IL-4R+SELL+ Naïve B Cell Expansion correlates with functional cure in PEG-IFNα Treated Chronic Hepatitis B Patients

IL-4R+SELL+ Naïve B Cell Expansion correlates with functional cure in PEG-IFNα Treated Chronic Hepatitis B Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article IL-4R+SELL+ Naïve B Cell Expansion correlates with functional cure in PEG-IFNα Treated Chronic Hepatitis B Patients ruonan xu, Lili Tang, Chunmei Bao, Cheng Zhen, Huan Wang, Chao Zhang, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7813973/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract During chronic hepatitis B (CHB) infection, B cell dysfunction is a key contributor to viral persistence. Pegylated interferon alpha (PEG-IFNα) acts as an effective therapeutic agent for CHB by restoring immune responses directed against HBV, however, a comprehensive landscape of the B-cell responses associated with functional cure has not been fully elucidated. In this study, we employed single-cell RNA sequencing (scRNA-seq) and flow cytometry to quantitatively assess the B-cell subsets in nucleos(t)ide analog (NAs)-treated CHB patients receiving sequential PEG-IFNα add-on therapy. We identified two functionally distinct naïve B cell subsets (IL-4R + SELL + and IL-4R-SELL-) and three memory B cell populations in peripheral blood. Patients who achieved a functional cure displayed significantly elevated frequencies of total B cells and the IL-4R + SELL + naïve B cell subset, whereas memory B cell frequencies remained comparable between groups. In contrast to cured patients, uncured individuals exhibited sustained activation of type I interferon response pathways in both naive and memory B cells, which may be a key mechanism of B cell dysfunction. Notably, the frequency of IL-4R + SELL + naïve B cells during the treatment was inversely correlated with baseline HBsAg levels at the initiation of PEG-IFNα therapy, and has high predictive value for HBsAg loss following PEG-IFNα therapy. Our results indicate that CHB patients attaining functional cure after PEG-IFNα add-on therapy undergo a distinct B cell reconstitution, characterized by a pronounced expansion of peripheral IL-4R + SELL + naïve B cells. This finding highlights its dual significance as both a novel immunological biomarker and a potential therapeutic target for CHB functional cure. Biological sciences/Immunology/Infectious diseases/Hepatitis/Viral hepatitis/Hepatitis B Biological sciences/Immunology/Lymphocytes/B cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The World Health Organization estimates that 257 million people worldwide are chronically infected with hepatitis B virus (HBV) 1 . The development of neutralizing antibodies against HBV surface antigen (HBsAg) represents both a hallmark of viral resolution and a key therapeutic target for functional cure 2 , 3 . An indispensable contribution of B cell in HBV control is evidenced by observations that B cell-depleting therapies (e.g., rituximab) can trigger fatal HBV reactivation, even in patients with prior serological resolution 4 – 7 . Early studies reported hyperactivated circulating B cells in both immune-active and inactive CHB carriers, marked by upregulation of activation-related genes (CD83, CD300c, CXCR4, CD69) and innate immune stimulators 8 , 9 . The coexistence of this systemic B-cell activation with an expanded atypical memory B-cell (AtMBCs) population suggests chronic overstimulation may drive phenotypic and functional exhaustion in CHB 10 – 13 . Recent advances in methodological breakthroughs and high-dimensional scRNA-seq have uncovered significant heterogeneity in circulating B cells, revealing distinct transcriptomic and proteomic profiles across subsets 14 , 15 . Key findings demonstrate fundamental differences between HBV specific B cells in CHB, the HBcAg-specific B cells predominantly exhibit an IgG + memory phenotype, and the HBsAg-specific B cells show expansion of atypical subsets with impaired antibody production capacity, this functional dichotomy contributes to the persistently low HBsAg seroconversion rates observed in chronic HBV infection 11 – 13 , 16 , 17 . Therefore, comprehensive characterization of peripheral blood B cell composition and phenotype is therefore essential to elucidate their role in HBsAg seroclearance and guide the development of targeted immunotherapeutic strategies. Among current treatments for CHB, PEG-IFNα remains the most effective strategy due to its higher HBsAg seroclearance rates compared to NAs 2 , 18 – 20 . While PEG-IFNα therapy can only induce favorable responses in a subset of patients, and the immunological mechanisms driving HBsAg seroclearance remain incompletely understood. Recent studies of CHB patients receiving sequential PEG-IFNα-based therapy revealed that functional cure correlates with restored HBsAg-specific memory B cells antibody secretion and distinct phenotypic profiles compared to non-responders 17 , 21 , 22 . However, naïve B cells have been largely neglected in single-cell transcriptomic studies of CHB, owing to their inadvertent exclusion during sample processing and computational analysis. Although HBsAg and HBcAg specific memory B cells have been well characterized in PEG-IFNα-treated patients, the global B cell changes at HBsAg loss remain poorly defined. Through comparative transcriptional profiling of functionally cured versus uncured patients, we sought to identify B cells signatures predictive of PEG-IFNα add-on treatment success. Here, through integrated scRNA-seq analysis of B cells from NAs-treated CHB patients receiving sequential PEG-IFNα add-on therapy, we provide a comprehensive characterization of human B cells heterogeneity. Our results reveal that enrichment of IL-4R + SELL + naïve B cells serve as a hallmark of functional cure. The frequency of these cells is inversely correlated with baseline HBsAg levels and predictive of treatment response, supporting their potential use as a predictive biomarker for PEG-IFNα add-on therapy outcomes. Materials and Methods Study population All studies were approved by the Ethics Committee of Fifth Medical Center of the Chinese PLA General Hospital (KY-2023-12-86-6). All participants were provided with written informed consent at the time of sampling. Peripheral blood mononuclear cells (PBMCs) were separately collected from patients (n = 32) who were assessed for functional cure status after completed 96-week follow-up period that counting from therapy initiation, and included both treatment and post-treatment observation. CHB patients receiving NAs monotherapy (n = 17) were also included. Thirty-two patients were classified into cured and uncured patients according to the presence of HBsAg seroclearance with or without HBsAg seroconversion, 11 of patients were selected for scRNA-seq analysis (Table 1), and 21 patients were collected for flow analysis. Among the 21 patients, 6 of those patients were HBsAg positive at the time of sampling, while converted into HBsAg loss within 96 weeks after PEG-IFNα add-on therapy, and 10 patients were still HBsAg positive after 96 weeks follow-up (Supplementary Table 1). The inclusion criteria for patients received PEG-IFNα add-on therapy: (1) Confirmed CHB diagnosis according to the Guideline of Prevention and Treatment for Chronic Hepatitis B, HBsAg (+) for at least 6months, (2) Age 18–65 years at enrollment, and received at least 12 months of continuous NAs treatment before receiving PEG-IFNα add-on treatment. (3) Patients exhibited HBsAg levels < 1,500 IU/mL, HBeAg-negative, and HBV DNA < 40 IU/mL at baseline prior to PEG-IFNα add-on. Exclusion criteria included: (1) HIV infection; (2) decompensated cirrhosis (Child-Pugh class B or C); (3) hepatic failure; (4) hepatocellular carcinoma; (5) history of solid organ transplantation; (6) active autoimmune disorders; (7) severe cardiovascular, cerebrovascular, renal or neurological comorbidities; and (8) current or planned pregnancy. The CHB patients following NAs monotherapy were those who had received continuous NAs therapy for ≥ 2 years with sustained virological suppression (HBV DNA < 40 IU/mL on ≥ 3 consecutive tests). The stop of PEG-IFNα treatment was according to the guidance: If after 24 weeks of treatment, the HBsAg level is < 200 IU/mL or shows a decline of 1 log IU/mL, continuation of combined NAs and Peg-IFN-α therapy was recommended for an additional 48–96 weeks. While, if after 24 weeks of treatment, the HBsAg level remains ≥ 200 IU/mL, discontinuation of PEG-IFNα was considered while maintaining NAs monotherapy 3 . PBMC isolation and processing Peripheral blood samples were collected in lithium-heparin vacutainer tubes (BD Biosciences, Franklin Lakes, NJ). PBMCs and plasma were isolated by density gradient centrifugation (400 × g, 20°C for 20 min) using Ficoll-Paque PLUS (TBD science, TianJin). Following two washes with phosphate-buffered saline (PBS, Gibco), PBMCs were resuspended in medium consisting of 90% heat-inactivated fetal bovine serum (FBS, Gibco, A5669701) and 10% dimethyl sulfoxide (DMSO, Sigma-Aldrich, St. Louis, MO). Cells were aliquoted at 5×10 6 cells/mL in cryovials and transferred to a controlled-rate freezing container for gradual cooling before long-term storage in liquid nitrogen. Flow Cytometry analysis Cryopreserved PBMCs were thawed at 37°C and stained for surface and intracellular markers using optimized protocols. Briefly, cells were resuspended in FACS buffer (2% FBS/PBS) and incubated with pre-titrated surface antibody cocktails (Supplementary Table 2) for 30 min at 4°C. After two washes with cold FACS buffer (300 × g, 5 min), intracellular staining was performed using BD Cytofix/Cytoperm™ Kit with 30 min fixation at RT, followed by Fc receptor blocking (5µL/test, 15 min on 4°C). Cells were then stained with anti-MX-1 primary antibody and FITC-conjugated secondary antibody (each 30 min at 4°C), with Perm/Wash buffer washes between steps. Samples were acquired on a BD FACSAria™ III. Data were analyzed in FlowJo software, v10.8.1. Single-cell RNA-sequencing data filtering, quality control, and integration The isolated cells were sequenced using 10x Chromium Single-cell (10x Genomics, USA, CG000527), according to the manufacturer’s instructions. scRNA-seq data filtering and quality control were pre-processed using CellRanger against the GRCh38 human reference. Genes that were detected less than 3 cells were removed. High quality cells were retained with criteria: 200 < expressed genes < 3000. mitochondrial transcript ratio < 10%, 2,000 < UMI number < 25,000. Potential doublets were identified and removed using DoubletFinder. We then applied Seurat (5.1.0) perform data scaling, transformation, clustering, dimensionality reduction, differential expression analyses and most visualization. Differential gene expression, pathways enrichment and HPA analysis Differentially expressed gene (DEGs) were identified using the FindMarkers function in Seurat with Wilcoxon rank sum test, and the Benjamini–Hochberg method was used to adjust the p-values for multiple hypothesis testing. DEGs were filtered using a minimum log2(fold change) of 0.5 and a adjust the p-values of 0.05. Pathway analysis for the DEGs was performed using the function ‘GSEA’ in clusterProfiler package. Human Protein Atlas (HPA) were referenced to B cells marker genes. The significantly upregulated genes identified in Seurat analysis (p.adj < 0.05) were cross-referenced with tissue-specific genes from the HPA database. Single-cell trajectory analysis In order to predict the differentiation relationship among the subtypes of B cells, pseudotime analysis was performed by monocle2 v.2.30.0 23,24 . A set of genes that defined B cells development were ordered for supervised trajectories. These genes included IGH genes, atypical memory B genes, ISGs, naïve B, classical memory B, and GC pathway genes. The expression profiles were reduced to 2 dimensions using the DDRTree algorithm in the function ‘reduceDimension’. The developmental trajectory was rooted at the predominant IGHD + B cell population (the starting point). The analysis systematically identified branch points corresponding to cell fate decisions during B cells differentiation. The ‘plot_cell_trajectory’ function was used for visualization of the different states of cells through a pseudotime analysis. Calculation of Function Module Scores for Each Cell To quantify pathway activity in B cell subsets, we performed gene signature scoring using the AUCell (v1.24.0). Gene sets were curated from MSigDB (v7.5.1) via the msigdbr package (v7.5.1), focusing on GO terms(C5), including GOBP_RESPONSE_TO_TYPE_I_INTERFERON, GOBP_B_CELL_ACTIVATION,GOBP_OXIDATIVE_PHOSPHORYLATION, and GOBP_ATP_SYNTHESIS_COUPLED_ELECTRON_TRANSPORT. Scores were calculated from log1p-transformed normalized counts, with AUC thresholds automatically determined via distribution knee points (minimum threshold: 5% of maximum theoretical AUC). Cells with < 200 detected genes were excluded. Differential activity across subsets was assessed using Wilcoxon rank-sum tests with Benjamini-Hochberg correction (FDR < 0.05). Statistical analyses GraphPad Prism version 8 and R version 4.3.2 were used for statistical analyses. Continuous variables were expressed as median (interquartile range, IQR). Mann-Whitney-tests were used for comparisons between two groups, and the Wilcoxon signed-rank test was used for matched pairs. Correlations between two quantitative variables were evaluated using Pearson’s rank correlation test. Categorical variables were expressed as number (%) and compared by Chi-squared test. At the end time point of follow-up, the area under the receiver-operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value of the target B cell subsets or combine with HBsAg for predicting HBsAg seroclearance was calculated. Statistical significance was defined as p < 0.05, indicated as follows; *p < 0.05, **p < 0.01, ***p < 0.001, or ****p < 0.0001. Results Expansion of peripheral IL-4R + SELL + naïve B Cells associates with functional cure in CHB patients receiving sequential PEG-IFNα add-on therapy We performed single-cell RNA sequencing on peripheral blood mononuclear cells isolated from 11 NAs-treated HBeAg-negative CHB patients with or without functional cure following sequential PEG-IFNα add-on therapy, 6 who achieved functional cure and 5 who did not (Fig. 1 A, Table 1). All patients were HBeAg-negative at baseline. Although pre-treatment HBsAg levels were slightly lower in cured patients (median 138.4 IU/mL, IQR 28.9–943.5) compared to uncured patients (median 419.9 IU/mL, IQR 297.8–1045.0), this difference was not statistically significant. Complete epidemiological, clinical, and virological parameters are simultaneously outlined. After rigorous quality control, cell populations were identified through unsupervised clustering, with clusters expressing canonical lineage markers retained for analysis (Fig. 1 B and 1 C). The proportion of cells within PBMCs was calculated (Fig. 1 D), the proportion of B cells was significantly elevated in functionally cured patients (p < 0.05) (Fig. 1 E), and negatively associated with the baseline level of HBsAg (r = -0.747, p = 0.088). While other lymphocyte subsets (plasma cells, NK cells, CD4+/CD8 + T cells, monocytes, dendritic cells) showed no intergroup differences (Supplementary Fig. 1A and 1B), and only the frequency of NK cells showed a negative correlation with baseline level of HBsAg in uncured patients (r = -0.897, p = 0.039). These results underscore the potential role of B cells reconstitution in achieving functional cure during PEG-IFNα based add-on therapy. Following rigorous quality control, we successfully segregated B cells from other lymphocyte populations. Unsupervised clustering revealed two distinct naïve B cell subsets and three memory B cell subsets, each defined by unique canonical marker expression (Fig. 1 F and 1 H). One subset of naïve B cells enriched for NR4A1, CD72, and PLD4, and the other subset of naïve B cells marked by elevated FCER2, IL-4R, SELL, and PLPP5. Pre-memory B cells were identified by higher expression of TNFRSF13B and GPR183, and low expression of IGHD and IGHM. Atypical memory B cells were identified by higher expression of FCRL5, FCRL3 and SOX5, classical memory B cells were identified by higher expression of SELL, COCH, CD80, and CD86, highlighting their transcriptional divergence (Fig. 1 H). Naïve B cells make up over 