Discovery and structural characterization of newly identified mutations in the HBx gene of chronic HBV patients

Abstract

HBV infection remains a major cause of chronic liver disease and hepatocellular carcinoma worldwide. HBx is a key regulatory protein involved in viral persistence and host–virus interactions, yet its sequence variability in Middle Eastern populations remains insufficiently characterized. In this study, the HBx region was screened in 50 Iranian patients with chronic HBV infection, and four representative samples with distinct HRM profiles were selected for sequencing. Several newly identified substitutions were detected, including two glycine substitutions (G37A and G73V) and one proline substitution (P32H), while G43D corresponded to a previously reported variant. Among these, Gly73 variants were recurrent across multiple samples. Qualitative structural modeling of full-length HBx suggested that these substitutions may contribute to subtle local conformational changes near regulatory regions; however, these observations remain preliminary and require experimental validation. Clinical and biochemical parameters showed heterogeneous patterns across cases, with Gly73 variants detected in patients with higher viral loads, although no statistically significant associations were observed due to the small sample size. All sequences belonged to genotype D. Overall, this exploratory analysis expands the existing catalog of HBx variability in a Middle Eastern cohort and highlights several newly identified substitutions that warrant further investigation in larger functional studies.

Introduction

Hepatitis B virus (HBV) infection remains a major global health concern, with nearly 300 million people living with chronic infection worldwide¹. The HBV X protein (HBx) plays a pivotal role in viral replication, modulation of host signaling pathways, and the transition from chronic infection to hepatocellular carcinoma (HCC)². HBx is a multifunctional regulatory protein involved in transcriptional activation, signal transduction, and inhibition of apoptosis, thereby facilitating viral persistence and promoting liver disease progression³. Genetic variability within the HBx gene has gained increasing attention, as specific mutations can markedly influence protein function and have been associated with disease severity, therapeutic response, and hepatocarcinogenesis⁴. Mutations in key functional domains of HBx may enhance viral oncogenicity by altering interactions with host factors, dysregulating transcription, or modulating cell survival pathways⁵. Consequently, understanding the spectrum of HBx mutations in chronic HBV patients is crucial for elucidating mechanisms of viral persistence and identifying novel targets for therapeutic intervention. Advances in molecular diagnostics and three-dimensional (3D) structural modeling have enabled more precise evaluations of how individual mutations reshape HBx structure and mechanistic activity⁶. These structural insights are essential for predicting functional consequences and for guiding the development of targeted therapeutic strategies. Despite growing evidence linking HBx mutations to clinical outcomes, comprehensive analyses of HBx variability in Middle Eastern populations—particularly within the predominantly genotype D–infected Iranian cohort—remain limited. Previous studies in Iranian patients (Kerman city) have reported mutations in the Enhancer II/HBx region of HBV, highlighting their potential impact on viral regulation and pathogenesis⁷. Therefore, this study aimed to characterize the mutational profile of the HBx gene in chronic HBV patients from Kerman, Iran, and to employ 3D structural modeling to elucidate the potential structural and functional impacts of the identified variants, with a focus on their implications for disease progression.

Materials and methods

Patient samples

Fifty patients with chronic hepatitis B virus (HBV) infection were recruited based on PCR-confirmed diagnosis. Chronic HBV infection was defined as persistent HBsAg positivity for more than six months. Written informed consent was obtained from all participants, and the study protocol was approved by the Institutional Ethics Committee in accordance with the Declaration of Helsinki. From these patients, serum samples were collected for molecular analysis. Clinical data for these cases included age, sex, HBV viral load, liver enzyme levels alkaline phosphatase (ALK-P), aspartate aminotransferase (SGOT), alanine aminotransferase (SGPT), and hepatitis B e antigen (HBeAg) status. HBeAg is a viral protein indicative of active viral replication and infectivity in HBV patients. These parameters were evaluated to explore potential associations between glycine-related HBx mutations and indicators of disease progression.

