Single-Cell Transcriptomic Landscape of Intrahepatic B Cells in NASH

Single-Cell Transcriptomic Landscape of Intrahepatic B Cells in NASH | 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 Research Article Single-Cell Transcriptomic Landscape of Intrahepatic B Cells in NASH Jia-Chun Lu, Zhi-Qi Cai, Ting Mao, Long Tang, Hui-Yi Li, Ming-Yi Xu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7607404/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 To understand the heterogeneity of single-B cell responses to Non-alcoholic steatohepatitis (NASH), we performed Single-cell RNA sequencing (scRNA-seq) on single-B cells isolated from control and MCD-fed mice livers. Subsequent analyses included clustering, identification of differentially expressed genes (DEGs) and enrichment analysis. The expressions of high specific DEGs were validated using quantitative real-time PCR (qRT-PCR), immunofluorescence staining and function study. Four single-B cell clusters (3, 14, 16 and 20) were identified. The total number and proportion of B cells significantly decreased in NASH mice livers. In cluster 3, the decreasing Fcer2α + mature B cells were supposed with anti-inflammatory role associated with B cell activation and differentiation of other immune cells in NASH. The DEGs ( Fcer2α , Cd22 , Cr2 and Fcmr ) of cluster 3 were consistently downregulated in B cells cocultued with lipotoxic hepatocytes. And the portal area of livers contained fewer Fcer2α + B cells in NASH patients and mice compared with controls. Fcer2α + B cells attenuated lipotoxicity-driven inflammation by enhancing anti-inflammatory factor (IL-10, IL-35) secretion and inhibiting T cell inflammatory factor (IFN-γ, TNF-α, IL-17) production and proliferation. The other 3 clusters (14, 16 and 20) contained small numbers of single-B cell. Tnfrsf17 + plasmacytes (PCs) of cluster 14 were identified with the effect related to endoplasmic reticulum stress and N-Glycan biosynthesis. Klk1 + B cells of cluster 16 were implicated in regulating immune response in NASH. Apol7c + B cells of cluster 20 participated in apoptosis, NF-κB, TNF and chemokine pathway in NASH. Thus, a subgroup of Fcer2α + mature B cells, diminished in NASH, likely exerted anti-inflammatory or immunosuppressive effects. Non-alcoholic steatohepatitis B cell single-cell RNA sequencing Fcer2α Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Non-alcoholic fatty liver disease (NAFLD) affects approximately 38% of the global population and represents the most prevalent chronic liver disease worldwide [ 1 ] . Up to 20% of NAFLD cases progress to non-alcoholic steatohepatitis (NASH), which is characterized by sustained hepatocellular injury, chronic inflammation, and fibrogenesis, ultimately predisposing patients to cirrhosis, hepatocellular carcinoma, and liver-related mortality [ 2 ] . Emerging evidence implicates hepatic B cells in the pathogenesis of NASH, particularly through modulation of the B cell–activating factor axis and promotion of oxidative stress [ 3 ] . Nevertheless, the precise mechanisms by which B cells contribute to NASH remain incompletely understood. Single-cell RNA sequencing (scRNA-seq), a powerful tool enabling transcriptomic profiling at single-cell resolution, has recently been leveraged to unravel novel immune cell heterogeneity and functional states in NASH [ 4 , 5 ] . For instance, Barrow et al. identified three distinct hepatic B cell clusters, including mature B cells, immature B cells, and metabolically active subsets enriched in mitochondrial genes [ 4 ] . In parallel, Kotsiliti et al. reported increased intestinally derived activated B cells in both murine and human NASH, accompanied by elevated IgA levels and enhanced FcRg⁺ myeloid cell activity, which correlated positively with fibrosis severity [ 5 ] . These findings underscore the multifaceted roles of B cells in shaping the immunopathological landscape of NASH. Here, we performed scRNA-seq of liver nonparenchymal