50% of the total peripheral B cell population in our cohort (Fig. 1 G). Notably, the interferon therapy induced expansion of B cells in functionally cured patients was driven specifically by an IL-4R + SELL + naïve B cell subset. Most importantly, no correlation was observed between IL-4R + SELL + naïve B cells and HBsAg level at sampling in uncured patients, while there was a significantly negative correlation between the percentage of IL-4R + SELL + naïve B cells and the baseline level of HBsAg in cured patients (r = -0.843, p = 0.035) (Fig. 1 I), and the ratio of IL-4R-SELL- naïve B cells to IL-4R + SELL + naïve B cells is prone to positively correlated with the baseline level of HBsAg in those patients (r = 0.798, p = 0.057), highlighting the potential role of IL-4R + SELL + naïve B cells, and the well balance of IL-4R-SELL- naïve B cells to IL-4R + SELL + naïve B cells may benefit the favorable outcome of PEG-IFNα treatment (Fig. 1 J). While there is no difference of IL-4R-SELL- naïve B cells between the two groups. In our study, memory B cell subsets (pre-memory, atypical, and classical) and terminally differentiated B cells (plasma cells and plasmablast) showed no significant changes between cured and uncured patients. Additionally, no correlation was observed between different memory B cell subsets and HBsAg levels (Supplementary Fig. 2A and 2B). IL-4R + SELL + naïve B cells show a distinct genes and phenotype state We next compared the differential expression of genes in IL-4R-SELL- naïve B cells and IL-4R + SELL + naïve B cells. IL-4R + SELL + naïve B cells express high level of IL-4R, BACH2, FOXO1, FCRL1, CXCR4, CD83 and CD69. While, IL-4R-SELL- naïve B cells express high level of PLD4, CD38, CD72, MZB1, STAT6, IRF4, NR4A1 and JUNB (Fig. 2 A). Pathway enrichment analysis demonstrated that antigen receptor mediated signaling pathway and B cell receptor signaling pathway were enhanced in IL-4R + SELL + naïve B cells, while response to type I interferon, positive regulation of Erbb signaling pathway, and G protein coupled receptor signaling pathway were activated in IL-4R-SELL- naïve B cells (Fig. 2 B). Furthermore, we performed comparative analyses of IL-4R-SELL- naïve B cells and IL-4R + SELL + naïve B cells between cured and uncured patients. The results demonstrated that the key differences between these two naïve B cell subsets were primarily metabolic. Specifically, both subsets from cured patients showed significantly enhanced oxidative phosphorylation and electron transport-coupled ATP synthesis compared to those from uncured patients. In contrast, IL-4R + SELL + naïve B cells in uncured patients exhibited elevated immune cells activation and protein kinase activity, and IL-4R-SELL- naïve B cells displayed upregulation of long chain fatty acid metabolic process and increased activation of NF-kB-inducing kinase activity (Fig. 2 C and 2 D). We next evaluated the expression of a broader panel of functional genes in two naïve B cell subsets using AUCell scores. Compared to cured patients, uncured patients exhibited enhanced B cell activation and type I interferon responses in both subsets. Conversely, cured patients showed elevated activity in ATP metabolic processes and oxidative phosphorylation across both naïve B cell populations (Fig. 2 E). The interferon signaling pathway of memory B cells remains persistently activated in uncured patients. We then investigated the characteristics of memory B cells. Pre-memory B cells characterized by the specific expression of FOXP1, CXCR4, TNFRSF13B, CD83, PAX5, and GPR183, and atypical memory B cells expressed higher levels of ITGB2, FCRL3, TBX21 and IGHG3, classical memory expressed CD80, CD86, COCH, DUSP2, XAF1, BCL2A1 and IRF4 (Fig. 3 A). Although no differences of the frequency were observed in pre-memory, classical memory, or atypical memory B cells between cured and uncured patient groups, these cell populations exhibited distinct genes and signaling pathway profiles (Fig. 3 B and 3 C). The electron transport-coupled ATP synthesis pathway was consistently upregulated across all memory B cell subsets in cured patients. In contrast, atypical memory B cells from uncured patients showed enhanced positive regulation of phagocytosis, while classical memory and pre-memory B cells exhibited heightened type I interferon response pathways (Fig. 3 C). Comparative analysis revealed significant differences in signaling pathway activity between cured and uncured patients. In uncured patients, memory B cells exhibited elevated scores for type I interferon response and B cell activation. Conversely, cured patients showed increased activity in ATP synthesis-coupled electron transport and oxidative phosphorylation pathways (Fig. 3 D). In addition, we identified the top 25 up-regulated genes in IL-4R + SELL + naïve B cells inverse IL4-R-SELL- naïve B cells, which encode proteins previously detected in germinal center (GC) B cells according to the Human Protein Atlas (HPA) database. Notably, IL-4R + SELL + naïve B cells exhibited greater similarity to GC B cells (Fig. 3 E). To further elucidate the state transition trajectories of naïve and memory B cells, we reconstructed the developmental trajectories of B cells differentiation. Strikingly, in the uncured patients, naïve B cells exhibited a developmental trajectory to the atypical memory lineage. In contrast, in the cured patients, naïve B cells exhibited a developmental trajectory to the classical memory lineage (Fig. 3 F). High IL-4R + SELL + naïve B Cell Frequency Predicts Better PEG-IFN α Therapy Response. We employed flow cytometry to characterize naïve and memory B cell subsets in CHB patients undergoing sequential PEG-IFNα add-on therapy following NAs treatment. Peripheral blood samples were collected at different time points during PEG-IFNα add-on therapy, with functional cure defined as HBsAg loss confirmed at 96-week follow-up. Based on treatment outcomes, patients were stratified into functional cure (n = 11, six achieved a functional cure after sample collection, and five at the time of collection, and 10 uncured patients). Baseline demographic, clinical, and laboratory characteristics are detailed in Supplementary Table 1. Based on single-cell clustering patterns of naïve B cells, we further stratified total naïve B cells using IL-4R and SELL markers. Comparative analysis across functionally cured and uncured groups revealed significantly higher frequencies of IL-4R + SELL + naïve B cells in cured patients (p = 0.006, Fig. 4 A). Correlation analyses demonstrated inverse relationships between IL-4R + SELL + naïve B cell frequency and baseline HBsAg levels (r = -0.631, p = 0.002; Fig. 4 B), and HBsAg levels at sampling (r = -0.641, p = 0.008) (Supplementary Fig. 3A). The uncured patients exhibited a higher percentage of IL-4R-SELL- naïve B cells compared to cured patients (p = 0.06) (Fig. 4 C). This subset showed a positive correlation with baseline HBsAg levels (r = 0.681, p = 0.001; Fig. 4 D) and sampling timepoint (r = 0.652, p = 0.006; Supplementary Fig. 3B). Notably, the ratio of IL-4R + SELL + to IL-4R-SELL- naïve B cells was elevated in cured patients versus uncured patients (p = 0.004) and demonstrated a negative correlation with baseline HBsAg levels (r = -0.496, p = 0.022) (Supplementary Fig. 3C and 3D). Furthermore, the percentage of IL-4R + SELL + naïve B cells showed no correlation with age, duration of PEG-IFNα treatment, ALT, and AST levels (Figs. 4 E- 4 H). Initial flow cytometric analysis of CD21 and CD27 expression showed no significant differences in the frequencies of naïve B cells (CD19 + CD21 + CD27-), resting memory B cells (CD19 + CD21-CD27+), classical memory B cells (CD19 + CD21 + CD27+), and atypical memory B cells (CD19 + CD21-CD27-) (Supplementary Fig. 3E to 3H). Furthermore, the percentage of total naïve B cells negatively correlated with HBsAg levels at the time of baseline (r = -0.568, p = 0.007), and the percentage of atypical memory B cells positively correlated with HBsAg levels at the time of baseline (r = 0.473, p = 0.030) (Supplementary Fig. 3I to 3L). Most importantly, we conducted the ROC (Receiver Operating Characteristic) analyses, both separately and in combination on HBsAg levels and the percentage of IL-4R + SELL + naïve B cells across all patients. The results indicated that IL-4R + SELL + naïve B cells alone predicted treatment outcome with an ROC of 0.846 (p = 0.008) in the flow cytometry validation cohort and ROC of 0.90 (p = 0.029) in the scRNA-seq training cohort (Fig. 4 I). Combining IL-4R + SELL + naïve B cells with HBsAg further improved predictive efficiency, achieving an AUC of 0.891 (p = 0.003) in the flow cytometry validation cohort and 0.867 (p = 0.045) in the scRNA-seq training cohort (Fig. 4 J). In contrast, HBsAg alone showed no significant predictive value (Fig. 4 K and 4 L). IL-4R + SELL + naïve B cells are associated with the level of HBsAg in patients with CHB The percentage of IL-4R + SELL + naïve B cells showed no correlation with age, duration of PEG-IFNα treatment, ALT, and AST levels. However, this B cell subset demonstrated positive correlations with both pre-treatment HBsAg levels and HBsAg at sampling timepoints. Based on these findings, we enrolled NAs-treated CHB patients stratified by different HBsAg levels. Detailed patient characteristics are provided in Supplementary Table 2. Based on HBsAg levels, patients were stratified into two groups, the low HBsAg group ( 1000 IU/ml; median 2497.0 IU/ml, IQR 1915.0-3725.0). Flow cytometry analysis revealed distinct B cell subset patterns. As indicated that the patients with low HBsAg levels exhibited significantly higher percentages of IL-4R + SELL + naïve B cells (p = 0.006) and elevated IL-4R + SELL+/IL-4R-SELL- naïve B cell ratio (p = 0.015), both parameters demonstrated significant inverse correlation with HBsAg levels at sampling (r = -0.652, p = 0.079; r = -0.813, p = 0.014) (Fig. 5 A and 5 B). Conversely, these patients with high HBsAg exhibited increased frequency of both IL-4R-SELL- naïve B cells, and the IL-4R-SELL- population showed a positive correlation with HBsAg level at sampling (r = 0.893, p = 0.001; Fig. 5 C). Our analysis of memory B cell subsets in NAs-treated patients showed no significant differences in memory B cell percentages between patients with low and high HBsAg levels (Supplementary Fig. 4A). In addition, no significant correlations were found between memory B cell subset percentages, and HBsAg levels at any sampling timepoint (Supplementary Fig. 4B and 4C). We further characterized the phenotype markers associated with IFN pathway (MX-1) and cellular activation (CD83, CD38, CD69, CD86) in naïve B cells. We found that the patients with low HBsAg after NAs treatment have high percentage of MX-1 + IL-4R + SELL + naïve B cells (p = 0.005), and CD83 + IL-4R + SELL + naïve B cells (p = 0.005; Fig. 6 A) than those patients with high HBsAg. In addition, in patients with low HBsAg level, the IL-4R + SELL + naïve B cells expressed higher level of CD83 (p = 0.002) and lower level of CD86 (p = 0.021) than non- IL-4R + SELL + naïve B cells (Fig. 6 B). While in patients with high HBsAg level, the IL-4R + SELL + naïve B cells expressed lower level of MX-1 (p = 0.043), and higher level of CD83 (p = 0.02), CD38 (p = 0.057) and CD69 (p = 0.008) versus IL-4R- SELL- counterparts (Fig. 6 C). Discussion Despite PEG-IFNα treatment, only a minority of adult CHB patients with relatively low HBsAg levels achieve a functional cure 25 – 27 . Identifying reliable predictors of response beyond HBsAg levels is crucial to optimize PEG-IFNα therapy for patients most likely to benefit. Based on this rationale, we sought to identify cellular biomarkers associated with PEG-IFNα treatment response, enabling targeted treatment of CHB patients most likely to benefit. B cells play a pivotal role in achieving functional cure for CHB by sustaining HBV-specific immune responses, primarily via antibody production. The marked heterogeneity observed in B cell subset distribution and gene expression patterns during HBV infection suggests that different phenotypic subsets may play functionally distinct or antagonistic roles, while also highlighting potential therapeutic opportunities to selectively enhance protective B cell compartments. However, owing to their low frequency and marked functional heterogeneity, B cells remain relatively understudied in the context of HBV infection. By leveraging single-cell analysis of CHB patients receiving sequential PEG-IFNα combination therapy, we identify IL-4R + SELL + naïve B cell expansion as a defining feature of functional cure. This clinically favorable subset exhibits distinct transcriptional signatures, phenotypic plasticity, and represents a potential biomarker for functional cure prediction. Previous studies demonstrated that CHB patients exhibited increased total atypical memory B cells, which positively correlated with HBV DNA and ALT levels but not with HBsAg 11 , 12 . In contrast, our study did not detect significant associations between any memory B cell subsets and HBV DNA, ALT, or HBsAg levels in PEG-IFNα treated CHB patients. Notably, our cohort exclusively comprised an advantaged population with undetectable HBV DNA and low HBsAg levels after NAs therapy, suggesting that memory B cell profiling might not reliably reflect interferon treatment responsiveness in those patients. Strikingly, we found two subsets of naïve B cells with transcriptomic and functional divergence, and the frequency of protective IL-4R + SELL + naïve B cells was significantly elevated in patients achieving functional cure, showing an inverse correlation with baseline HBsAg levels that measured at PEG-IFNα initiation, and the level of HBsAg at sampling. Notably, IL-4R + SELL + naïve B cell frequency exhibited consistent predictive value across both our scRNA-seq cohort and flow cytometry validation cohorts. In contrast, baseline HBsAg levels at the time of PEG-IFNα administration failed to show significant predictive power in the flow cytometry validation cohort. These findings partially explain why some treatment-advantaged patients with low initial HBsAg fail to achieve HBsAg loss following interferon therapy. Of particular note, the combination of HBsAg level and IL-4R + SELL + naïve B cell frequency exhibits superior predictive performance for functional cure, these findings imply that integrating HBsAg with additional immune cell biomarkers could improve its predictive value in assessing treatment efficacy. While further investigation is needed to elucidate whether the observed association reflects selection of pre-existing high-frequency naïve B cell subsets or interferon-driven expansion of these populations, our results highlight the critical, yet underappreciated, role of naïve B cells in mediating HBV functional cure. Current evidence strongly confirms the critical link between HBsAg levels and HBV functional cure. Additionally, pre-treatment autoantibody screening was associated with treatment responses in PEG-IFNα therapy 28 , 29 . Our single-cell RNA sequencing revealed a significant inverse correlation between IL-4R + SELL + naïve B cell frequency and baseline HBsAg titers during interferon therapy, indicating potential regulation of this B cell subsets by HBsAg. To investigate the association between HBsAg levels and naïve B cell frequency independent of IFNα effects, we analyzed IL-4R + SELL + naïve B cells in CHB patients received NAs treatment. Notably, IL-4R + SELL + naïve B cells were significantly enriched in patients with low HBsAg levels ( 1000 IU/mL). So reduced HBsAg levels may create a permissive environment for restoring B cells function, and exogenous interferon administration under these conditions potently amplifies antiviral responses. This discovery identifies a critical "immune reconstitution window" in hepatitis B therapy, providing a mechanistic framework for integrating antiviral and immunomodulatory strategies. In addition, contrary to established reports of age-dependent interferon responsiveness, our cured cohort demonstrated comparable outcomes across age groups. The age-independent nature of IL-4R + SELL + naïve B cell frequencies in patients further suggests these protective B cell subsets may operate through mechanisms distinct from classical, age-associated HBsAg-specific T cell immunity 30 . Data from chronic hepatitis B patients indicate a deficiency in endogenous