DNA extraction

Viral DNA was extracted from 200 µL of each serum sample using the QIAamp DNA Mini Kit (Qiagen, Germany) following the manufacturer’s instructions. The concentration and purity of the extracted DNA were determined using a NanoDrop spectrophotometer (Thermo Fisher Scientific, USA).

PCR amplification and HRM screening

All 50 serum samples were initially screened for HBx genetic alterations via PCR amplification coupled with HRM analysis. The HBx gene was amplified using two sets of primers: one for real-time PCR detection and one for full-length sequencing. The PCR mixture (25 µL total volume) contained 50 ng DNA template, 1× PCR buffer, 2 mM MgCl₂, 200 µM dNTPs, 0.4 µM of each primer, and 1 U of Taq DNA polymerase (CinnaGen, Iran). Primer sequences and amplicon sizes are summarized in Table 1. Primer specificity was confirmed in silico using Primer-BLAST (NCBI). HRM analysis was conducted using a Rotor-Gene Q system (Qiagen, Germany) and SYBR Green I dye. Melting curves were analyzed with Rotor-Gene software to detect potential sequence variations. For reference, the HBx genotype D1 sequence (GenBank accession: U95551.1) was included in the comparative analysis. Reactions were performed in a (Name of Real-Time PCR System, e.g., Rotor-Gene Q 5plex HRM, Qiagen) using a total volume of 20 µL containing 10 µL HRM master mix (e.g., Type-it HRM Kit, Qiagen), 0.5 µM of each primer, and 50 ng of genomic DNA. The thermal cycling protocol included an initial denaturation at 95 °C for 5 min, followed by 40 cycles of 95 °C for 10 s, annealing at 60 °C for 20 s, and extension at 72 °C for 20 s. Following PCR amplification, melting analysis was performed by gradually increasing the temperature from 75 °C to 90 °C at a ramp rate of 0.1 °C/s, with continuous fluorescence acquisition. The melting profiles were normalized and the derivative plots (-dF/dT vs. temperature) were generated to identify distinct genotypic patterns.

Table 1.

Primer sequences used for HBx gene detection and sequencing.

Name	Real-time PCR primers	Location	Product size (bp)
HBXF:	GTCTGTGCCTTCTCATCTG	265–284	168 bp*
HBXR:	GTTCACGGTGGTCTCCAT	433 − 415
Name	Sequencing Primers	Location	506 bp
HBXSF:	ATGGCTGCTAGGCTGTGCT	−19-0
HBXSR:	GGCAGAGGTGAAAAAGTTGC	487 − 465

*The 168 bp product was used for initial HBx detection; the 506 bp product covered the full-length coding sequence and was used for mutation analysis

Sanger sequencing and mutation analysis

PCR products showing abnormal melting profiles were purified using a PCR purification kit (Qiagen, Germany) and subjected to direct Sanger sequencing on an ABI 3500 Genetic Analyzer (Applied Biosystems, USA). Sequences were aligned with the HBV reference genome (GenBank accession number: NC_003977) using MEGA X software. Nucleotide and amino acid variations, including point mutations, insertions, and deletions, were recorded.

Phylogenetic analysis

Multiple sequence alignment of the six HBx sequences with representative HBV genotypes retrieved from GenBank was performed using ClustalW. A phylogenetic tree was constructed using the Maximum Likelihood (ML) method with the Tamura-Nei model and 1,000 bootstrap replications in MEGA X software.

3D Structural Modeling of HBx Protein

The three-dimensional structures of both reference and mutant HBx proteins were generated using SWISS-MODEL (https://swissmodel.expasy.org/). The quality of predicted models was validated by GMQE and QMEAN scores. Structural visualization and comparison were performed using UCSF Chimera software. Conformational alterations, particularly within the C-terminal transactivation domain, were assessed.

Protein–Protein interaction and pathway analysis

To explore the biological relevance of the observed mutations, protein–protein interaction (PPI) networks were analyzed using the STRING database (https://string-db.org/) with a confidence score cutoff of 0.7. Network visualization and pathway enrichment analysis were conducted using Cytoscape software (v3.10). Specific focus was placed on HBx interactions with p53, DDB1, and signaling pathways related to cell cycle regulation, apoptosis, and hepatocarcinogenesis.