cells (NPCs) from NASH and control mice to systematically dissect intrahepatic B cell heterogeneity. We identified four transcriptionally distinct B cell subsets and observed marked compositional changes in NASH. Notably, Fcer2α⁺ mature B cells were significantly reduced, suggesting a loss of their potential anti-inflammatory capacity. In addition, we characterized Tnfrsf17 + plasmacytes, Klk1⁺ B cells, and Apol7c⁺ B cells, each exhibiting unique transcriptional signatures and functional enrichment patterns, thereby revealing previously unrecognized B cell subsets with potential contributions to NASH pathogenesis. Collectively, these findings provide new insights into B cell biology in fatty liver disease and establish a framework for exploring their functional relevance as potential immunotherapeutic targets. Methods and materials Human Samples A total of six NAFLD patients were enrolled. All patients underwent biopsy confirming NAFLD diagnosis based on pathological steatosis scores. Patients were divided into two groups: mild NAFLD and advanced NASH (n = 3 per group). Cohort details are provided in Table S1 . Written informed consent was obtained from all participants, and the study was approved by the ethics committee of Shanghai East Hospital. NASH mouse model Twelve C57BL/6N mice (8 weeks of age, male) were fed with a standard diet (control group) or a methionine-choline deficient diet (MCD, NASH group) for 6 weeks (n = 6 per group). Three pairs were used for scRNA-seq and three pairs for immunofluorescence staining. Histological identification of NASH patients and mice Human liver tissue sections were prepared and stained with hematoxylin-eosin (H&E). Mouse liver tissue sections were stained with H&E, Masson's trichrome (Masson) and Oil Red O (ORO). Immunohistochemistry (IHC) for liver macrophages was performed using an anti-mouse F4/80 antibody, and F4/80-positive cells were counted. Steatohepatitis, lipid droplets, fibrosis and inflammatory infiltration of liver were assessed by light microscopy (Leica Microsystems, Wetzlar, Germany). Images were analyzed using Image J 1.8.0 software (National Institutes of Health, USA). NASH activity scores were evaluated by a pathologist based on established criteria [ 6 ] , considering steatosis, inflammation, and ballooning degeneration. scRNA-seq and data analysis Liver tissues from NASH and control mice (n = 3 per group) were subjected to scRNA-seq (Sinotech Genomics Co. Ltd., Shanghai, China) as our previous research [ 7 ] . Details on single-cell suspension preparation, transcriptome processing, library construction, and sequencing are provided in the supplemental file. Clustering was performed using t-distributed stochastic neighborhood embedding (t-SNE). Feature plots, violin plots and heatmap were used to visualize the expression of the differentially expressed genes (DEGs). Specific marker genes for each cluster were identified using the FindAllMarkers function (Wilcoxon test; criteria: |log2-fold change| >0.25, min. percentage > 0.25) in Seurat 3.0. Cell type annotation for the cell subpopulations was performed using the built-in mouse RNA-sequencing reference dataset within the R package Single R 1.4.1. B cells were identified based on the expression of cluster of differentiation 79a ( Cd79a ), cluster of differentiation 19 ( Cd19 ) and membrane spanning 4-domains α l ( Ms4α1 ). The average of logFC (avg-logFC) and the percentage of FC (pct_FC) represented the enrichment of the DEGs in corresponding cluster. To explore the related function and signal pathways of DEGs, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed by Cluster Profiler package. GO analysis contained biological process (BP), cellular component (CC) and molecular function (MF). Cell line and culture For cell culture, HepG2 cells, GM12878 cells and Jurkat cell lines were obtained from the Shanghai Cell Bank in the Chinese Academy of Sciences. HepG2 cells (human hepatocellular carcinoma