IFNα during persistent infection, yet these individuals retain the capacity to respond to exogenous IFNα 31,32 . Our study aims to define the distinct interferon transcriptomic signatures of naïve and memory B cells in functionally cured versus uncured patients. Comparative analysis revealed fundamental differences in B cell profiles, the cured patients exhibited upregulation of bioenergetic pathways (e.g., oxidative phosphorylation and ATP synthesis), whereas uncured patients showed persistent IFN pathway activation across both naïve and memory B cell subsets. Notably, type I interferons have been shown to induce an epigenetically distinct memory B cell subset during chronic viral infection 33 , while sustained IFN signaling is associated with CD4 + T cell exhaustion and impaired naïve B cell development in HIV-1 infection 34 . Our findings further suggest that persistent IFN activation may limit treatment efficacy, even in patients who otherwise exhibit favorable responses. Although the precise molecular initiators and mechanisms driving beneficial interferon signaling in cured individuals remain incompletely understood, targeted modulation of this pathway may enhance HBsAg seroclearance. Emerging evidence suggests that reducing SOCS2 levels, a key negative feedback regulator of IFN signaling could improve cure rates 35 . However, further mechanistic studies are needed to validate this therapeutic strategy. Our study has some limitations. First, our data confirm the protective role and predictive value of IL-4R + SELL + naïve B cells for functional cure. However, the dynamic changes of these protective B cells during interferon therapy remain unmonitored. Our study cannot currently differentiate whether the effects stem from intrinsic naïve B cell levels or interferon treatment efficacy. Second, serial measurements of immunoregulatory cytokines (e.g., IL-4, IL-21) associated with naïve B cell differentiation were unavailable due to missing pre-/mid-treatment samples, limiting our understanding of host-IFNα interactions. Third, our analysis was limited to total B cell populations rather than antigen-specific subsets, precluding assessment of HBsAg-specific B cell dynamics. Additionally, the exclusive focus on peripheral blood B cells may not fully capture liver-localized immunological processes critical for HBV seroclearance. Finally, to our knowledge, no prior studies have comprehensively characterized naïve B cell dynamics in PEG-IFNα treated CHB patients stratified by functional cure status. As such, our clustering approach while revealing novel subsets may have underestimated. Overall, for a long time, there has been a lack of reliable predictive immunological markers to evaluate treatment efficacy during interferon therapy. In this study, we identified a protective subset of IL-4R + SELL + naïve B cells in the interferon-treated cohort, characterized the phenotypic and functional features of these cells, and assessed their value in predicting functional cure. This research not only enhances our understanding of B cells but also contributes to the accurate prediction of interferon treatment outcomes. Declarations Conflict of Interest All authors declare no conflict of interest related to this publication. Authors’ Contributions Guarantor of study: Runan Xu, Fu-Sheng Wang; Study concept and design: Runan Xu, Fu-sheng Wang; Data collection and/or interpretation: Honghong Liu, Huan Wang, Yue Yuan, Jinhong Yuan, Yingying Gao, Yangliu Chen, Lin Cao; Technical support: Cheng Zhen; Data analysis: Lili Tang, Chunmei Bao; Drafting of manuscript: Runan Xu, Lili Tang; Critical revision of manuscript: Chao Zhang, Yang Zhang, Jinwen Song, Yanmei Jiao, Tao Yang, Jun-Liang Fu. All authors read and approved the final manuscript. Lili Tang* and Chunmei Bao* contributed equally to this study. Acknowledgments This work was supported by grants from the National Key Research and Development Program of China (no.2023YFC2308100) and National Natural Science Foundation of China (no.82130019). We thank all patients who participated in this study. We would like to thank Dr. Liguo Zhang for providing the recombinant human MX-1 protein. Data Availability Statements The scRNAseq datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References Polaris Observatory, C. Global prevalence, treatment, and prevention of hepatitis B virus infection in 2016: a modelling study. Lancet Gastroenterol Hepatol 3, 383–403, doi: 10.1016/S2468-1253(18)30056-6 (2018). Huang, D. et al. End-of-treatment HBcrAg and HBsAb levels identify durable functional cure after Peg-IFN-based therapy in patients with CHB. J Hepatol 77, 42–54, doi: 10.1016/j.jhep.2022.01.021 (2022). Hepatology, C. S. o. I. D. S. o. Guidelines for the prevention and treatment of chronic hepatitis B (version 2022). Chinese Journal of Infectious Diseases [Chinese] 30(12), 1309–1331, doi: 10.3760/cma.j.cn501113-20221204-00607 (2022). Huang, H. et al. Entecavir vs lamivudine for prevention of hepatitis B virus reactivation among patients with untreated diffuse large B-cell lymphoma receiving R-CHOP chemotherapy: a randomized clinical trial. JAMA 312, 2521–2530, doi: 10.1001/jama.2014.15704 (2014). Loomba, R. & Liang, T. J. Hepatitis B Reactivation Associated With Immune Suppressive and Biological Modifier Therapies: Current Concepts, Management Strategies, and Future Directions. Gastroenterology 152, 1297–1309, doi: 10.1053/j.gastro.2017.02.009 (2017). Kusumoto, S. et al. Risk of HBV reactivation in patients with B-cell lymphomas receiving obinutuzumab or rituximab immunochemotherapy. Blood 133, 137–146, doi: 10.1182/blood-2018-04-848044 (2019). Dervite, I., Hober, D. & Morel, P. Acute hepatitis B in a patient with antibodies to hepatitis B surface antigen who was receiving rituximab. N Engl J Med 344, 68–69, doi: 10.1056/NEJM200101043440120 (2001). Oliviero, B. et al. Enhanced B-cell differentiation and reduced proliferative capacity in chronic hepatitis C and chronic hepatitis B virus infections. J Hepatol 55, 53–60, doi: 10.1016/j.jhep.2010.10.016 (2011). Xu, X. et al. Reversal of B-cell hyperactivation and functional impairment is associated with HBsAg seroconversion in chronic hepatitis B patients. Cell Mol Immunol 12, 309–316, doi: 10.1038/cmi.2015.25 (2015). Vanwolleghem, T. et al. Re-evaluation of hepatitis B virus clinical phases by systems biology identifies unappreciated roles for the innate immune response and B cells. Hepatology 62, 87–100, doi: 10.1002/hep.27805 (2015). Salimzadeh, L. et al. PD-1 blockade partially recovers dysfunctional virus-specific B cells in chronic hepatitis B infection. J Clin Invest 128, 4573–4587, doi: 10.1172/JCI121957 (2018). Burton, A. R. et al. Circulating and intrahepatic antiviral B cells are defective in hepatitis B. J Clin Invest 128, 4588–4603, doi: 10.1172/JCI121960 (2018). Vanwolleghem, T. et al. Hepatitis B core-specific memory B cell responses associate with clinical parameters in patients with chronic HBV. J Hepatol 73, 52–61, doi: 10.1016/j.jhep.2020.01.024 (2020). Dusheiko, G. M., Hoofnagle, J. H., Cooksley, W. G., James, S. P. & Jones, E. A. Synthesis of antibodies to hepatitis B virus by cultured lymphocytes from chronic hepatitis B surface antigen carriers. J Clin Invest 71, 1104–1113, doi: 10.1172/jci110860 (1983). Vanwolleghem, T., Adomati, T., Van Hees, S. & Janssen, H. L. A. Humoral immunity in hepatitis B virus infection: Rehabilitating the B in HBV. JHEP Rep 4, 100398, doi: 10.1016/j.jhepr.2021.100398 (2022). Le Bert, N. et al. Comparative characterization of B cells specific for HBV nucleocapsid and envelope proteins in patients with chronic hepatitis B. J Hepatol 72, 34–44, doi: 10.1016/j.jhep.2019.07.015 (2020). Zhang, J. W. et al. Varied immune responses of HBV-specific B cells in patients undergoing pegylated interferon-alpha treatment for chronic hepatitis B. J Hepatol 81, 960–970, doi: 10.1016/j.jhep.2024.06.033 (2024). Buti, M. et al. Sequential Peg-IFN after bepirovirsen may reduce post-treatment relapse in chronic hepatitis B. J Hepatol 82, 222–234, doi: 10.1016/j.jhep.2024.08.010 (2025). Li, F. et al. PegIFN alpha-2a reduces relapse in HBeAg-negative patients after nucleo(s)tide analogue cessation: A randomized-controlled trial. J Hepatol 82, 211–221, doi: 10.1016/j.jhep.2024.07.019 (2025). Vecchi, A. et al. HBcrAg values may predict virological and immunological responses to pegIFN-alpha in NUC-suppressed HBeAg-negative chronic hepatitis B. Gut 73, 1737–1748, doi: 10.1136/gutjnl-2024-332290 (2024). Gu, S. et al. Circulating HBsAg-specific B cells are partially rescued in chronically HBV-infected patients with functional cure. Emerg Microbes Infect 13, 2409350, doi: 10.1080/22221751.2024.2409350 (2024). Tian, C. et al. Use of ELISpot assay to study HBs-specific B cell responses in vaccinated and HBV infected humans. Emerg Microbes Infect 7, 16, doi: 10.1038/s41426-018-0034-0 (2018). Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 32, 381–386, doi: 10.1038/nbt.2859 (2014). Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat Methods 14, 979–982, doi: 10.1038/nmeth.4402 (2017). Wong, G. L. H., Gane, E. & Lok, A. S. F. How to achieve functional cure of HBV: Stopping NUCs, adding interferon or new drug development? J Hepatol 76, 1249–1262, doi: 10.1016/j.jhep.2021.11.024 (2022). Chu, J. H. et al. Real-world study on HBsAg loss of combination therapy in HBeAg-negative chronic hepatitis B patients. J Viral Hepat 29, 765–776, doi: 10.1111/jvh.13722 (2022). Zeng, Q. L. et al. Short-term Peginterferon-Induced High Functional Cure Rate in Inactive Chronic Hepatitis B Virus Carriers With Low Surface Antigen Levels. Open Forum Infect Dis 7, ofaa208, doi: 10.1093/ofid/ofaa208 (2020). Fink, D. L. et al. Auto-antibodies against interferons are common in people living with chronic hepatitis B virus infection and associate with PegIFNalpha non-response. JHEP Rep 7, 101382, doi: 10.1016/j.jhepr.2025.101382 (2025). Ferri, D. M. et al. Elevated Levels of Interferon-alpha Act Directly on B Cells to Breach Multiple Tolerance Mechanisms Promoting Autoantibody Production. Arthritis Rheumatol 75, 1542–1555, doi: 10.1002/art.42482 (2023). Le Bert, N. et al. Effects of Hepatitis B Surface Antigen on Virus-Specific and Global T Cells in Patients With Chronic Hepatitis B Virus infection. Gastroenterology 159, 652–664, doi: 10.1053/j.gastro.2020.04.019 (2020). Onji, M., Lever, A. M., Saito, I. & Thomas, H. C. Defective response to interferons in cells transfected with the hepatitis B virus genome. Hepatology 9, 92–96, doi: 10.1002/hep.1840090115 (1989). Davis, G. L. & Hoofnagle, J. H. Interferon in viral hepatitis: role in pathogenesis and treatment. Hepatology 6, 1038–1041, doi: 10.1002/hep.1840060537 (1986). Cooper, L. et al. Type I interferons induce an epigenetically distinct memory B cell subset in chronic viral infection. Immunity 57, 1037–1055 e1036, doi: 10.1016/j.immuni.2024.03.016 (2024). Liu, X. et al. Single-cell multi-omics profiling uncovers the immune heterogeneity in HIV-infected immunological non-responders. EBioMedicine 115, 105667, doi: 10.1016/j.ebiom.2025.105667 (2025). Guan, G. et al. Higher TP53BP2 expression is associated with HBsAg loss in peginterferon-alpha-treated patients with chronic hepatitis B. J Hepatol 80, 41–52, doi: 10.1016/j.jhep.2023.09.039 (2024). Tables Table 1 is available in the Supplementary Files section. Additional Declarations (Not answered) Supplementary Files Table1.xlsx Table 1 SupplementaryTable3.xlsx Supplementary Table 3 SupplementaryTable2.xlsx Supplementary Table 2 SupplementaryTable1.xlsx Supplementary Table 1 Supplementaryfigure1.doc Supplementary-figure -1 Supplementaryfigure5.doc Supplementary-figure -5 Supplementaryfigure4.doc Supplementary-figure -4 Supplementaryfigure3.doc Supplementary-figure -3 SupplementaryFigure15.docx Supplementary-Figure-1-5 Supplementaryfigure2.doc Supplementary-figure -2 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7813973","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":535626194,"identity":"fa405ed9-687c-4f95-a886-f2d842226931","order_by":0,"name":"ruonan xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDADfmbGBoMPDBY8xGuRbG8+UDiDQYIELQZnjiV85mGQIELljdxnEh932OUx3Mgx3GxTIyEDFDnA8KNiG273zEg3k5x5JrmYcUaOsXHOMQkegxt5CYw9Z27j1MIvkcYmzdvGnNgskWNmnMMG0pJjwMzYhlsLG0RLfWKbRI75b4t/RGiB2nI4sYfnWIIxYxsRWiR7njFbzmw7njiDvfmAYW+fBI/kmTcGB/H5xeB4GuONj23VifsPA6Pyxzcbe77jOYYPflTg1oIJFA4wMBwgQT0QyDeQpn4UjIJRMAqGPwAA4eVSsL1KsrQAAAAASUVORK5CYII=","orcid":"","institution":"Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":true,"prefix":"","firstName":"ruonan","middleName":"","lastName":"xu","suffix":""},{"id":535626195,"identity":"0528c864-6785-4b12-9cfd-ad0d4ca75b40","order_by":1,"name":"Lili Tang","email":"","orcid":"","institution":"Institute of Military Cognition and Brain Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Tang","suffix":""},{"id":535626196,"identity":"f2cee465-6dcb-4649-a970-915580636867","order_by":2,"name":"Chunmei Bao","email":"","orcid":"","institution":"Beijing302 hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunmei","middleName":"","lastName":"Bao","suffix":""},{"id":535626197,"identity":"6e5ce592-3a06-47bf-b246-727d4394732e","order_by":3,"name":"Cheng Zhen","email":"","orcid":"","institution":"Senior Department of Infectious Diseases, Fifth Medical Center of Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Zhen","suffix":""},{"id":535626198,"identity":"2759f706-2f1b-497f-85b8-b638a114f57a","order_by":4,"name":"Huan Wang","email":"","orcid":"","institution":"The Fifth Medical Center of Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Wang","suffix":""},{"id":535626199,"identity":"32ea66b6-f27c-4cab-b281-815ee5555869","order_by":5,"name":"Chao Zhang","email":"","orcid":"","institution":"Beijing 302 hospital","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Zhang","suffix":""},{"id":535626200,"identity":"2b35dd53-40fa-446c-a523-e876f3c29efc","order_by":6,"name":"Yang Zhang","email":"","orcid":"","institution":"The Fifth Medical Center of Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Zhang","suffix":""},{"id":535626201,"identity":"29978b61-bc6f-4739-928f-fab65f3dd810","order_by":7,"name":"Hong-Hong Liu","email":"","orcid":"","institution":"Beijing 302 hospital","correspondingAuthor":false,"prefix":"","firstName":"Hong-Hong","middleName":"","lastName":"Liu","suffix":""},{"id":535626202,"identity":"33144b62-2769-47aa-b095-25518660708b","order_by":8,"name":"Jin-Wen Song","email":"","orcid":"https://orcid.org/0000-0002-8582-8012","institution":"National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Jin-Wen","middleName":"","lastName":"Song","suffix":""},{"id":535626203,"identity":"0fab5344-820c-463e-a32d-6ae0d6549e2a","order_by":9,"name":"Yanmei Jiao","email":"","orcid":"","institution":"Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Yanmei","middleName":"","lastName":"Jiao","suffix":""},{"id":535626204,"identity":"df5f367b-ae6a-4a25-b524-2aa782643d52","order_by":10,"name":"Tao Yang","email":"","orcid":"","institution":"Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Yang","suffix":""},{"id":535626205,"identity":"fdf43ab3-8417-420c-a72e-8123f478dee5","order_by":11,"name":"Yue Yuan","email":"","orcid":"","institution":"Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Yuan","suffix":""},{"id":535626206,"identity":"5f887c1c-1861-4874-8f94-fa243105ac5b","order_by":12,"name":"Jin-Hong Yuan","email":"","orcid":"","institution":"Beijing 302 Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jin-Hong","middleName":"","lastName":"Yuan","suffix":""},{"id":535626207,"identity":"d054cab0-b8fe-4a45-bb43-f219d7e82ac7","order_by":13,"name":"Yingying Gao","email":"","orcid":"","institution":"Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Gao","suffix":""},{"id":535626208,"identity":"19897a73-91fd-4e2a-969a-ae366c89337f","order_by":14,"name":"Yangliu Chen","email":"","orcid":"","institution":"Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Yangliu","middleName":"","lastName":"Chen","suffix":""},{"id":535626209,"identity":"058e8da5-2a1b-4b53-99ea-20106ca28d09","order_by":15,"name":"Lin Cao","email":"","orcid":"","institution":"Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Cao","suffix":""},{"id":535626210,"identity":"bf7c31f2-f8a6-4728-a8a8-e9c2a4b26e4f","order_by":16,"name":"Junliang Fu","email":"","orcid":"https://orcid.org/0009-0001-8318-6888","institution":"the Fifth Medical Center of PLA General Hospital, National Clinical Research Center for Infectious Diseases","correspondingAuthor":false,"prefix":"","firstName":"Junliang","middleName":"","lastName":"Fu","suffix":""},{"id":535626211,"identity":"3a02230f-a85b-4ffd-bfb6-c37e7df14f76","order_by":17,"name":"Fu-Sheng Wang","email":"","orcid":"https://orcid.org/0000-0002-8043-6685","institution":"Fifth Medical Center of Chinese PLA General Hospital, Beijing, China; Chinese PLA Medical School, The Fifth Medical Center of PLA General Hospital, Beijing, China.","correspondingAuthor":false,"prefix":"","firstName":"Fu-Sheng","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-10-09 07:00:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7813973/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7813973/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95523489,"identity":"2f75fe88-6b88-49bf-80a5-bf826e89a678","added_by":"auto","created_at":"2025-11-10 09:56:53","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2744320,"visible":true,"origin":"","legend":"","description":"","filename":"figure1.