [PubMed]
37. Wang Y, Xiao X, Chen S, et al. The Impact of HBV Quasispecies Features on Immune Status in HBsAg+/HBsAb+ Patients With HBV Genotype C Using Next-Generation Sequencing. Front Immunol 2021;12:775461. [Crossref] [PubMed]
38. Zhang X, Kraft A, Broering R, et al. Preclinical development of TLR ligands as drugs for the treatment of chronic viral infections. Expert Opin Drug Discov 2012;7:597-611. [Crossref] [PubMed]
39. Schwarz T, Ptok J, Damagnez M, et al. HBV shows different levels of adaptation to HLA class I-associated selection pressure correlating with markers of replication. J Hepatol 2025;82:805-15. [Crossref] [PubMed]
40. Salpini R, Colagrossi L, Bellocchi MC, et al. Hepatitis B surface antigen genetic elements critical for immune escape correlate with hepatitis B virus reactivation upon immunosuppression. Hepatology 2015;61:823-33. [Crossref] [PubMed]
41. Ye Q, Shang SQ, Li W. A new vaccine escape mutant of hepatitis B virus causes occult infection. Hum Vaccin Immunother 2015;11:407-10. [Crossref] [PubMed]
42. Wang H, Liao F, Xie J, et al. E2 Site Mutations in S Protein Strongly Affect Hepatitis B Surface Antigen Detection in the Occult Hepatitis B Virus. Front Microbiol 2021;12:664833. [Crossref] [PubMed]
43. Wang H, Wang M, Huang J, et al. Novel hepatitis B virus surface antigen mutations associated with occult genotype B hepatitis B virus infection affect HBsAg detection. J Viral Hepat 2020;27:915-21. [Crossref] [PubMed]
44. Maman Y, Blancher A, Benichou J, et al. Immune-induced evolutionary selection focused on a single reading frame in overlapping hepatitis B virus proteins. J Virol 2011;85:4558-66. [Crossref] [PubMed]
45. Wang Q, Michailidis E, Yu Y, et al. A Combination of Human Broadly Neutralizing Antibodies against Hepatitis B Virus HBsAg with Distinct Epitopes Suppresses Escape Mutations. Cell Host Microbe 2020;28:335-349.e6. [Crossref] [PubMed]
46. Sayad B, Anvari FA, Alavian SM, et al. Correlation of Hepatitis B surface antigen mutations with clinical status of the chronically infected patients from Kermanshah, West of Iran. Minerva Gastroenterol Dietol 2012;58:9-18.
47. De Francesco MA, Gargiulo F, Dello Iaco F, et al. Immune Escape and Drug Resistance Mutations in Patients with Hepatitis B Virus Infection: Clinical and Epidemiological Implications. Life (Basel) 2025;15:672. [Crossref] [PubMed]
48. He C, Wu X, You Z, et al. Evaluation of genotype characteristics and drug resistance mutations in patients with chronic hepatitis B. Sci Rep 2024;14:27575. [Crossref] [PubMed]
49. Lyoo KS, Hong SW, Song MJ, et al. Subgenotype and genetic variability in the precore/core regions of hepatitis B virus in Korean patients with chronic liver disease. Intervirology 2011;54:333-8. [Crossref] [PubMed]
50. Duchen D, Clipman SJ, Vergara C, et al. A hepatitis B virus (HBV) sequence variation graph improves alignment and sample-specific consensus sequence construction. PLoS One 2024;19:e0301069. [Crossref] [PubMed]
51. DuchenDClipmanSVergaraCA hepatitis B virus (HBV) sequence variation graph improves sequence alignment and sample-specific consensus sequence construction for genetic analysis of HBV. Preprint bioRxiv 2023;2023.01.11.523611. 38669259
52. Liao F, Xie J, Du R, et al. Replication and Expression of the Consensus Genome of Hepatitis B Virus Genotype C from the Chinese Population. Viruses 2023;15:2302. [Crossref] [PubMed]
53. Liu WC, Lin CP, Cheng CP, et al. Aligning to the sample-specific reference sequence to optimize the accuracy of next-generation sequencing analysis for hepatitis B virus. Hepatol Int 2016;10:147-57. [Crossref] [PubMed]
54. Jin X, Cai Q, Zhang Z, et al. Establishment of reference sequences of hepatitis B virus genotype B subgenotypes. Arch Biol Sci 2020;72:483-90.