cell line) were cultured in Dulbecco's Modified Eagle Medium (DMEM, Gibco, CA, USA) with 10% Fetal Bovine Serum (FBS, Gibco) and 1% penicillin-streptomycin (Invitrogen, Carlsbad, CA). GM12878 cells (human B lymphocyte line) were cultured in complete Roswell Park Memorial Institute-1640 (RPMI-1640, Gibco) containing 15% FBS and 1% penicillin-streptomycin. Jurkat cells (human T lymphocyte line) were cultured in RPMI-1640 with 10% FBS (Gibco). All cells were grown at 37°C with 5% CO 2 . B cell line (GM12878 cells) transfection The pCMV-MCS-3flag vector (HANBIO, Shanghai, China) and the full-length fragments of Fcer2α were double digested and ligated with T4 DNA ligase (Takara, Kyoto, Japan). After construction, the plasmids were verified by sequencing. GM12878 cells (1×10 5 cells/well) in 6-well plates were transfected with Fcer2α overexpression plasmid (ov- Fcer2α ) or negative control plasmid (ov-NC) using Lipofectamine 3000 (Invitrogen, Carlsbad, US) for 48 h in accordance with the manufacturer's instructions. B cells-hepatocytes coculture To assess the effects of hepatocyte-derived factors on B cells in lipotoxic environment, HepG2 cells were incubated for 24 hours with serum-free DMEM containing either bovine serum albumin (BSA, BioFroxx; CM-BSA group) or palmitic acid (PA, 200 µmol/L, Sigma; CM-PA group). The conditioned medium (CM) was collected and filtered (0.22 µm). GM12878 cells (2×10⁵ cells/well in 6-well plates) were cultured for 24 hours with a 1:1 mixture of CM (CM-BSA or CM-PA) and RPMI-1640 complete medium. To verify the function of Fcer2α + B cells in a lipotoxic environment, ov- Fcer2α or ov-NC GM12878 cells were established. After 24 hours, transfected cells were treated with CM-PA (1:1 with RPMI-1640) for an additional 24 hours. Then, GM12878 cells were harvested for RNA extraction. B cells-T cells coculture B cell-T cell interactions were assessed using a Transwell coculture system (0.4 µm pore polyester membrane, Corning Inc., Corning, NY, USA). GM12878 cells (2.5×10⁵) transfected with either ov- Fcer2α or ov-NC plasmids and pre-conditioned with CM-PA were seeded in the upper chamber of 24-well plates. Jurkat cells (5×10⁵) were placed in the lower chamber. After 24 h coculture at 37°C/5% CO₂, Jurkat cells were harvested for parallel analyses: (1) Total RNA was extracted for qPCR quantification of pro-inflammatory cytokine. (2) EdU⁺ cell proliferation assessment. All conditions were run in technical triplicates with three independent biological replicates. EdU cell proliferation assay Cellular proliferation was quantified using the Click-iT EdU-594 kit (Servicebio, Wuhan, China) according to the manufacturer's protocol. Briefly, cells were pulsed with 10 µM EdU for 2 h prior to fixation. After washing with PBS, cells were fixed with 4% paraformaldehyde (15 min), permeabilized with 0.5% Triton X-100 (20 min), and incubated with click reaction solution containing fluorescent dye iF594 for 30 min protected from light. Nuclei were counterstained with Hoechst 33342 staining solution (1 µg/mL, 10 min). Images were acquired on a TCS SP8 CARS fluorescence microscope (Leica Microsystems) and analyzed using ImageJ (v1.8.0) to calculate the EdU⁺/Hoechst⁺ ratio. Quantitative real-time PCR (qRT-PCR) QRT-PCR used the SYBR Green PCR Kit (Yeasen Biotech Co. Ltd., Shanghai, China). The primers were showed (Sangon Biotech Co., Ltd., Shanghai, China, Table S2). Immunofluorescence (IF) assay IF staining of liver tissues was examined employing of anti-Cd79a (as B cell marker), anti-Fcer2α and anti-Tnfrsf17 at a 1:200 dilution (Table S3). Nucleus were stained with DAPI. Images were captured (TCS SP8 CARS fluorescence microscope, Leica Microsystems), and relative percentage of positive cell area was calculated. Statistical analysis For scRNA-seq, wilcoxon test and Bonferroni correction built in Seurat package (version 4.0) of R software were used to analyze DEGs; fisher exact test and false discovery rate