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/1ad9e6037647f2b4d139c522.doc"},{"id":95320858,"identity":"79842e65-350f-49ba-939a-6938d2442092","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152064,"visible":true,"origin":"","legend":"","description":"","filename":"Articalclear1.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/15f91618ed8427d941eca5ca.doc"},{"id":95320863,"identity":"b7460da6-4d74-4398-96a3-2303b1f8902d","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2871808,"visible":true,"origin":"","legend":"","description":"","filename":"figure2.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/7a4e39e04879e363106b1283.doc"},{"id":95320859,"identity":"94238119-6ec7-43d8-9709-8e37301c641a","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11223,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/3bd8a3380b7338d8861e77a8.xlsx"},{"id":95523874,"identity":"1103acde-c58f-4627-a753-546fb273c99f","added_by":"auto","created_at":"2025-11-10 10:01:21","extension":"doc","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2655232,"visible":true,"origin":"","legend":"","description":"","filename":"figure3.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/03dcc04f743668fe83149827.doc"},{"id":95320872,"identity":"38f080fe-aa43-4951-9553-af379bcc5290","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":811520,"visible":true,"origin":"","legend":"","description":"","filename":"figure4.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/f60af6774482d67b5600577a.doc"},{"id":95320878,"identity":"16187dc9-7f4d-408a-95a6-58a667a7dbdb","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":689152,"visible":true,"origin":"","legend":"","description":"","filename":"figure5.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/1952c6e5313b785d2ddd9be8.doc"},{"id":95320874,"identity":"fc134d1f-56b8-44b3-9842-810c5d63d338","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":748544,"visible":true,"origin":"","legend":"","description":"","filename":"figure6.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/414abfcfdd7d0f1e25d95686.doc"},{"id":95523485,"identity":"712e1ee4-9bab-4a7d-83a7-baf3f92e0073","added_by":"auto","created_at":"2025-11-10 09:56:51","extension":"json","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17985,"visible":true,"origin":"","legend":"","description":"","filename":"CMI20251285.json","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/5beeb67f30d74af022535567.json"},{"id":95523771,"identity":"ad6dfa36-f020-425a-9beb-3fb863cc5d03","added_by":"auto","created_at":"2025-11-10 10:00:42","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11849,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/3523658f2a1db3918d1a6e4a.xlsx"},{"id":95523628,"identity":"39c0a792-8532-4546-b0bd-facede30296e","added_by":"auto","created_at":"2025-11-10 09:59:24","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9588,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/13cb60934c5a85baa256ff22.xlsx"},{"id":95523820,"identity":"504e3aaa-6aee-48b6-a650-58f6f27de1d6","added_by":"auto","created_at":"2025-11-10 10:01:01","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9785,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/40403a87abbc96771d44c500.xlsx"},{"id":95320884,"identity":"30dd717b-b90d-4790-812c-e48d5866c56f","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1275192,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure15.docx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/630db696ae654c3196d25223.docx"},{"id":95523515,"identity":"7bf1bfbd-ae18-46a7-ba6c-9af58d99030b","added_by":"auto","created_at":"2025-11-10 09:57:28","extension":"doc","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":777728,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure1.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/a208d97230edd36d734a91e5.doc"},{"id":95523539,"identity":"ddc8439f-dc67-41ef-9adc-289dc43b1cbc","added_by":"auto","created_at":"2025-11-10 09:57:46","extension":"doc","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":668672,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure2.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/ce530dc2e436251bdffbe28d.doc"},{"id":95320882,"identity":"458e0d92-6729-4789-86e2-083aacfba56d","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":797184,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure3.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/4ceb00ac6ef6e7a031668ae6.doc"},{"id":95524390,"identity":"7d2fee72-a3f5-47d9-86ec-fb32e0fd77c3","added_by":"auto","created_at":"2025-11-10 10:02:42","extension":"doc","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":630272,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure4.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/5adcf0feaf2dc4e4d55e198a.doc"},{"id":95524247,"identity":"9d7c7c30-6cbb-4b52-85d3-6353c29d245b","added_by":"auto","created_at":"2025-11-10 10:02:33","extension":"doc","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1664000,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure5.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/8720469571affa457e28f68b.doc"},{"id":95320881,"identity":"a6e65d1d-57cb-48ef-9967-b7376e9f058f","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"xml","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":128261,"visible":true,"origin":"","legend":"","description":"","filename":"CMI202512850enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/c9f1ad8e3e786679c58d6dea.xml"},{"id":95523917,"identity":"a9023f50-c583-4527-91e5-8d80f52d1876","added_by":"auto","created_at":"2025-11-10 10:01:29","extension":"jpeg","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2555974,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/b5d74bbd06875fc3c3443117.jpeg"},{"id":95523597,"identity":"c11674ac-0d47-4cc8-a9c1-975783fdce7b","added_by":"auto","created_at":"2025-11-10 09:58:57","extension":"jpeg","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2682345,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/45cf980ac20e7e39169f4c9b.jpeg"},{"id":95320889,"identity":"e61ca3a5-5fcf-4fd3-b51b-11c9eeb16109","added_by":"auto","created_at":"2025-11-06 16:41:15","extension":"jpeg","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2467404,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/a412b6cd0a51418acf489ead.jpeg"},{"id":95320887,"identity":"7241c696-2282-475f-a4e8-5f92a8cc4e89","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"jpeg","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":638093,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/a2c512860ba9ef8ed377f035.jpeg"},{"id":95523542,"identity":"b89d2dcb-f603-4c7e-8c27-56e7bae82f21","added_by":"auto","created_at":"2025-11-10 09:57:48","extension":"jpeg","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":516409,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/08f46c49972fddd90328939c.jpeg"},{"id":95523455,"identity":"4de92bc1-7d5c-4093-bb73-086ca5fa06e5","added_by":"auto","created_at":"2025-11-10 09:55:38","extension":"jpeg","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":575665,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/a2a9cdd01a68eb4da8b12357.jpeg"},{"id":95524338,"identity":"b0bf91b1-4b5b-4e47-afc6-38c9d66f2daa","added_by":"auto","created_at":"2025-11-10 10:02:37","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":214522,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/b23405b9124119dc28041286.png"},{"id":95320888,"identity":"492aa313-350a-409a-8597-a8dd111c9b13","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":193713,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/84d5db3f9078a4ca4be8ea13.png"},{"id":95523976,"identity":"f61f5bcf-a923-4d14-a980-f4a77daf4472","added_by":"auto","created_at":"2025-11-10 10:01:45","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":243024,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/29f575c83af83ab4ae48236d.png"},{"id":95523746,"identity":"6a8dda14-aa26-4cf3-9e43-368fe6205d0d","added_by":"auto","created_at":"2025-11-10 10:00:33","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102646,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/21335c49fc6fb325339e01dc.png"},{"id":95320893,"identity":"036bd573-c5dd-43eb-947b-bab5a18d1fc4","added_by":"auto","created_at":"2025-11-06 16:41:15","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100095,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/ea40210f604876b2b2943c86.png"},{"id":95524011,"identity":"45d56b4e-1bbe-4816-85e5-66ce0649db55","added_by":"auto","created_at":"2025-11-10 10:01:55","extension":"png","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":112623,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/881a9d6e249973b40c570160.png"},{"id":95523758,"identity":"31618b79-b6ec-4f42-81ef-ef1337db9640","added_by":"auto","created_at":"2025-11-10 10:00:37","extension":"xml","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":122783,"visible":true,"origin":"","legend":"","description":"","filename":"CMI202512850structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/f835567fa297509237cec7dc.xml"},{"id":95320899,"identity":"f58c7adf-faa8-4e17-9e25-80a95de22491","added_by":"auto","created_at":"2025-11-06 16:41:15","extension":"html","order_by":32,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":139665,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/91714abcd68b98a11312dfef.html"},{"id":95320856,"identity":"ee08d08e-8dd6-48aa-a058-97c5c14611c1","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":871203,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSingle-cell transcriptomic profiling of peripheral blood mononuclear cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Flow Chart of the Experiment. (B) UMAP visualisation of 104341 PBMCs clustered into 10 distinct cell subpopulations. (C) Dot plot displaying cluster-defining marker gene expression. Color intensity indicates maximum scaled mean expression, and the size represents the percentage of cells expressing these genes. (D) The distribution of PBMC subsets in cured and uncured groups. (E) Comparative frequencies of B cells between cured and uncured patient groups (left) and spearman correlation analysis between B cells frequencies and baseline HBsAg levels (right). (F) A total of 7080 B cells were isolated and subsequently clustered using UMAP visualization. (G) The distribution of B cells subsets in cured and uncured groups. (H) Canonical markers distinguishing major B cells subsets. Color intensity indicates maximum scaled mean expression, while dot size represents the percentage of cells expressing each gene. Differential analysis of IL4R+SELL+ Naïve B cell frequencies (I), ratio of IL4R-SELL- Naïve B to IL4R+SELL+ Naïve B cell (J) with corresponding Spearman correlations to baseline HBsAg levels. UMAP, uniform manifold approximation and projection. Data are presented as mean ± SEM and differences were analyzed with the Mann–Whitney non-parametric t-test.\u003c/p\u003e","description":"","filename":"figure11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/fe9b2d7dd94680e5ff882447.jpg"},{"id":95524363,"identity":"91678beb-928c-408b-8dd9-1233abf4f98a","added_by":"auto","created_at":"2025-11-10 10:02:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":677025,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeterogeneity of IL4R+SELL+ Naïve B cells and IL4R-SELL- Naïve B cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Dot plot showing differentially marker genes expressed in both IL4R+SELL+ Naïve B and IL4R-SELL- Naïve B cell. (B) Volcano plots of DESeq2 analysis comparing gene expression profiles between IL4R+SELL+ and IL4R-SELL- Naïve B cells (Left panel), representative Gene Set Enrichment Analysis (GSEA) analysis of differentially expressed genes between two clusters (Right panel). Volcano plots of DESeq2 analysis of differentially expressed genes between IL4R+SELL+Naïve B (C) and L4R-SELL- Naïve B cells (D) in cured versus uncured groups (Left panel), GSEA analysis of differentially expressed genes between cured versus uncured for each naïve cluster (Right panel). (E) Comparative pathway activity scores between IL4R+SELL+Naïve B and L4R-SELL- Naïve B cells in cured versus uncured group, analyzed using AUCell.\u003c/p\u003e","description":"","filename":"figure12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/2abd9792a163fd13fd661262.jpg"},{"id":95320854,"identity":"c28afb04-e440-462c-b05d-9554e834aa95","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":895184,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProfiling heterogeneity across memory B cell subsets.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Dot plot showing the expression of differential marker genes across atypical memory B cells., pre-memory B and classical memory B cells. (B) Volcano plots of DESeq2 analysis comparing gene expression profiles among three memory B subsets in cured versus uncured. (C) Representative results of GSEA analysis between three memory clusters. (D) Comparative pathway activity scores for atypical memory B, pre-memory B and classical memory B cells in cured versus uncured group, analyzed using AUCell. (E) The top 25 upregulated genes in IL4R+SELL+ naïve B cells versus IL4R-SELL- naïve B cells were cross-referenced with germinal center B cell-specific genes from the Human Protein Atlas (HPA). All expressed genes demonstrated tissue specificity. Reliability classifications are indicated by evidence codes: dark orange (enhanced validation), orange (supported), light orange (approved), and gray (uncertain). Genes not detected in the analysis were excluded. (F) Monocle pseudotime trajectory analysis of naïve B and memory B cells differentiation. The state with highest IGHD+ B cells percentage are designated as the start (pseudotime = 0). The percentages of cells that developed into different subsets were shown.\u003c/p\u003e","description":"","filename":"figure13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/c566ba5685b0474f405cfdfe.jpg"},{"id":95320861,"identity":"ab095bd1-8f0e-460b-be16-4ae4ad868535","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":386674,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClinical significance of IL4R+SELL+ Naïve B cells in CHB patients with and without functional cure.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Comparative frequencies of IL4R+SELL+ Naïve B cells across clinical response groups (cured, uncured). (B) Pearson correlation between IL4R+SELL+ Naïve B cell frequencies and levels of baseline HBsAg. (C) Comparative frequencies of IL4R-SELL- Naïve B cells among cured and uncured groups. (D) Pearson correlation between IL4R-SELL- Naïve B cell frequencies and levels of baseline HBsAg. Pearson correlation between IL4R+SELL+ Naïve B cell frequency and patient age (E), duration of PEG-IFNα therapy (F), ALT levels at sampling timepoint (G), AST levels at sampling timepoint (H). (I-L) Receiver operating characteristic (ROC) analysis:\u003c/p\u003e\n\u003cp\u003e(I) Predictive value of IL4R+SELL+ Naïve B cell frequency alone, (J) Combined predictive model incorporating IL4R+SELL+ Naïve B cells and baseline HBsAg, (K) Baseline HBsAg alone. Analysis performed in both training (scRNA-seq cohort) and validation cohorts (flow cytometry validation cohort). (L) The predictive accuracy of IL4R+SELL+ Naïve B cells in forecasting treatment outcomes for CHB patients, as measured by the area under the receiver operating characteristic curve (AUROC). Data are presented as mean ± SEM and differences were analyzed with the Mann–Whitney non-parametric t-test.