Results

Initial mutation screening of the HBx gene was performed using High Resolution Melting (HRM) analysis. Among the 50 initial HBV patient samples, four samples were selected for detailed mutational analysis due to their distinct HRM profiles, which differed from the majority of samples. These representative samples exhibited unique melting patterns indicative of potentially novel mutations, justifying their selection for further study. Based on distinct HRM profile patterns, four representative samples—designated Kerman_3, Kerman_15, Kerman_17, and Kerman_19 were selected for in-depth clinical and genetic investigation. Clinical characteristics of these patients are summarized in Table 2. Patient Kerman_3 exhibited the highest HBV viral load (5600 IU/mL) along with markedly elevated liver enzymes (ALK-P: 552 U/L, SGOT: 251 U/L, SGPT: 265 U/L) and positive HBeAg status. The remaining patients showed lower viral loads (450–829 IU/mL), moderate elevations in liver enzymes, and negative HBeAg status.

Table 2.

Clinical characteristics of four chronic HBV-infected patients harboring glycine-related mutations in the HBx gene.

Patient ID	Age	Sex	HBV Viral Load (IU/mL)	ALK-P (U/L)	SGOT (U/L)	SGPT (U/L)	HBeAg Status
Kerman_3	52	Male	5600	552	251	265	Positive
Kerman_15	35	Female	450	110	58	61	Negative
Kerman_17	36	Male	650	65	87	85	Negative
Kerman_19	46	Male	829	160	96	125	Negative

Normal reference ranges: SGPT (0–40 U/L), SGOT (0–35 U/L), ALK-P (44–147 U/L), HBV DNA (< 10³ IU/mL)

Initial HRM screening and selection of representative samples

All 50 HBV-positive patient samples were initially examined using High-Resolution Melting (HRM) analysis as a rapid mutation-screening approach for the mutation of HBx region. Most samples displayed melting profiles consistent with the wild-type reference pattern. However, four samples (Kerman_3, Kerman_15, Kerman_17, and Kerman_19) showed distinct abnormal HRM curves, characterized by shifted melting peaks and altered derivative profiles, suggesting the presence of nucleotide substitutions. These aberrant HRM patterns (Fig. 1) were reproducible and clearly separated from the HRM cluster of wild-type samples. Based on these observations, these four samples were selected for downstream Sanger sequencing and structural analyses, as they represented the most prominent and informative mutation-carrying profiles within the cohort. This selection approach ensured that the samples used for detailed characterization reflected true HRM-defined outliers rather than random cases. The remaining 46 samples, which showed wild-type HRM behavior, were not expected to contain significant sequence variation and were therefore not subjected to further sequencing.

Fig. 1.

High-resolution melting (HRM) analysis of the HBx gene. Four patient samples (Kerman_3, Kerman_15, Kerman_17, and Kerman_19) showed distinct melting profiles compared with the reference, indicating nucleotide substitutions or partial deletions.

HRM profiling of HBx variants

The HRM analysis revealed distinct melting curve profiles for the four sequenced samples (Kerman_3, Kerman_15, Kerman_17, and Kerman_19). As shown in Fig. 1, each sample exhibited a characteristic melting peak, with Kerman_15, Kerman_17, and Kerman_19 displaying a shift in melting temperature (Tm) compared to Kerman_3, which is consistent with the reference sequence. These peak shifts suggest the presence of nucleotide changes—either point mutations or partial deletions—in the HBx region. The observed variations in melting profiles were later confirmed by direct Sanger sequencing.

Multiple sequence alignment of the four HBx sequences obtained from chronic HBV patients in Kerman with the reference sequence (D1, U95551.1) revealed several nucleotide variations. Among them, only novel and potentially functional mutations within the coding region of the HBx gene were highlighted in this study. Previously reported and recurrent polymorphisms, particularly within enhancer regions, were intentionally excluded from the main analysis to maintain the focus on novel variations with possible biological relevance.