correction were performed on GO and KEGG data using ClusterProfiler package. In qRT-PCR and IF experiments, differences between 2 groups were analyzed with unpaired Student’s t test ( p- value < 0.05 was statistically different). Results Identification of single-B cell clusters in livers of NASH mice The NASH activity score, degree of liver fibrosis and lipid deposition, as well as the percentage of F4/80-positive area, were markedly higher in the livers of MCD-fed mice compared with controls (Fig. S1 ), confirming the successful establishment of the NASH model. Nonparenchymal cells (NPCs) isolated from liver tissues of NASH and control mice were subjected to scRNA-seq, as described previously [ 7 ] . B cells were identified based on the expression of canonical markers Cd79a, Cd19, and Ms4a1 (CD20) (Fig. 1 C). A total of 1,106 and 581 B cells were obtained from control and NASH livers, respectively, revealing a significant reduction in both the absolute number and proportion of B cells in NASH. To further characterize B cell alterations, t-SNE analysis was applied to cluster single B cells. Four subsets (clusters 3, 14, 16, and 20) were identified, each displaying distinct abundance patterns between control and NASH groups (Fig. 1 A). The proportions of clusters 3 and 14 within NPCs were decreased in NASH, whereas cluster 20 was increased (cluster 3: 10.45% vs. 14.64%; cluster 14: 3.72% vs. 5.80%; cluster 20: 2.12% vs. 1.44%; NASH vs. control, Fig. 1 B). Notably, the distribution of clusters 3, 14, and 16 within the total B cell population remained largely unchanged, except for cluster 20, which was enriched in NASH (Fig. 1 B). An unsupervised heatmap highlighted the top 10 differentially expressed genes (DEGs) for each subset, based on relative expression intensity (Fig. 1 D). The characteristics of a cluster of Fcer2α + mature B cells The proportion of cluster 3 B cells was markedly reduced in NASH. Notably, cluster 3 represented the predominant B cell population among the four subsets (Fig. 1 B). This cluster was defined by enriched expression of Fcer2α, complement receptor 2 (Cr2), IgM Fc receptor (Fcmr), and Cd22, along with six additional differentially expressed genes (Cxcr5, Bank1, B3gnt5, Serpinb1a, Zfp318, and Ighd), as visualized by t-SNE and violin plots (Fig. 2 A–D; Table S4). Fcer2α (also known as Cd23), a low-affinity IgE receptor, is highly expressed on mature B cells, particularly the B2 subset. Cr2 (Cd21) expression is dynamically regulated during B lymphopoiesis and coincides with B cell maturation [ 8 ] . Fcmr (also termed TOSO/FAIM3), selectively expressed by lymphocytes, modulates B cell receptor (BCR) signaling through interactions with spleen tyrosine kinase [ 9 ] . Cd22 (Siglec-2), another classical B cell marker, is also frequently used in identifying malignant B cells [ 10 ] . Approximately 60% of cluster 3 B cells expressed Fcer2α, supporting its designation as the most specific marker gene for this cluster (Table S4), thereby identifying it as a mature B cell subset. Gene Ontology (GO) enrichment analysis revealed biological processes (BP) associated with B cell activation, B cell differentiation, and lymphocyte differentiation; cellular components (CC) enriched for nuclear chromatin, major histocompatibility complex (MHC) protein complex, and ribonucleoprotein granules; and molecular functions (MF) including MHC protein complex binding, transcriptional co-regulator activity, and transcriptional co-activator activity (Fig. 2 E). KEGG pathway analysis further demonstrated significant enrichment in Th1/Th2/Th17 cell differentiation and BCR signaling pathways (Fig. 2 E). Together, these findings indicate that NASH is associated with a depletion of mature Fcer2α⁺ B cells. Functionally, this subset appears to be involved in the suppression of inflammatory responses, likely through regulation of B cell activation and cross-talk with other immune cell differentiation pathways in the NASH