\u003c/p\u003e","description":"","filename":"figure14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/aab78de0086f0b9300a43a9a.jpg"},{"id":95320862,"identity":"b45ed731-ec9e-4726-a0a3-b9a2931fecd1","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":370406,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential effects of serum HBsAg levels on B cell subset.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Frequency comparison between low (\u0026lt;100 IU/mL) and high (\u0026gt;1000 IU/mL) HBsAg groups (left), correlation with quantitative HBsAg levels in low-HBsAg cohort (middle), correlation with quantitative HBsAg levels in high-HBsAg cohort (right). (B) Ratio of IL4R+SELL+ Naïve B cells to IL4R-SELL- Naïve B cells between two groups (left). Ratio correlation with low HBsAg levels (middle) or high HBsAg levels (right). (C) Comparative analysis of IL4R-SELL- Naïve B cell frequencies between low and high HBsAg group (left). Correlation between IL4R-SELL- Naïve B cell frequencies and quantitative low HBsAg levels (middle) and high HBsAg levels (right). Data are presented as mean ± SEM and differences were analyzed with the Mann–Whitney non-parametric t-test.\u003c/p\u003e","description":"","filename":"figure15.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/51db570fd716bbe4da3c338c.jpg"},{"id":95320865,"identity":"b7c2edb3-fbbd-44bb-ab2f-4ceec363f5cb","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":372984,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics of IL4R+SELL+ naïve B cells in CHB patients stratified by post-treatment HBsAg levels after receiving NAs treatment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Flow cytometric analysis of activation markers (MX-1, CD83, CD38, CD69, CD86) expression in IL4R+SELL+ naïve B cells from patients with low HBsAg versus high HBsAg after NAs treatment. Comparative analysis of those genes expression between IL4R+SELL+Naïve B and IL4R-SELL-Naïve B in low HBsAg group (B) and high HBsAg group (C). Data are presented as mean ± SEM and differences were analyzed with the Mann–Whitney non-parametric t-test.\u003c/p\u003e","description":"","filename":"figure16.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/552c895e58dba638757ebbc6.jpg"},{"id":97138349,"identity":"3fad6c8b-4608-4bea-8ce8-f641494857c6","added_by":"auto","created_at":"2025-12-01 09:58:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4628979,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/a3298870-a2ae-4857-a8fb-d10fee5e6ea4.pdf"},{"id":95523950,"identity":"1e21b36c-9d71-424a-b75e-ef1e3e68160c","added_by":"auto","created_at":"2025-11-10 10:01:37","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11223,"visible":true,"origin":"","legend":"Table 1","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/6084b88d782764e5c9a41118.xlsx"},{"id":95320852,"identity":"45709c39-e86f-4ffc-9189-85ade16a13d0","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9785,"visible":true,"origin":"","legend":"Supplementary Table 3","description":"","filename":"SupplementaryTable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/70561cbdd2955265859f989f.xlsx"},{"id":95524219,"identity":"2bba060c-5534-471c-8f54-38079277c055","added_by":"auto","created_at":"2025-11-10 10:02:31","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":9588,"visible":true,"origin":"","legend":"Supplementary Table 2","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/69bd943040526ec3ff070c9f.xlsx"},{"id":95523616,"identity":"b1d94e4e-fbfc-450e-b69e-a53a235f0cb7","added_by":"auto","created_at":"2025-11-10 09:59:14","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":11849,"visible":true,"origin":"","legend":"Supplementary Table 1","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/5236e7031ea486f2b6c256e4.xlsx"},{"id":95320866,"identity":"3a5b9348-07b5-42cc-bd09-cc99458e7677","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":777728,"visible":true,"origin":"","legend":"Supplementary-figure -1","description":"","filename":"Supplementaryfigure1.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/9ffa7096273dc831c858f909.doc"},{"id":95523968,"identity":"f3483e5a-435e-4400-8a9d-c5f44ac70e97","added_by":"auto","created_at":"2025-11-10 10:01:43","extension":"doc","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1664000,"visible":true,"origin":"","legend":"Supplementary-figure -5","description":"","filename":"Supplementaryfigure5.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/565c4009b73215e8c8eede63.doc"},{"id":95523512,"identity":"17b62260-3962-4769-b303-644c44133348","added_by":"auto","created_at":"2025-11-10 09:57:23","extension":"doc","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":630272,"visible":true,"origin":"","legend":"Supplementary-figure -4","description":"","filename":"Supplementaryfigure4.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/31f8762d1466d7888d67b97b.doc"},{"id":95523973,"identity":"1c007aca-97ba-4403-8134-bd6a2add9ed3","added_by":"auto","created_at":"2025-11-10 10:01:44","extension":"doc","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":797184,"visible":true,"origin":"","legend":"Supplementary-figure -3","description":"","filename":"Supplementaryfigure3.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/c810b329d66f55a2bfd14a7b.doc"},{"id":95523936,"identity":"3348b68d-59d5-4c01-adac-2ec10e85bf6c","added_by":"auto","created_at":"2025-11-10 10:01:32","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":1275192,"visible":true,"origin":"","legend":"Supplementary-Figure-1-5","description":"","filename":"SupplementaryFigure15.docx","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/0abf2db1a46baedb66c7373e.docx"},{"id":95320869,"identity":"48d9922c-7234-436c-84bf-767e1043de5a","added_by":"auto","created_at":"2025-11-06 16:41:14","extension":"doc","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":668672,"visible":true,"origin":"","legend":"Supplementary-figure -2","description":"","filename":"Supplementaryfigure2.doc","url":"https://assets-eu.researchsquare.com/files/rs-7813973/v1/5466dab27e8162ed3d925143.doc"}],"financialInterests":"(Not answered)","formattedTitle":"IL-4R+SELL+ Naïve B Cell Expansion correlates with functional cure in PEG-IFNα Treated Chronic Hepatitis B Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe World Health Organization estimates that 257\u0026nbsp;million people worldwide are chronically infected with hepatitis B virus (HBV) \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The development of neutralizing antibodies against HBV surface antigen (HBsAg) represents both a hallmark of viral resolution and a key therapeutic target for functional cure \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. An indispensable contribution of B cell in HBV control is evidenced by observations that B cell-depleting therapies (e.g., rituximab) can trigger fatal HBV reactivation, even in patients with prior serological resolution \u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEarly studies reported hyperactivated circulating B cells in both immune-active and inactive CHB carriers, marked by upregulation of activation-related genes (CD83, CD300c, CXCR4, CD69) and innate immune stimulators \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The coexistence of this systemic B-cell activation with an expanded atypical memory B-cell (AtMBCs) population suggests chronic overstimulation may drive phenotypic and functional exhaustion in CHB \u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Recent advances in methodological breakthroughs and high-dimensional scRNA-seq have uncovered significant heterogeneity in circulating B cells, revealing distinct transcriptomic and proteomic profiles across subsets \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Key findings demonstrate fundamental differences between HBV specific B cells in CHB, the HBcAg-specific B cells predominantly exhibit an IgG\u0026thinsp;+\u0026thinsp;memory phenotype, and the HBsAg-specific B cells show expansion of atypical subsets with impaired antibody production capacity, this functional dichotomy contributes to the persistently low HBsAg seroconversion rates observed in chronic HBV infection \u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Therefore, comprehensive characterization of peripheral blood B cell composition and phenotype is therefore essential to elucidate their role in HBsAg seroclearance and guide the development of targeted immunotherapeutic strategies.\u003c/p\u003e\u003cp\u003eAmong current treatments for CHB, PEG-IFNα remains the most effective strategy due to its higher HBsAg seroclearance rates compared to NAs \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. While PEG-IFNα therapy can only induce favorable responses in a subset of patients, and the immunological mechanisms driving HBsAg seroclearance remain incompletely understood. Recent studies of CHB patients receiving sequential PEG-IFNα-based therapy revealed that functional cure correlates with restored HBsAg-specific memory B cells antibody secretion and distinct phenotypic profiles compared to non-responders \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, na\u0026iuml;ve B cells have been largely neglected in single-cell transcriptomic studies of CHB, owing to their inadvertent exclusion during sample processing and computational analysis. Although HBsAg and HBcAg specific memory B cells have been well characterized in PEG-IFNα-treated patients, the global B cell changes at HBsAg loss remain poorly defined. Through comparative transcriptional profiling of functionally cured versus uncured patients, we sought to identify B cells signatures predictive of PEG-IFNα add-on treatment success.\u003c/p\u003e\u003cp\u003eHere, through integrated scRNA-seq analysis of B cells from NAs-treated CHB patients receiving sequential PEG-IFNα add-on therapy, we provide a comprehensive characterization of human B cells heterogeneity. Our results reveal that enrichment of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells serve as a hallmark of functional cure. The frequency of these cells is inversely correlated with baseline HBsAg levels and predictive of treatment response, supporting their potential use as a predictive biomarker for PEG-IFNα add-on therapy outcomes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003e All studies were approved by the Ethics Committee of Fifth Medical Center of the Chinese PLA General Hospital (KY-2023-12-86-6). All participants were provided with written informed consent at the time of sampling. Peripheral blood mononuclear cells (PBMCs) were separately collected from patients (n\u0026thinsp;=\u0026thinsp;32) who were assessed for functional cure status after completed 96-week follow-up period that counting from therapy initiation, and included both treatment and post-treatment observation. CHB patients receiving NAs monotherapy (n\u0026thinsp;=\u0026thinsp;17) were also included. Thirty-two patients were classified into cured and uncured patients according to the presence of HBsAg seroclearance with or without HBsAg seroconversion, 11 of patients were selected for scRNA-seq analysis (Table\u0026nbsp;1), and 21 patients were collected for flow analysis. Among the 21 patients, 6 of those patients were HBsAg positive at the time of sampling, while converted into HBsAg loss within 96 weeks after PEG-IFNα add-on therapy, and 10 patients were still HBsAg positive after 96 weeks follow-up (Supplementary Table\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e The inclusion criteria for patients received PEG-IFNα add-on therapy: (1) Confirmed CHB diagnosis according to the Guideline of Prevention and Treatment for Chronic Hepatitis B, HBsAg (+) for at least 6months, (2) Age 18\u0026ndash;65 years at enrollment, and received at least 12 months of continuous NAs treatment before receiving PEG-IFNα add-on treatment. (3) Patients exhibited HBsAg levels\u0026thinsp;\u0026lt;\u0026thinsp;1,500 IU/mL, HBeAg-negative, and HBV DNA\u0026thinsp;\u0026lt;\u0026thinsp;40 IU/mL at baseline prior to PEG-IFNα add-on. Exclusion criteria included: (1) HIV infection; (2) decompensated cirrhosis (Child-Pugh class B or C); (3) hepatic failure; (4) hepatocellular carcinoma; (5) history of solid organ transplantation; (6) active autoimmune disorders; (7) severe cardiovascular, cerebrovascular, renal or neurological comorbidities; and (8) current or planned pregnancy. The CHB patients following NAs monotherapy were those who had received continuous NAs therapy for \u0026ge;\u0026thinsp;2 years with sustained virological suppression (HBV DNA\u0026thinsp;\u0026lt;\u0026thinsp;40 IU/mL on \u0026ge;\u0026thinsp;3 consecutive tests). The stop of PEG-IFNα treatment was according to the guidance: If after 24 weeks of treatment, the HBsAg level is \u0026lt;\u0026thinsp;200 IU/mL or shows a decline of 1 log IU/mL, continuation of combined NAs and Peg-IFN-α therapy was recommended for an additional 48\u0026ndash;96 weeks. While, if after 24 weeks of treatment, the HBsAg level remains\u0026thinsp;\u0026ge;\u0026thinsp;200 IU/mL, discontinuation of PEG-IFNα was considered while maintaining NAs monotherapy \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePBMC isolation and processing\u003c/h3\u003e\n\u003cp\u003ePeripheral blood samples were collected in lithium-heparin vacutainer tubes (BD Biosciences, Franklin Lakes, NJ). PBMCs and plasma were isolated by density gradient centrifugation (400 \u0026times; g, 20\u0026deg;C for 20 min) using Ficoll-Paque PLUS (TBD science, TianJin). Following two washes with phosphate-buffered saline (PBS, Gibco), PBMCs were resuspended in medium consisting of 90% heat-inactivated fetal bovine serum (FBS, Gibco, A5669701) and 10% dimethyl sulfoxide (DMSO, Sigma-Aldrich, St. Louis, MO). Cells were aliquoted at 5\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells/mL in cryovials and transferred to a controlled-rate freezing container for gradual cooling before long-term storage in liquid nitrogen.\u003c/p\u003e\n\u003ch3\u003eFlow Cytometry analysis\u003c/h3\u003e\n\u003cp\u003eCryopreserved PBMCs were thawed at 37\u0026deg;C and stained for surface and intracellular markers using optimized protocols. Briefly, cells were resuspended in FACS buffer (2% FBS/PBS) and incubated with pre-titrated surface antibody cocktails (Supplementary Table\u0026nbsp;2) for 30 min at 4\u0026deg;C. After two washes with cold FACS buffer (300 \u0026times; g, 5 min), intracellular staining was performed using BD Cytofix/Cytoperm\u0026trade; Kit with 30 min fixation at RT, followed by Fc receptor blocking (5\u0026micro;L/test, 15 min on 4\u0026deg;C). Cells were then stained with anti-MX-1 primary antibody and FITC-conjugated secondary antibody (each 30 min at 4\u0026deg;C), with Perm/Wash buffer washes between steps. Samples were acquired on a BD FACSAria\u0026trade; III. Data were analyzed in FlowJo software, v10.8.1.\u003c/p\u003e\n\u003ch3\u003eSingle-cell RNA-sequencing data filtering, quality control, and integration\u003c/h3\u003e\n\u003cp\u003eThe isolated cells were sequenced using 10x Chromium Single-cell (10x Genomics, USA, CG000527), according to the manufacturer\u0026rsquo;s instructions. scRNA-seq data filtering and quality control were pre-processed using CellRanger against the GRCh38 human reference. Genes that were detected less than 3 cells were removed. High quality cells were retained with criteria: 200\u0026thinsp;\u0026lt;\u0026thinsp;expressed genes\u0026thinsp;\u0026lt;\u0026thinsp;3000. mitochondrial transcript ratio\u0026thinsp;\u0026lt;\u0026thinsp;10%, 2,000\u0026thinsp;\u0026lt;\u0026thinsp;UMI number\u0026thinsp;\u0026lt;\u0026thinsp;25,000. Potential doublets were identified and removed using DoubletFinder. We then applied Seurat (5.1.0) perform data scaling, transformation, clustering, dimensionality reduction, differential expression analyses and most visualization.