The HBx nucleotide sequences generated and analysed during the current study have been deposited in the GenBank repository under accession numbers MT986033.1, MT986035.1, MT986036.1, and MT986037.1 (https://www.ncbi.nlm.nih.gov/nuccore/). Only newly observed or biologically important variations are presented, while previously reported enhancer mutations and recurrent polymorphisms were excluded. In total, five novel nonsynonymous mutations and one synonymous mutation were identified across the four patient samples (Table 3). These included substitutions such as Gly→Ala, Gly→Val, and Pro→His which are located in the N-terminal regulatory domain of HBx and are predicted to affect protein conformation, transcriptional regulation, and oncogenic potential. Notably, mutations Gly73Val (observed in samples Kerman_17 and Kerman_19) and Gly73Val (sample Kerman_3) occurred within the transactivation domain, a critical region for HBx-mediated transcriptional regulation, suggesting their potential involvement in hepatocarcinogenesis. The synonymous mutation at position 312 (T→C) was also retained in the analysis, as it may serve as a genetic marker despite not altering the encoded amino acid. Collectively, these results suggest that the novel nonsynonymous substitutions, especially those in the C-terminal portion of HBx, may play an important role in viral persistence and disease progression, while excluding well-documented enhancer polymorphisms ensures the novelty of our findings.

Table 3.

Summary of novel and functionally relevant HBx mutations identified in four chronic HBV patient samples from Kerman compared with the D1 reference sequence (U95551.1).

Sample ID	Nt* position	Nt* change	Aa* position	Aa change	Mutation type	Transition/Transversion	Predicted functional impact	Reported/Novel	Gene accession number
Kerman_3	217	G → T	73	Gly → Val	Nonsynonymous	Transversion	May alter protein secondary structure and HBx interactions	Novel	MT986033.1
Kerman_15	109	G → C	37	Gly → Ala	Nonsynonymous	Transversion	Potential effect on helix stability and transcription factor binding	Novel	MT986035.1
Kerman_15	128	G → A	43	Gly → Asp	Nonsynonymous	Transition	Possible impact on HBx protein stability	Reported	MT986035.1
Kerman_17	96	C → A	32	Pro → His	Nonsynonymous	Transversion	Structural alteration in the regulatory domain of HBx	Novel	MT986036.1
Kerman_17	217	G → T	73	Gly → Val	Nonsynonymous	Transversion	Located in the transactivation domain, may contribute to carcinogenesis	Novel	MT986036.1
Kerman_19	217	G → T	73	Gly → Val	Nonsynonymous	Transversion	Similar to 17_Kerman, associated with disease severity	Novel	MT986037.1
Kerman_19	312	T → C	104	— (synonymous)	Synonymous	Transition	No amino acid change, but may serve as a genetic marker	—	MT986037.1

^*Nucleotide, ^*Amino acid.

The HBx protein is composed of an N-terminal regulatory region (aa 1–50) and a transactivation domain (aa 51–140), each harboring clusters of sequence variation reported in earlier studies as well as mutations identified in the present work. Known HBx mutations (blue circles) are mapped according to their true amino-acid positions within the linear structure, including S19A and K23R in the N-terminal regulatory segment and P38T, T81P, S101P, and V131I in the transactivation domain. Newly identified mutations detected in this study (red circles) are also shown at their proportional locations, including P32H, G37A, G43D, G73V, and the synonymous substitution c.312T > C (p.=) corresponding to amino-acid position 104. Domain boundaries are drawn to scale to clearly demarcate the N-terminal regulatory region (aa 1–50) from the transactivation domain (aa 51–140). This schematic is intended to convey the positional context of HBx variation rather than infer functional consequences.