microenvironment. The characteristics of a cluster of Tnfrsf17 + plasmacytes (PCs) The proportion of cluster 14 B cells was also reduced in NASH (Fig. 1 B). Cluster 14 distinctly expressed Asns , Pycr1 , Dnm3 , Ccr10 and other 6 DEGs [TNF receptor superfamily 17( Tnfrsf17 ), dynein axonemal heavy chain 3( Dnah3 ), Cpeb3 , PR domain-containing protein 1( Prdm1 ), Derlin-3 (Derl3) and Selenom ], as revealed by t-SNE and violin plot analyses (Fig. 3 A–D; Table S5). Among these, four DEGs (Tnfrsf17, Dnah3, Prdm1, and Derl3) were expressed in more than 50% of B cells in this cluster (Table S5). Tnfrsf 17, encoding for B cell maturation antigen, is a receptor involved in B cell activating factor affecting on cells [ 11 ] and predominates on plasmablasts and PCs [ 12 ] . Prdm1-IRF4 signaling activation would encode Blimp1 in B lineage cells and initiate PCs differentiation [ 13 ] . Derl3 was enriched in PCs of the B cells [ 14 ] . Dnah3 is a spermatogenesis related gene; its role in B cells is still unclear. Nearly 72% of cluster 14 cells expressed Tnfrsf17, ranking fifth in pct-FC values (Table S5), thereby establishing Tnfrsf17 as the defining marker gene of this cluster and identifying it as a plasma cell subset. GO enrichment analysis highlighted BP related to endoplasmic reticulum (ER) stress responses, including unfolded and misfolded protein processing; CC enriched in the ER chaperone complex, ER lumen, and rough ER; and MF associated with ribonucleoprotein complex binding and unfolded protein binding (Fig. 3 E). KEGG pathway analysis revealed significant enrichment in ER protein processing and N-glycan biosynthesis pathways (Fig. 3 E). Collectively, these findings identify an intrahepatic Tnfrsf17⁺ plasma cell subset that is reduced in NASH. Functionally, this population may represent a transitional stage from mature B cells to plasma cells and could contribute to disease progression through dysregulated ER stress responses and aberrant glycosylation pathways. The characteristics of a cluster of Klk1 + B cells The proportion of cluster 16 B cells was comparable between NASH and control groups (Fig. 1 B). Cluster 16 specifically expressed Klk1 (kallikrein related peptidase 1), Chdh (choline dehydrogenase), Dntt (terminal deoxynucleotidyl transferase), Paqr5 and other six DEGs ( Gm21762 , Klk1b27 , Cd209d , Obscn , Atp2a1 and Smim5 ),as revealed by t-SNE and violin plot analyses (Fig. 4 A–C; Table S6). Among them, three genes—Klk1, Chdh, and Dntt—were expressed in more than 55% of B cells within this cluster (Table S6). Klk1 (tissue kallikrein), a widespread serine protease, typically inhibits kallistatin activity [ 15 ] . Nearly 71% of cells in cluster 16 expressed Klk1, with the highest pct-FC value among all DEGs (Table S6), thereby establishing Klk1 as the defining marker gene of this cluster. GO enrichment analysis indicated BP related to T cell activation, differentiation, and regulation; CC associated with lysosomes, lytic vacuoles, and the MHC protein complex; and MF including enzyme activator activity, primary active transmembrane transporter activity, and cytokine receptor activity (Fig. 4 D). KEGG pathway analysis further revealed significant enrichment in antigen processing and presentation, BCR signaling, and Th17 cell differentiation pathways (Fig. 4 E). Taken together, these data identify a hepatic Klk1⁺ B cell subset in NASH that may participate in immune regulation by shaping antigen presentation, BCR signaling, and T cell differentiation, thereby suggesting a potential role in modulating cross-talk between B cells and other immune populations in the diseased liver. The characteristics of a cluster of very few Apol7c + B cells The proportion of cluster 20 B cells, which represented the smallest subset, was further reduced in NASH (Fig. 1 B).Cluster 20 specifically expressed of Apol7c (apolipoproteins L7c), Lad1 (leukocyte adhesion deficiency 1), Arhgap22 (Rho GTPase activating protein 22), Arhgap28 and