\u003c/p\u003e\n\u003ch3\u003eDifferential gene expression, pathways enrichment and HPA analysis\u003c/h3\u003e\n\u003cp\u003eDifferentially expressed gene (DEGs) were identified using the FindMarkers function in Seurat with Wilcoxon rank sum test, and the Benjamini\u0026ndash;Hochberg method was used to adjust the p-values for multiple hypothesis testing. DEGs were filtered using a minimum log2(fold change) of 0.5 and a adjust the p-values of 0.05. Pathway analysis for the DEGs was performed using the function \u0026lsquo;GSEA\u0026rsquo; in clusterProfiler package. Human Protein Atlas (HPA) were referenced to B cells marker genes. The significantly upregulated genes identified in Seurat analysis (p.adj\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were cross-referenced with tissue-specific genes from the HPA database.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSingle-cell trajectory analysis\u003c/h2\u003e\u003cp\u003eIn order to predict the differentiation relationship among the subtypes of B cells, pseudotime analysis was performed by monocle2 v.2.30.0 \u003csup\u003e23,24\u003c/sup\u003e. A set of genes that defined B cells development were ordered for supervised trajectories. These genes included IGH genes, atypical memory B genes, ISGs, na\u0026iuml;ve B, classical memory B, and GC pathway genes. The expression profiles were reduced to 2 dimensions using the DDRTree algorithm in the function \u0026lsquo;reduceDimension\u0026rsquo;. The developmental trajectory was rooted at the predominant IGHD\u0026thinsp;+\u0026thinsp;B cell population (the starting point). The analysis systematically identified branch points corresponding to cell fate decisions during B cells differentiation. The \u0026lsquo;plot_cell_trajectory\u0026rsquo; function was used for visualization of the different states of cells through a pseudotime analysis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCalculation of Function Module Scores for Each Cell\u003c/h3\u003e\n\u003cp\u003eTo quantify pathway activity in B cell subsets, we performed gene signature scoring using the AUCell (v1.24.0). Gene sets were curated from MSigDB (v7.5.1) via the msigdbr package (v7.5.1), focusing on GO terms(C5), including GOBP_RESPONSE_TO_TYPE_I_INTERFERON, GOBP_B_CELL_ACTIVATION,GOBP_OXIDATIVE_PHOSPHORYLATION, and GOBP_ATP_SYNTHESIS_COUPLED_ELECTRON_TRANSPORT. Scores were calculated from log1p-transformed normalized counts, with AUC thresholds automatically determined via distribution knee points (minimum threshold: 5% of maximum theoretical AUC). Cells with \u0026lt;\u0026thinsp;200 detected genes were excluded. Differential activity across subsets was assessed using Wilcoxon rank-sum tests with Benjamini-Hochberg correction (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eGraphPad Prism version 8 and R version 4.3.2 were used for statistical analyses. Continuous variables were expressed as median (interquartile range, IQR). Mann-Whitney-tests were used for comparisons between two groups, and the Wilcoxon signed-rank test was used for matched pairs. Correlations between two quantitative variables were evaluated using Pearson\u0026rsquo;s rank correlation test. Categorical variables were expressed as number (%) and compared by Chi-squared test. At the end time point of follow-up, the area under the receiver-operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value of the target B cell subsets or combine with HBsAg for predicting HBsAg seroclearance was calculated. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, indicated as follows; *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, or ****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eExpansion of peripheral IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B Cells associates with functional cure in CHB patients receiving sequential PEG-IFNα add-on therapy\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe performed single-cell RNA sequencing on peripheral blood mononuclear cells isolated from 11 NAs-treated HBeAg-negative CHB patients with or without functional cure following sequential PEG-IFNα add-on therapy, 6 who achieved functional cure and 5 who did not (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, Table\u0026nbsp;1). All patients were HBeAg-negative at baseline. Although pre-treatment HBsAg levels were slightly lower in cured patients (median 138.4 IU/mL, IQR 28.9\u0026ndash;943.5) compared to uncured patients (median 419.9 IU/mL, IQR 297.8\u0026ndash;1045.0), this difference was not statistically significant. Complete epidemiological, clinical, and virological parameters are simultaneously outlined.\u003c/p\u003e\u003cp\u003eAfter rigorous quality control, cell populations were identified through unsupervised clustering, with clusters expressing canonical lineage markers retained for analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). The proportion of cells within PBMCs was calculated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), the proportion of B cells was significantly elevated in functionally cured patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), and negatively associated with the baseline level of HBsAg (r = -0.747, p\u0026thinsp;=\u0026thinsp;0.088). While other lymphocyte subsets (plasma cells, NK cells, CD4+/CD8\u0026thinsp;+\u0026thinsp;T cells, monocytes, dendritic cells) showed no intergroup differences (Supplementary Fig.\u0026nbsp;1A and 1B), and only the frequency of NK cells showed a negative correlation with baseline level of HBsAg in uncured patients (r = -0.897, p\u0026thinsp;=\u0026thinsp;0.039). These results underscore the potential role of B cells reconstitution in achieving functional cure during PEG-IFNα based add-on therapy.\u003c/p\u003e\u003cp\u003eFollowing rigorous quality control, we successfully segregated B cells from other lymphocyte populations. Unsupervised clustering revealed two distinct na\u0026iuml;ve B cell subsets and three memory B cell subsets, each defined by unique canonical marker expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). One subset of na\u0026iuml;ve B cells enriched for NR4A1, CD72, and PLD4, and the other subset of na\u0026iuml;ve B cells marked by elevated FCER2, IL-4R, SELL, and PLPP5. Pre-memory B cells were identified by higher expression of TNFRSF13B and GPR183, and low expression of IGHD and IGHM. Atypical memory B cells were identified by higher expression of FCRL5, FCRL3 and SOX5, classical memory B cells were identified by higher expression of SELL, COCH, CD80, and CD86, highlighting their transcriptional divergence (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003eNa\u0026iuml;ve B cells make up over 50% of the total peripheral B cell population in our cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). Notably, the interferon therapy induced expansion of B cells in functionally cured patients was driven specifically by an IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell subset. Most importantly, no correlation was observed between IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells and HBsAg level at sampling in uncured patients, while there was a significantly negative correlation between the percentage of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells and the baseline level of HBsAg in cured patients (r = -0.843, p\u0026thinsp;=\u0026thinsp;0.035) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI), and the ratio of IL-4R-SELL- na\u0026iuml;ve B cells to IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells is prone to positively correlated with the baseline level of HBsAg in those patients (r\u0026thinsp;=\u0026thinsp;0.798, p\u0026thinsp;=\u0026thinsp;0.057), highlighting the potential role of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells, and the well balance of IL-4R-SELL- na\u0026iuml;ve B cells to IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells may benefit the favorable outcome of PEG-IFNα treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ). While there is no difference of IL-4R-SELL- na\u0026iuml;ve B cells between the two groups. In our study, memory B cell subsets (pre-memory, atypical, and classical) and terminally differentiated B cells (plasma cells and plasmablast) showed no significant changes between cured and uncured patients. Additionally, no correlation was observed between different memory B cell subsets and HBsAg levels (Supplementary Fig.\u0026nbsp;2A and 2B).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eIL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells show a distinct genes and phenotype state\u003c/h2\u003e\u003cp\u003eWe next compared the differential expression of genes in IL-4R-SELL- na\u0026iuml;ve B cells and IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells. IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells express high level of IL-4R, BACH2, FOXO1, FCRL1, CXCR4, CD83 and CD69. While, IL-4R-SELL- na\u0026iuml;ve B cells express high level of PLD4, CD38, CD72, MZB1, STAT6, IRF4, NR4A1 and JUNB (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Pathway enrichment analysis demonstrated that antigen receptor mediated signaling pathway and B cell receptor signaling pathway were enhanced in IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells, while response to type I interferon, positive regulation of Erbb signaling pathway, and G protein coupled receptor signaling pathway were activated in IL-4R-SELL- na\u0026iuml;ve B cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eFurthermore, we performed comparative analyses of IL-4R-SELL- na\u0026iuml;ve B cells and IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells between cured and uncured patients. The results demonstrated that the key differences between these two na\u0026iuml;ve B cell subsets were primarily metabolic. Specifically, both subsets from cured patients showed significantly enhanced oxidative phosphorylation and electron transport-coupled ATP synthesis compared to those from uncured patients. In contrast, IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells in uncured patients exhibited elevated immune cells activation and protein kinase activity, and IL-4R-SELL- na\u0026iuml;ve B cells displayed upregulation of long chain fatty acid metabolic process and increased activation of NF-kB-inducing kinase activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eWe next evaluated the expression of a broader panel of functional genes in two na\u0026iuml;ve B cell subsets using AUCell scores. Compared to cured patients, uncured patients exhibited enhanced B cell activation and type I interferon responses in both subsets. Conversely, cured patients showed elevated activity in ATP metabolic processes and oxidative phosphorylation across both na\u0026iuml;ve B cell populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe interferon signaling pathway of memory B cells remains persistently activated in uncured patients.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe then investigated the characteristics of memory B cells. Pre-memory B cells characterized by the specific expression of FOXP1, CXCR4, TNFRSF13B, CD83, PAX5, and GPR183, and atypical memory B cells expressed higher levels of ITGB2, FCRL3, TBX21 and IGHG3, classical memory expressed CD80, CD86, COCH, DUSP2, XAF1, BCL2A1 and IRF4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Although no differences of the frequency were observed in pre-memory, classical memory, or atypical memory B cells between cured and uncured patient groups, these cell populations exhibited distinct genes and signaling pathway profiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eThe electron transport-coupled ATP synthesis pathway was consistently upregulated across all memory B cell subsets in cured patients. In contrast, atypical memory B cells from uncured patients showed enhanced positive regulation of phagocytosis, while classical memory and pre-memory B cells exhibited heightened type I interferon response pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Comparative analysis revealed significant differences in signaling pathway activity between cured and uncured patients. In uncured patients, memory B cells exhibited elevated scores for type I interferon response and B cell activation. Conversely, cured patients showed increased activity in ATP synthesis-coupled electron transport and oxidative phosphorylation pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eIn addition, we identified the top 25 up-regulated genes in IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells inverse IL4-R-SELL- na\u0026iuml;ve B cells, which encode proteins previously detected in germinal center (GC) B cells according to the Human Protein Atlas (HPA) database. Notably, IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells exhibited greater similarity to GC B cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). To further elucidate the state transition trajectories of na\u0026iuml;ve and memory B cells, we reconstructed the developmental trajectories of B cells differentiation. Strikingly, in the uncured patients, na\u0026iuml;ve B cells exhibited a developmental trajectory to the atypical memory lineage. In contrast, in the cured patients, na\u0026iuml;ve B cells exhibited a developmental trajectory to the classical memory lineage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003e\u003cb\u003eHigh IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B Cell Frequency Predicts Better PEG-IFN\u003c/b\u003eα \u003cb\u003eTherapy Response.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe employed flow cytometry to characterize na\u0026iuml;ve and memory B cell subsets in CHB patients undergoing sequential PEG-IFNα add-on therapy following NAs treatment. Peripheral blood samples were collected at different time points during PEG-IFNα add-on therapy, with functional cure defined as HBsAg loss confirmed at 96-week follow-up. Based on treatment outcomes, patients were stratified into functional cure (n\u0026thinsp;=\u0026thinsp;11, six achieved a functional cure after sample collection, and five at the time of collection, and 10 uncured patients). Baseline demographic, clinical, and laboratory characteristics are detailed in Supplementary Table\u0026nbsp;1.\u003c/p\u003e\u003cp\u003eBased on single-cell clustering patterns of na\u0026iuml;ve B cells, we further stratified total na\u0026iuml;ve B cells using IL-4R and SELL markers. Comparative analysis across functionally cured and uncured groups revealed significantly higher frequencies of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells in cured patients (p\u0026thinsp;=\u0026thinsp;0.006, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Correlation analyses demonstrated inverse relationships between IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell frequency and baseline HBsAg levels (r = -0.631, p\u0026thinsp;=\u0026thinsp;0.002; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), and HBsAg levels at sampling (r = -0.641, p\u0026thinsp;=\u0026thinsp;0.008) (Supplementary Fig.\u0026nbsp;3A).\u003c/p\u003e\u003cp\u003eThe uncured patients exhibited a higher percentage of IL-4R-SELL- na\u0026iuml;ve B cells compared to cured patients (p\u0026thinsp;=\u0026thinsp;0.06) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). This subset showed a positive correlation with baseline HBsAg levels (r\u0026thinsp;=\u0026thinsp;0.681, p\u0026thinsp;=\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) and sampling timepoint (r\u0026thinsp;=\u0026thinsp;0.652, p\u0026thinsp;=\u0026thinsp;0.006; Supplementary Fig.\u0026nbsp;3B). Notably, the ratio of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;to IL-4R-SELL- na\u0026iuml;ve B cells was elevated in cured patients versus uncured patients (p\u0026thinsp;=\u0026thinsp;0.004) and demonstrated a negative correlation with baseline HBsAg levels (r = -0.496, p\u0026thinsp;=\u0026thinsp;0.022) (Supplementary Fig.\u0026nbsp;3C and 3D). Furthermore, the percentage of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells showed no correlation with age, duration of PEG-IFNα treatment, ALT, and AST levels (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH). Initial flow cytometric analysis of CD21 and CD27 expression showed no significant differences in the frequencies of na\u0026iuml;ve B cells (CD19\u0026thinsp;+\u0026thinsp;CD21\u0026thinsp;+\u0026thinsp;CD27-), resting memory B cells (CD19\u0026thinsp;+\u0026thinsp;CD21-CD27+), classical memory B cells (CD19\u0026thinsp;+\u0026thinsp;CD21\u0026thinsp;+\u0026thinsp;CD27+), and atypical memory B cells (CD19\u0026thinsp;+\u0026thinsp;CD21-CD27-) (Supplementary Fig.