To contextualize the positional arrangement of HBx sequence variation, we generated a linear schematic mapping previously reported mutations alongside those newly identified in our cohort (Fig. 2). The HBx protein consists of two major regions: the N-terminal regulatory domain (residues 1–50), which contributes to transcriptional modulation and protein–protein interactions, and the transactivation domain (residues 51–140), a multifunctional segment involved in signaling, mitochondrial targeting, and host-factor engagement. Within the N-terminal region, several known mutations (S19A, K23R, P38T) were positioned in their correct proportional locations, reflecting areas previously implicated in early regulatory activity. Newly identified substitutions detected in this study—P32H, G37A, and G43D—also mapped within this segment, indicating that the N-terminal domain remains a hotspot for amino-acid variation in genotype D HBV. The transactivation domain contained both known and newly identified variants. Previously reported mutations (T81P, S101P, V131I) were located across the central and distal portions of the domain. Newly identified variants—G73V and the synonymous nucleotide change c.312T > C (p.=) corresponding to codon 104—were also localized within this region, emphasizing the diversity of sequence alterations that accumulate across functional boundaries of HBx. By aligning all variants according to their true amino-acid positions, this schematic overcomes the limitations noted by the reviewer and distinguishes the mutation clusters according to biologically meaningful structural regions. The figure is designed to present positional accuracy rather than equal spacing, thereby providing a domain-based visualization that reflects the underlying architecture of HBx.

Fig. 2.

Linear schematic representation of HBx illustrating the spatial distribution of previously reported and newly identified mutations.

The Kerman isolates clustered closely with genotype D reference strains (Fig. 3), suggesting their genetic similarity and probable genotype classification. A phylogenetic tree was constructed using the Maximum Likelihood method based on nucleotide sequences of the HBx gene from 13 samples, including clinical isolates from Kerman and reference sequences from GenBank. The analysis revealed that the Kerman isolates clustered tightly with genotype D reference sequences (AB033558, AB033559, AB048704, U95551.1, and AB109475), confirming that these isolates belong to the HBV genotype D. Bootstrap values above 70% supported the robustness of several major clades, particularly the cluster formed by Kerman isolates and genotype D references. The sample labeled " Kerman_3” showed the closest relation to the D5 reference strain (AB109475), with a bootstrap value of 95%, indicating a strong phylogenetic link. The sequences from the Kerman patients formed a distinct cluster, indicating a possible regional similarity. Among them, Kerman_17 and Kerman_19 showed greater genetic divergence compared to other local samples, suggesting unique mutational events. Interestingly, the tree also included reference sequences from genotypes B, C, F, and H for comparative purposes. These genotypes formed distinct, well-separated clades, confirming the clear divergence between the local isolates and non-D genotypes. These findings suggest that the HBx sequences from Kerman patients are genetically conserved and closely related to the dominant genotype D strains circulating in the Middle East and Asia.

Fig. 3.

Phylogenetic tree of HBx nucleotide sequences from Kerman isolates and reference strains. Maximum likelihood analysis confirmed clustering with genotype D, supported by bootstrap values > 70%.

Note on Panel B: The 3D HBx structure displayed in Panel B represents only the portion of the protein that could be reliably modeled using SWISS-MODEL and visualized in UCSF Chimera. HBx contains intrinsically disordered regions—particularly within the N-terminal (~ 1–20 aa) and extreme C-terminal (~ 130–154 aa) segments—that cannot be resolved by template-based modeling and therefore do not appear in the predicted structure. No residues or mutations were manually omitted; the apparent shortening of the model reflects intrinsic HBx disorder and modeling limitations rather than exclusion of any variant.