\u0026nbsp;3E to 3H). Furthermore, the percentage of total na\u0026iuml;ve B cells negatively correlated with HBsAg levels at the time of baseline (r = -0.568, p\u0026thinsp;=\u0026thinsp;0.007), and the percentage of atypical memory B cells positively correlated with HBsAg levels at the time of baseline (r\u0026thinsp;=\u0026thinsp;0.473, p\u0026thinsp;=\u0026thinsp;0.030) (Supplementary Fig.\u0026nbsp;3I to 3L).\u003c/p\u003e\u003cp\u003eMost importantly, we conducted the ROC (Receiver Operating Characteristic) analyses, both separately and in combination on HBsAg levels and the percentage of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells across all patients. The results indicated that IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells alone predicted treatment outcome with an ROC of 0.846 (p\u0026thinsp;=\u0026thinsp;0.008) in the flow cytometry validation cohort and ROC of 0.90 (p\u0026thinsp;=\u0026thinsp;0.029) in the scRNA-seq training cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI). Combining IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells with HBsAg further improved predictive efficiency, achieving an AUC of 0.891 (p\u0026thinsp;=\u0026thinsp;0.003) in the flow cytometry validation cohort and 0.867 (p\u0026thinsp;=\u0026thinsp;0.045) in the scRNA-seq training cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ). In contrast, HBsAg alone showed no significant predictive value (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eL).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eIL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells are associated with the level of HBsAg in patients with CHB\u003c/h2\u003e\u003cp\u003eThe percentage of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells showed no correlation with age, duration of PEG-IFNα treatment, ALT, and AST levels. However, this B cell subset demonstrated positive correlations with both pre-treatment HBsAg levels and HBsAg at sampling timepoints. Based on these findings, we enrolled NAs-treated CHB patients stratified by different HBsAg levels. Detailed patient characteristics are provided in Supplementary Table\u0026nbsp;2. Based on HBsAg levels, patients were stratified into two groups, the low HBsAg group (\u0026lt;\u0026thinsp;100 IU/ml; median 64.6 IU/ml, IQR 23.3\u0026ndash;86.0) and the high HBsAg group (\u0026gt;\u0026thinsp;1000 IU/ml; median 2497.0 IU/ml, IQR 1915.0-3725.0).\u003c/p\u003e\u003cp\u003eFlow cytometry analysis revealed distinct B cell subset patterns. As indicated that the patients with low HBsAg levels exhibited significantly higher percentages of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells (p\u0026thinsp;=\u0026thinsp;0.006) and elevated IL-4R\u0026thinsp;+\u0026thinsp;SELL+/IL-4R-SELL- na\u0026iuml;ve B cell ratio (p\u0026thinsp;=\u0026thinsp;0.015), both parameters demonstrated significant inverse correlation with HBsAg levels at sampling (r = -0.652, p\u0026thinsp;=\u0026thinsp;0.079; r = -0.813, p\u0026thinsp;=\u0026thinsp;0.014) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Conversely, these patients with high HBsAg exhibited increased frequency of both IL-4R-SELL- na\u0026iuml;ve B cells, and the IL-4R-SELL- population showed a positive correlation with HBsAg level at sampling (r\u0026thinsp;=\u0026thinsp;0.893, p\u0026thinsp;=\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Our analysis of memory B cell subsets in NAs-treated patients showed no significant differences in memory B cell percentages between patients with low and high HBsAg levels (Supplementary Fig.\u0026nbsp;4A). In addition, no significant correlations were found between memory B cell subset percentages, and HBsAg levels at any sampling timepoint (Supplementary Fig.\u0026nbsp;4B and 4C).\u003c/p\u003e\u003cp\u003eWe further characterized the phenotype markers associated with IFN pathway (MX-1) and cellular activation (CD83, CD38, CD69, CD86) in na\u0026iuml;ve B cells. We found that the patients with low HBsAg after NAs treatment have high percentage of MX-1\u0026thinsp;+\u0026thinsp;IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells (p\u0026thinsp;=\u0026thinsp;0.005), and CD83\u0026thinsp;+\u0026thinsp;IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells (p\u0026thinsp;=\u0026thinsp;0.005; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA) than those patients with high HBsAg. In addition, in patients with low HBsAg level, the IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells expressed higher level of CD83 (p\u0026thinsp;=\u0026thinsp;0.002) and lower level of CD86 (p\u0026thinsp;=\u0026thinsp;0.021) than non- IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). While in patients with high HBsAg level, the IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells expressed lower level of MX-1 (p\u0026thinsp;=\u0026thinsp;0.043), and higher level of CD83 (p\u0026thinsp;=\u0026thinsp;0.02), CD38 (p\u0026thinsp;=\u0026thinsp;0.057) and CD69 (p\u0026thinsp;=\u0026thinsp;0.008) versus IL-4R- SELL- counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDespite PEG-IFNα treatment, only a minority of adult CHB patients with relatively low HBsAg levels achieve a functional cure \u003csup\u003e\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Identifying reliable predictors of response beyond HBsAg levels is crucial to optimize PEG-IFNα therapy for patients most likely to benefit. Based on this rationale, we sought to identify cellular biomarkers associated with PEG-IFNα treatment response, enabling targeted treatment of CHB patients most likely to benefit. B cells play a pivotal role in achieving functional cure for CHB by sustaining HBV-specific immune responses, primarily via antibody production. The marked heterogeneity observed in B cell subset distribution and gene expression patterns during HBV infection suggests that different phenotypic subsets may play functionally distinct or antagonistic roles, while also highlighting potential therapeutic opportunities to selectively enhance protective B cell compartments. However, owing to their low frequency and marked functional heterogeneity, B cells remain relatively understudied in the context of HBV infection. By leveraging single-cell analysis of CHB patients receiving sequential PEG-IFNα combination therapy, we identify IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell expansion as a defining feature of functional cure. This clinically favorable subset exhibits distinct transcriptional signatures, phenotypic plasticity, and represents a potential biomarker for functional cure prediction.\u003c/p\u003e\u003cp\u003ePrevious studies demonstrated that CHB patients exhibited increased total atypical memory B cells, which positively correlated with HBV DNA and ALT levels but not with HBsAg \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In contrast, our study did not detect significant associations between any memory B cell subsets and HBV DNA, ALT, or HBsAg levels in PEG-IFNα treated CHB patients. Notably, our cohort exclusively comprised an advantaged population with undetectable HBV DNA and low HBsAg levels after NAs therapy, suggesting that memory B cell profiling might not reliably reflect interferon treatment responsiveness in those patients. Strikingly, we found two subsets of na\u0026iuml;ve B cells with transcriptomic and functional divergence, and the frequency of protective IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells was significantly elevated in patients achieving functional cure, showing an inverse correlation with baseline HBsAg levels that measured at PEG-IFNα initiation, and the level of HBsAg at sampling. Notably, IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell frequency exhibited consistent predictive value across both our scRNA-seq cohort and flow cytometry validation cohorts. In contrast, baseline HBsAg levels at the time of PEG-IFNα administration failed to show significant predictive power in the flow cytometry validation cohort. These findings partially explain why some treatment-advantaged patients with low initial HBsAg fail to achieve HBsAg loss following interferon therapy. Of particular note, the combination of HBsAg level and IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell frequency exhibits superior predictive performance for functional cure, these findings imply that integrating HBsAg with additional immune cell biomarkers could improve its predictive value in assessing treatment efficacy. While further investigation is needed to elucidate whether the observed association reflects selection of pre-existing high-frequency na\u0026iuml;ve B cell subsets or interferon-driven expansion of these populations, our results highlight the critical, yet underappreciated, role of na\u0026iuml;ve B cells in mediating HBV functional cure.\u003c/p\u003e\u003cp\u003eCurrent evidence strongly confirms the critical link between HBsAg levels and HBV functional cure. Additionally, pre-treatment autoantibody screening was associated with treatment responses in PEG-IFNα therapy \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Our single-cell RNA sequencing revealed a significant inverse correlation between IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell frequency and baseline HBsAg titers during interferon therapy, indicating potential regulation of this B cell subsets by HBsAg. To investigate the association between HBsAg levels and na\u0026iuml;ve B cell frequency independent of IFNα effects, we analyzed IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells in CHB patients received NAs treatment. Notably, IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells were significantly enriched in patients with low HBsAg levels (\u0026lt;\u0026thinsp;100 IU/mL) compared to those with higher HBsAg levels (\u0026gt;\u0026thinsp;1000 IU/mL). So reduced HBsAg levels may create a permissive environment for restoring B cells function, and exogenous interferon administration under these conditions potently amplifies antiviral responses. This discovery identifies a critical \"immune reconstitution window\" in hepatitis B therapy, providing a mechanistic framework for integrating antiviral and immunomodulatory strategies. In addition, contrary to established reports of age-dependent interferon responsiveness, our cured cohort demonstrated comparable outcomes across age groups. The age-independent nature of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell frequencies in patients further suggests these protective B cell subsets may operate through mechanisms distinct from classical, age-associated HBsAg-specific T cell immunity \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eData from chronic hepatitis B patients indicate a deficiency in endogenous IFNα during persistent infection, yet these individuals retain the capacity to respond to exogenous IFNα \u003csup\u003e31,32\u003c/sup\u003e. Our study aims to define the distinct interferon transcriptomic signatures of na\u0026iuml;ve and memory B cells in functionally cured versus uncured patients. Comparative analysis revealed fundamental differences in B cell profiles, the cured patients exhibited upregulation of bioenergetic pathways (e.g., oxidative phosphorylation and ATP synthesis), whereas uncured patients showed persistent IFN pathway activation across both na\u0026iuml;ve and memory B cell subsets. Notably, type I interferons have been shown to induce an epigenetically distinct memory B cell subset during chronic viral infection \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, while sustained IFN signaling is associated with CD4\u0026thinsp;+\u0026thinsp;T cell exhaustion and impaired na\u0026iuml;ve B cell development in HIV-1 infection \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Our findings further suggest that persistent IFN activation may limit treatment efficacy, even in patients who otherwise exhibit favorable responses. Although the precise molecular initiators and mechanisms driving beneficial interferon signaling in cured individuals remain incompletely understood, targeted modulation of this pathway may enhance HBsAg seroclearance. Emerging evidence suggests that reducing SOCS2 levels, a key negative feedback regulator of IFN signaling could improve cure rates \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. However, further mechanistic studies are needed to validate this therapeutic strategy.\u003c/p\u003e\u003cp\u003eOur study has some limitations. First, our data confirm the protective role and predictive value of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells for functional cure. However, the dynamic changes of these protective B cells during interferon therapy remain unmonitored. Our study cannot currently differentiate whether the effects stem from intrinsic na\u0026iuml;ve B cell levels or interferon treatment efficacy. Second, serial measurements of immunoregulatory cytokines (e.g., IL-4, IL-21) associated with na\u0026iuml;ve B cell differentiation were unavailable due to missing pre-/mid-treatment samples, limiting our understanding of host-IFNα interactions. Third, our analysis was limited to total B cell populations rather than antigen-specific subsets, precluding assessment of HBsAg-specific B cell dynamics. Additionally, the exclusive focus on peripheral blood B cells may not fully capture liver-localized immunological processes critical for HBV seroclearance. Finally, to our knowledge, no prior studies have comprehensively characterized na\u0026iuml;ve B cell dynamics in PEG-IFNα treated CHB patients stratified by functional cure status. As such, our clustering approach while revealing novel subsets may have underestimated.\u003c/p\u003e\u003cp\u003eOverall, for a long time, there has been a lack of reliable predictive immunological markers to evaluate treatment efficacy during interferon therapy. In this study, we identified a protective subset of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells in the interferon-treated cohort, characterized the phenotypic and functional features of these cells, and assessed their value in predicting functional cure. This research not only enhances our understanding of B cells but also contributes to the accurate prediction of interferon treatment outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest\u003c/h2\u003e\n\u003cp\u003eAll authors declare no conflict of interest related to this publication.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; Contributions\u003c/h2\u003e\n\u003cp\u003eGuarantor of study: Runan Xu, Fu-Sheng Wang; Study concept and design: Runan Xu, Fu-sheng Wang; Data collection and/or interpretation: Honghong Liu, Huan Wang, Yue Yuan, Jinhong Yuan, Yingying Gao, Yangliu Chen, Lin Cao; Technical support: Cheng Zhen; Data analysis: Lili Tang, Chunmei Bao; Drafting of manuscript: Runan Xu, Lili Tang; Critical revision of manuscript: Chao Zhang, Yang Zhang, Jinwen Song, Yanmei Jiao, Tao Yang, Jun-Liang Fu. All authors read and approved the final manuscript. Lili Tang* and Chunmei Bao* contributed equally to this study.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThis work was supported by grants from the National Key Research and Development Program of China (no.2023YFC2308100) and National Natural Science Foundation of China (no.82130019). We thank all patients who participated in this study. We would like to thank Dr. Liguo Zhang for providing the recombinant human MX-1 protein.\u003c/p\u003e\n\u003ch2\u003eData Availability Statements\u003c/h2\u003e\n\u003cp\u003eThe scRNAseq datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePolaris Observatory, C. Global prevalence, treatment, and prevention of hepatitis B virus infection in 2016: a modelling study. \u003cem\u003eLancet Gastroenterol Hepatol\u003c/em\u003e 3, 383\u0026ndash;403, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2468-1253(18)30056-6\u003c/span\u003e\u003cspan address=\"10.1016/S2468-1253(18)30056-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang, D. \u003cem\u003eet al.\u003c/em\u003e End-of-treatment HBcrAg and HBsAb levels identify durable functional cure after Peg-IFN-based therapy in patients with CHB. \u003cem\u003eJ Hepatol\u003c/em\u003e 77, 42\u0026ndash;54, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2022.01.021\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2022.01.