To visualize the spatial distribution of the identified glycine substitutions (Fig. 4), full-length 3D models of both the reference HBx protein and the three patient-derived variants were generated using SWISS-MODEL and rendered in UCSF Chimera. Given the functional significance of the C-terminal α-helical transactivation domain, special emphasis was placed on the localization of glycine residues within this region. Native glycine residues in the reference HBx model were highlighted in green, representing the glycine hotspot cluster that is frequently reported as a structurally flexible and mutation-prone segment of HBx. All amino-acid substitutions identified in our samples—Gly→Asp and Gly→Ala (Kerman_15), Gly→Val accompanied by Pro→His (Kerman_17), and Gly→Val plus c.312T > C (Kerman_19)—were mapped onto the corresponding structural positions and annotated using red circular markers. Across all three variants, glycine substitutions occurred at positions embedded within or immediately adjacent to the C-terminal α-helix. This region is known to contribute to HBx transactivation capacity, protein–protein interactions, and stability of the helix–turn–helix architecture. While the modeling does not imply direct functional alteration, the spatial clustering of glycine substitutions within this localized helix suggests a potential impact on its conformational flexibility. These visual analyses complement the mutational profiling data and provide a structural context for interpreting the newly identified glycine variants.

Fig. 4.

Full-length structural models of HBx variants highlighting newly identified glycine-associated substitutions. (A–C) Three-dimensional structural models of HBx variants identified in patients Kerman_15, Kerman_17, and Kerman_19. Red circular markers indicate the precise positions of each amino-acid substitution, with labels showing the corresponding residue changes. Green-colored residues denote the native glycine positions in the reference HBx sequence, representing the glycine-associated cluster investigated in this study. These positions are located within or near the C-terminal α-helical transactivation region, a segment previously reported as structurally flexible and functionally relevant. (D) Reference HBx model (D1_reference_U95551.1) illustrating the conserved location of glycine residues within the C-terminal helix. All structures were modeled using SWISS-MODEL and visualized in UCSF Chimera under identical rendering parameters to ensure cross-panel consistency.

The HBx protein (red node) from HBV genotype C subtype ayr (NCBI Taxonomy ID: 10407) shows direct interactions with key human proteins (blue-green nodes, Homo sapiens, NCBI Taxonomy ID: 9606) including TP53, TNF, IL6, CREB1, BAX, and others. Edges represent experimentally validated, database-derived, and text-mining-supported interactions. This network highlights the central role of HBx in modulating host pathways related to apoptosis, inflammation, and tumorigenesis. STRING analysis revealed that the HBx protein (node X) interacts with a set of critical human proteins involved in apoptosis regulation, inflammatory responses, and cancer progression (Fig. 5). HBx demonstrated strong predicted and experimentally supported associations with TP53 (tumor suppressor), TNF and IL6 (inflammatory cytokines), BAX (pro-apoptotic factor), and CREB1 (transcriptional regulator). Additionally, interactions with CFLAR and BIRC5 suggest HBx may influence apoptosis inhibition mechanisms. The network topology showed TP53 as a major hub connecting multiple other proteins, indicating its central role in HBx-mediated modulation of host cell processes.

Fig. 5.

Protein–protein interaction (PPI) network of HBx and interacting human proteins based on STRING database analysis.