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHepatology, C. S. o. I. D. S. o. Guidelines for the prevention and treatment of chronic hepatitis B (version 2022). \u003cem\u003eChinese Journal of Infectious Diseases [Chinese]\u003c/em\u003e 30(12), 1309\u0026ndash;1331, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3760/cma.j.cn501113-20221204-00607\u003c/span\u003e\u003cspan address=\"10.3760/cma.j.cn501113-20221204-00607\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang, H. \u003cem\u003eet al.\u003c/em\u003e Entecavir vs lamivudine for prevention of hepatitis B virus reactivation among patients with untreated diffuse large B-cell lymphoma receiving R-CHOP chemotherapy: a randomized clinical trial. \u003cem\u003eJAMA\u003c/em\u003e 312, 2521\u0026ndash;2530, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2014.15704\u003c/span\u003e\u003cspan address=\"10.1001/jama.2014.15704\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLoomba, R. \u0026amp; Liang, T. J. Hepatitis B Reactivation Associated With Immune Suppressive and Biological Modifier Therapies: Current Concepts, Management Strategies, and Future Directions. \u003cem\u003eGastroenterology\u003c/em\u003e 152, 1297\u0026ndash;1309, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1053/j.gastro.2017.02.009\u003c/span\u003e\u003cspan address=\"10.1053/j.gastro.2017.02.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKusumoto, S. \u003cem\u003eet al.\u003c/em\u003e Risk of HBV reactivation in patients with B-cell lymphomas receiving obinutuzumab or rituximab immunochemotherapy. \u003cem\u003eBlood\u003c/em\u003e 133, 137\u0026ndash;146, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1182/blood-2018-04-848044\u003c/span\u003e\u003cspan address=\"10.1182/blood-2018-04-848044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDervite, I., Hober, D. \u0026amp; Morel, P. Acute hepatitis B in a patient with antibodies to hepatitis B surface antigen who was receiving rituximab. \u003cem\u003eN Engl J Med\u003c/em\u003e 344, 68\u0026ndash;69, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJM200101043440120\u003c/span\u003e\u003cspan address=\"10.1056/NEJM200101043440120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOliviero, B. \u003cem\u003eet al.\u003c/em\u003e Enhanced B-cell differentiation and reduced proliferative capacity in chronic hepatitis C and chronic hepatitis B virus infections. \u003cem\u003eJ Hepatol\u003c/em\u003e 55, 53\u0026ndash;60, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2010.10.016\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2010.10.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu, X. \u003cem\u003eet al.\u003c/em\u003e Reversal of B-cell hyperactivation and functional impairment is associated with HBsAg seroconversion in chronic hepatitis B patients. \u003cem\u003eCell Mol Immunol\u003c/em\u003e 12, 309\u0026ndash;316, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/cmi.2015.25\u003c/span\u003e\u003cspan address=\"10.1038/cmi.2015.25\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVanwolleghem, T. \u003cem\u003eet al.\u003c/em\u003e Re-evaluation of hepatitis B virus clinical phases by systems biology identifies unappreciated roles for the innate immune response and B cells. \u003cem\u003eHepatology\u003c/em\u003e 62, 87\u0026ndash;100, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hep.27805\u003c/span\u003e\u003cspan address=\"10.1002/hep.27805\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalimzadeh, L. \u003cem\u003eet al.\u003c/em\u003e PD-1 blockade partially recovers dysfunctional virus-specific B cells in chronic hepatitis B infection. \u003cem\u003eJ Clin Invest\u003c/em\u003e 128, 4573\u0026ndash;4587, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1172/JCI121957\u003c/span\u003e\u003cspan address=\"10.1172/JCI121957\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBurton, A. R. \u003cem\u003eet al.\u003c/em\u003e Circulating and intrahepatic antiviral B cells are defective in hepatitis B. \u003cem\u003eJ Clin Invest\u003c/em\u003e 128, 4588\u0026ndash;4603, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1172/JCI121960\u003c/span\u003e\u003cspan address=\"10.1172/JCI121960\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVanwolleghem, T. \u003cem\u003eet al.\u003c/em\u003e Hepatitis B core-specific memory B cell responses associate with clinical parameters in patients with chronic HBV. \u003cem\u003eJ Hepatol\u003c/em\u003e 73, 52\u0026ndash;61, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2020.01.024\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2020.01.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDusheiko, G. M., Hoofnagle, J. H., Cooksley, W. G., James, S. P. \u0026amp; Jones, E. A. Synthesis of antibodies to hepatitis B virus by cultured lymphocytes from chronic hepatitis B surface antigen carriers. \u003cem\u003eJ Clin Invest\u003c/em\u003e 71, 1104\u0026ndash;1113, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1172/jci110860\u003c/span\u003e\u003cspan address=\"10.1172/jci110860\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1983).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVanwolleghem, T., Adomati, T., Van Hees, S. \u0026amp; Janssen, H. L. A. Humoral immunity in hepatitis B virus infection: Rehabilitating the B in HBV. \u003cem\u003eJHEP Rep\u003c/em\u003e 4, 100398, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhepr.2021.100398\u003c/span\u003e\u003cspan address=\"10.1016/j.jhepr.2021.100398\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe Bert, N. \u003cem\u003eet al.\u003c/em\u003e Comparative characterization of B cells specific for HBV nucleocapsid and envelope proteins in patients with chronic hepatitis B. \u003cem\u003eJ Hepatol\u003c/em\u003e 72, 34\u0026ndash;44, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2019.07.015\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2019.07.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, J. W. \u003cem\u003eet al.\u003c/em\u003e Varied immune responses of HBV-specific B cells in patients undergoing pegylated interferon-alpha treatment for chronic hepatitis B. \u003cem\u003eJ Hepatol\u003c/em\u003e 81, 960\u0026ndash;970, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2024.06.033\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2024.06.033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eButi, M. \u003cem\u003eet al.\u003c/em\u003e Sequential Peg-IFN after bepirovirsen may reduce post-treatment relapse in chronic hepatitis B. \u003cem\u003eJ Hepatol\u003c/em\u003e 82, 222\u0026ndash;234, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2024.08.010\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2024.08.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, F. \u003cem\u003eet al.\u003c/em\u003e PegIFN alpha-2a reduces relapse in HBeAg-negative patients after nucleo(s)tide analogue cessation: A randomized-controlled trial. \u003cem\u003eJ Hepatol\u003c/em\u003e 82, 211\u0026ndash;221, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2024.07.019\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2024.07.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVecchi, A. \u003cem\u003eet al.\u003c/em\u003e HBcrAg values may predict virological and immunological responses to pegIFN-alpha in NUC-suppressed HBeAg-negative chronic hepatitis B. \u003cem\u003eGut\u003c/em\u003e 73, 1737\u0026ndash;1748, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/gutjnl-2024-332290\u003c/span\u003e\u003cspan address=\"10.1136/gutjnl-2024-332290\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGu, S. \u003cem\u003eet al.\u003c/em\u003e Circulating HBsAg-specific B cells are partially rescued in chronically HBV-infected patients with functional cure. \u003cem\u003eEmerg Microbes Infect\u003c/em\u003e 13, 2409350, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/22221751.2024.2409350\u003c/span\u003e\u003cspan address=\"10.1080/22221751.2024.2409350\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTian, C. \u003cem\u003eet al.\u003c/em\u003e Use of ELISpot assay to study HBs-specific B cell responses in vaccinated and HBV infected humans. \u003cem\u003eEmerg Microbes Infect\u003c/em\u003e 7, 16, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41426-018-0034-0\u003c/span\u003e\u003cspan address=\"10.1038/s41426-018-0034-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTrapnell, C. \u003cem\u003eet al.\u003c/em\u003e The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. \u003cem\u003eNat Biotechnol\u003c/em\u003e 32, 381\u0026ndash;386, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nbt.2859\u003c/span\u003e\u003cspan address=\"10.1038/nbt.2859\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQiu, X. \u003cem\u003eet al.\u003c/em\u003e Reversed graph embedding resolves complex single-cell trajectories. \u003cem\u003eNat Methods\u003c/em\u003e 14, 979\u0026ndash;982, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nmeth.4402\u003c/span\u003e\u003cspan address=\"10.1038/nmeth.4402\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWong, G. L. H., Gane, E. \u0026amp; Lok, A. S. F. How to achieve functional cure of HBV: Stopping NUCs, adding interferon or new drug development? \u003cem\u003eJ Hepatol\u003c/em\u003e 76, 1249\u0026ndash;1262, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2021.11.024\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2021.11.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChu, J. H. \u003cem\u003eet al.\u003c/em\u003e Real-world study on HBsAg loss of combination therapy in HBeAg-negative chronic hepatitis B patients. \u003cem\u003eJ Viral Hepat\u003c/em\u003e 29, 765\u0026ndash;776, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jvh.13722\u003c/span\u003e\u003cspan address=\"10.1111/jvh.13722\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeng, Q. L. \u003cem\u003eet al.\u003c/em\u003e Short-term Peginterferon-Induced High Functional Cure Rate in Inactive Chronic Hepatitis B Virus Carriers With Low Surface Antigen Levels. \u003cem\u003eOpen Forum Infect Dis\u003c/em\u003e 7, ofaa208, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ofid/ofaa208\u003c/span\u003e\u003cspan address=\"10.1093/ofid/ofaa208\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFink, D. L. \u003cem\u003eet al.\u003c/em\u003e Auto-antibodies against interferons are common in people living with chronic hepatitis B virus infection and associate with PegIFNalpha non-response. \u003cem\u003eJHEP Rep\u003c/em\u003e 7, 101382, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhepr.2025.101382\u003c/span\u003e\u003cspan address=\"10.1016/j.jhepr.2025.101382\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFerri, D. M. \u003cem\u003eet al.\u003c/em\u003e Elevated Levels of Interferon-alpha Act Directly on B Cells to Breach Multiple Tolerance Mechanisms Promoting Autoantibody Production. \u003cem\u003eArthritis Rheumatol\u003c/em\u003e 75, 1542\u0026ndash;1555, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/art.42482\u003c/span\u003e\u003cspan address=\"10.1002/art.42482\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe Bert, N. \u003cem\u003eet al.\u003c/em\u003e Effects of Hepatitis B Surface Antigen on Virus-Specific and Global T Cells in Patients With Chronic Hepatitis B Virus infection. \u003cem\u003eGastroenterology\u003c/em\u003e 159, 652\u0026ndash;664, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1053/j.gastro.2020.04.019\u003c/span\u003e\u003cspan address=\"10.1053/j.gastro.2020.04.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOnji, M., Lever, A. M., Saito, I. \u0026amp; Thomas, H. C. Defective response to interferons in cells transfected with the hepatitis B virus genome. \u003cem\u003eHepatology\u003c/em\u003e 9, 92\u0026ndash;96, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hep.1840090115\u003c/span\u003e\u003cspan address=\"10.1002/hep.1840090115\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1989).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavis, G. L. \u0026amp; Hoofnagle, J. H. Interferon in viral hepatitis: role in pathogenesis and treatment. \u003cem\u003eHepatology\u003c/em\u003e 6, 1038\u0026ndash;1041, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hep.1840060537\u003c/span\u003e\u003cspan address=\"10.1002/hep.1840060537\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1986).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCooper, L. \u003cem\u003eet al.\u003c/em\u003e Type I interferons induce an epigenetically distinct memory B cell subset in chronic viral infection. \u003cem\u003eImmunity\u003c/em\u003e 57, 1037\u0026ndash;1055 e1036, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.immuni.2024.03.016\u003c/span\u003e\u003cspan address=\"10.1016/j.immuni.2024.03.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu, X. \u003cem\u003eet al.\u003c/em\u003e Single-cell multi-omics profiling uncovers the immune heterogeneity in HIV-infected immunological non-responders. \u003cem\u003eEBioMedicine\u003c/em\u003e 115, 105667, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ebiom.2025.105667\u003c/span\u003e\u003cspan address=\"10.1016/j.ebiom.2025.105667\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuan, G. \u003cem\u003eet al.\u003c/em\u003e Higher TP53BP2 expression is associated with HBsAg loss in peginterferon-alpha-treated patients with chronic hepatitis B. \u003cem\u003eJ Hepatol\u003c/em\u003e 80, 41\u0026ndash;52, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2023.09.039\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2023.09.039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7813973/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7813973/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDuring chronic hepatitis B (CHB) infection, B cell dysfunction is a key contributor to viral persistence. Pegylated interferon alpha (PEG-IFNα) acts as an effective therapeutic agent for CHB by restoring immune responses directed against HBV, however, a comprehensive landscape of the B-cell responses associated with functional cure has not been fully elucidated. In this study, we employed single-cell RNA sequencing (scRNA-seq) and flow cytometry to quantitatively assess the B-cell subsets in nucleos(t)ide analog (NAs)-treated CHB patients receiving sequential PEG-IFNα add-on therapy. We identified two functionally distinct na\u0026iuml;ve B cell subsets (IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;and IL-4R-SELL-) and three memory B cell populations in peripheral blood. Patients who achieved a functional cure displayed significantly elevated frequencies of total B cells and the IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cell subset, whereas memory B cell frequencies remained comparable between groups. In contrast to cured patients, uncured individuals exhibited sustained activation of type I interferon response pathways in both naive and memory B cells, which may be a key mechanism of B cell dysfunction. Notably, the frequency of IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells during the treatment was inversely correlated with baseline HBsAg levels at the initiation of PEG-IFNα therapy, and has high predictive value for HBsAg loss following PEG-IFNα therapy. Our results indicate that CHB patients attaining functional cure after PEG-IFNα add-on therapy undergo a distinct B cell reconstitution, characterized by a pronounced expansion of peripheral IL-4R\u0026thinsp;+\u0026thinsp;SELL\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve B cells. This finding highlights its dual significance as both a novel immunological biomarker and a potential therapeutic target for CHB functional cure.\u003c/p\u003e","manuscriptTitle":"IL-4R+SELL+ Naïve B Cell Expansion correlates with functional cure in PEG-IFNα Treated Chronic Hepatitis B Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 16:41:09","doi":"10.21203/rs.3.rs-7813973/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d00f0397-3768-4fd9-83e5-a568ca613028","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56948413,"name":"Biological sciences/Immunology/Infectious diseases/Hepatitis/Viral hepatitis/Hepatitis B"},{"id":56948414,"name":"Biological sciences/Immunology/Lymphocytes/B cells"}],"tags":[],"updatedAt":"2025-11-28T08:50:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 16:41:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7813973","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7813973","identity":"rs-7813973","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}