Discussion

The HBx protein is a multifunctional regulatory factor that contributes to viral replication, immune modulation, host transcriptional regulation, and hepatocarcinogenesis^8,9. Because of its structural plasticity and involvement in several host–virus signaling pathways, sequence variation within HBx may influence viral behavior and contribute to heterogeneous clinical outcomes across chronic HBV infection. In this study, we identified several amino-acid substitutions within HBx, including three newly identified glycine substitutions (G37A, G43D, G73V) and one synonymous change (c.312T > C). Glycine residues often promote conformational flexibility, and their replacement with bulkier or charged residues can theoretically alter local structural dynamics¹⁰. Although our computational modeling indicated only subtle effects on predicted secondary structure, the functional significance of these variants remains to be determined experimentally. Most substitutions identified in our cohort localized within either the N-terminal regulatory domain (aa 1–50) or the transactivation domain (aa 51–140), consistent with the established functional importance of these regions¹¹. G37A and G43D are positioned in the N-terminal segment, an intrinsically disordered region implicated in early transcriptional modulation and interactions with cellular proteins. G73V lies within the transactivation domain, where several previously reported functionally relevant residues—such as positions 81, 101, and 131—have been associated with altered transactivation capacity. While the proximity of these newly identified variants to known functionally relevant residues raises the possibility of regulatory implications, the absence of functional assays precludes definitive interpretation. Accordingly, these findings should be regarded as exploratory. The synonymous mutation c.312T > C does not alter HBx amino-acid sequence; however, synonymous variants in overlapping HBV reading frames may influence translation efficiency or regulatory motifs^12,13. Although the variant detected here lies outside the most well-studied overlap regions, potential cross-gene effects cannot be excluded and were not evaluated in this study. Mapping all substitutions onto a schematic representation of the HBx polypeptide (Fig. 2) demonstrated clustering within two domains: the N-terminal regulatory region and the transactivation region. This pattern is consistent with previous reports indicating that these domains are structurally flexible and frequently accumulate genotype-specific variation. The updated schematic distinguishes previously reported substitutions from newly identified ones and assigns all residue positions according to their correct domain boundaries, improving clarity and interpretability compared with earlier versions. Computational structural modeling provided additional context for understanding the spatial distribution of the glycine substitutions. Although the full 3D structure of HBx is unresolved, the C-terminal α-helical region is consistently predicted to form the most ordered structural element and plays a key role in HBx–host interactions. PPI network analysis of the reference HBx sequence highlighted several pathways involving apoptosis (BAX, CFLAR), inflammation (IL6, TNF), and transcriptional regulation (CREB1, TP53). Although our study did not examine how the identified mutations might alter these interactions, the localization of multiple glycine substitutions within regulatory regions suggests that subtle effects on HBx–host interactions remain possible and warrant follow-up studies. The newly identified glycine substitutions were positioned adjacent to or within regions predicted to contribute to structural stability or conformational flexibility. While no major structural disruptions were predicted, even subtle local alterations could influence HBx function and interactions—possibilities that require experimental validation. Clinical correlations from the four cases offered additional descriptive context. The G73V variant was identified in three samples and coincided with higher HBV DNA levels and HBeAg positivity in one patient. Conversely, the G37A and G43D substitutions were detected in patients with lower viral loads and negative HBeAg serology. These trends were not statistically significant due to the small cohort size but illustrate the heterogeneity of HBx variation across cases. Larger studies are required to determine whether these variants carry prognostic or functional relevance.

This study has several limitations, including the small sample size, lack of functional assays, reliance on computational predictions, and incomplete assessment of overlapping ORFs. Furthermore, although reference-based PPI network modeling highlights several HBx-associated pathways—including apoptosis, inflammation, and transcriptional regulation—our study did not assess whether the identified variants may alter these interactions.

In conclusion, this study expands the mutational spectrum of HBx by identifying several newly detected substitutions within chronic HBV cases and contextualizes them within structural, clinical, and evolutionary frameworks. While the biological implications of these variants remain speculative, the findings provide a basis for future investigations integrating functional assays, larger genotype-specific cohorts, and longitudinal clinical data to clarify the role of HBx variability in disease progression.

Author contributions

Kamyar Mazloum Jalali: Conceptualization, Methodology, Data curation, Formal analysis, Investigation, Writing – original draft, Visualization.Elahe Mosayebnejad Roudbaneh: Resources, Data collection, Validation, Writing – review & editing.Both authors read and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The datasets generated and/or analysed during the current study are available in GenBank under accession number: MT986033.1, MT986035.1, MT986036.1, and MT986037.1 (https://www.ncbi.nlm.nih.gov/nuccore/). Additional datasets supporting the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Consent for publication

As this report is based on fully anonymized archival samples with no identifying information, specific consent for publication was not required.

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participate

This study was conducted on archived, anonymized biological samples collected for diagnostic purposes. No identifiable personal data were used. Therefore, institutional ethical approval and written informed consent were not required, in accordance with local regulations and the Declaration of Helsinki. This study was approved by the Ethics Committee of Kerman University of Medical Sciences, Iran (Approval ID: IR.KMU.REC96000733). All methods were carried out in accordance with relevant guidelines and regulations.