other 6 DEGs ( Gm10851 , Il12b , H2-M2 , Dnah2 , Avpi1 and Lpar3 ),as revealed by t-SNE and violin plot analyses (Fig. 5 A–C; Table S7). Three major DEGs ( Apol7c , Lad1 , Arhgap22 ) were enriched in >50% B cells of this cluster (Table S7). Apol7c (in mouse, or Apol1 in human) was found to bind Bcl-xL (anti-apoptosis) to mediate cell death [ 16 ] . The functions of these DEGs were unclear in B cells and NASH. Notably, 57% of cluster 20 cells expressed Apol7c, which also exhibited the highest pct-FC (Table S7), establishing Apol7c as the defining marker gene of this cluster. GO enrichment analysis revealed BP related to interferon-γ response, antigen processing and presentation, and regulation of leukocyte adhesion; CC associated with lysosomes, lytic vacuoles, and membrane ruffles; and MF including enzyme activator activity, actin filament binding, and cytokine receptor activity (Fig. 5 D). KEGG pathway analysis further demonstrated enrichment in apoptosis, NF-κB, TNF, and chemokine signaling pathways (Fig. 5 E). These findings identify a rare intrahepatic Apol7c⁺ B cell subset that is diminished in NASH. Functionally, this subset may be involved in apoptotic regulation and proinflammatory signaling through NF-κB, TNF, and chemokine pathways, suggesting a potential contribution to the inflammatory milieu of the diseased liver. The expressions of 4 sets of DEGs in each B cell cluster through hepatocytes-B cells coculture study To further investigate the expressions of four sets of high specific DEGs in each cluster through hepatocytes-B cells coculture systems to understand whether lipotoxic hepatocytes mediating the inhibitory immune effect on B cells. GM12878 B cells were cultured in conditioned medium (CM) from HepG2 cells stimulated with 200µM PA (CM-PA) or BSA (CM-BSA). The mRNA of Fcer2α , Cd22 , Cr2 and Fcmr of cluster 3 were unifiedly downregulated in GM12878 cells incubated in the CM-PA versus CM-BSA ( p < 0.05, Fig. 6 A). In cluster 14, the mRNA of Tnfrsf17 , Prdm1 and Derl3 were consistently downregulated in CM-PA group compared with CM-BSA, except for Dnah3 ( p < 0.05, Fig. 6 B). Compared to CM-BSA, CM-PA exhibited a downregulated effect on Chdh , whereas an unregulated effect on Dntt and Klk1 in cluster 16 ( p < 0.05, Fig. 6 C). In cluster 20, CM-PA coculture resulted in lower mRNA levels of Apol1 (Apol7c) and Arhgap22 compared to CM-BSA, except for Lad1 ( p < 0.05, Fig. 6 D). These findings indicate that downregulation of Fcer2α and Tnfrsf17 in B cells contributes to NASH progression. Presence of Fcer2α + B cells subpopulation in NASH mice livers To determine the alteration of Fcer2α + B cells in NASH, we assessed the percentage of Fcer2α + Cd79a + cells in liver tissues of NASH mice by IF staining (n = 3 per group). Cd79a served as a B cell marker. Nuclei were visualized by DAPI (blue IF). The portal area of liver tissues contained abundant Fcer2α + (green IF) Cd79a + (red IF) cells in control mice, but contained rare Fcer2α + Cd79a + cells in NASH mice (NASH vs control group: 23.64 ± 10.88% vs 64.92 ± 6.87%, p < 0.05, Fig. 6 E-F). Then we checked the percentage of Fcer2α + Cd79a + cells in liver tissues of NASH patients by IF staining. Mild NAFLD and advanced NASH was distinguished through H&E staining of liver tissues from patients (Fig. 6 G-H). IF staining of human liver tissues showed a substantial decrease in Fcer2α ⁺ Cd79a ⁺ cells in advanced NASH patients compared to mild NAFLD controls (advanced NASH vs mild NAFLD group: 9.50 ± 0.63% vs 26.70 ± 8.93%, p < 0.05, Fig. 6 I-J). These findings, consistent with scRNA-seq results, suggested the diminished Fcer2α ⁺ B cell subgroup was involved in NASH pathogenesis. Fcer2α + B cells could attenuate inflammation in NASH We further aimed to clarify the function of Fcer2α + B cells in NASH. Given that Fcer2α ⁺ B cells constituted the predominant hepatic B cell subset yet were significantly reduced in the livers of NASH, we established Fcer2α overexpressing (ov- Fcer2α ) and the control (ov-NC) GM12878 cells in a lipotoxic model (cocultured in CM-PA from HepG2 cells). In lipotxic environment, Fcer2α- overexpressing B cells exhibited enhanced anti-inflammatory capacity, secreting 2.76-fold more IL-10 and 1.96-fold more IL-35 versus ov-NC cells ( p < 0.05; Fig. 7 A-B). Then KEGG pathway analysis implicated the Fcer2α signaling of B cells mainly regulated T cell differentiation; we next cocultured T cells (Jurkat cells) with ov- Fcer2α or ov-NC B cells (GM12878 cells) in the lipotoxic CM-PA. While coculturing with ov- Fcer2α B cells in the lipotoxic CM-PA, suppressed T cell-driven inflammation occurred, as reducing IFN-γ, TNF-α, and IL-17 secretion of T cells (ov- Fcer2α group vs. ov-NC group by IFN-γ: 61.07 ± 4.40%, TNF-α: 54.90 ± 2.12%, IL-17: 69.07 ± 2.20%; p < 0.05; Fig. 7 C-E) and diminishing T cell proliferation (EdU⁺ cells in ov- Fcer2α group vs. ov-NC group: 11.55 ± 2.86% vs. 25.76 ± 4.49%; p < 0.05; Fig. 7 F-G). Therefore, Fcer2α + B cells could attenuate lipotoxicity driven inflammation by enhancing anti-inflammatory factor secretion and inhibiting T cell proliferation. Discussion NAFLD is projected to become the primary cause of end-stage liver disease and is associated with increased risks of cardiovascular disease and type 2 diabetes [ 17 ] . NASH prevalence is approximately 4.76% globally and represents the second leading etiology for liver transplantation in the US, with incidence rising [ 1 ] . The mechanisms underlying NASH are multifactorial and remain incompletely understood. B cells are classified B1 and B2 subsets based on surface markers. They participate in NAFLD via cytokines/antibodies secretion and inflammation activation. High-fat diet induced NASH mice showed B cell accumulation expressing inflammatory cytokines and activating T cells [ 18 ] . Barrow et al. demonstrated intrahepatic B2 cell accumulation in NASH mice livers. expressing proinflammatory genes and secreting IL-6 and TNF-α to promote inflammation and fibrogenesis [ 4 ] . Recent scRNA-seq studies confirm B cell heterogeneity in NASH. Through sc-RNAseq, Barrow et al identified 3 specific clusters of B cells [ 4 ] . Xiong et al supported a B cells subset highly expressed Cxcl12/Cxcr4 with a fibrogenic function by sc-RNAseq analysis in NASH [ 19 ] . Deczkowska et al found a reduction of hepatic B cells in MCD induced NASH mice through scRNA-seq [ 20 ] . In our study, 21 major clusters of single-NPC were found based on cell-specific markers between MCD induced NASH and control mice livers by scRNA-seq analysis. Four single-B cell clusters were characterized. The total B cell percentage decreased significantly in NASH livers, consistent with previous report [ 20 ] . Interestingly, B cells of cluster 3 (the major cluster) was mature B cells. The cellular function of cluster 3 consisted of B cells activation and differentiation, and lymphocyte differentiation. Importantly, cluster 3 mainly contained with Fcer2α + B cells and the proportion of them was decreased in NASH. Fcer2α is also known as a marker for B regulatory cells with inhibition function of inflammation [ 21 – 22 ] . Our study proved Fcer2α mRNA downregulation in lipotoxic B cells, and fewer portal Fcer2α ⁺ B cells in NASH patients/mice versus controls. Functional study showed Fcer2α + B cells alleviated NASH by enhancing anti-inflammatory factor secretion and inhibiting T cell proliferation. Ge et al. similarly found CD20 + Fcer2α + IL10V Breg cells exert immunosuppressive effects [ 23 ] . Therefore, we speculated that decreasing Fcer2α + mature B cells distributed in cluster 3 perhaps play an inhibition of inflammatory role in NASH. In cluster 3, Cr2 + /Fcmr + /Cd22 + B cells were also seen, this set of genes ( Cd22 , Cr2 and Fcmr ) were consistently downregulated in lipotoxic B cells. Allman et al. proposed that Cr2 was highly expressed on B cells and selected by BCR signaling during transition and maturation [ 24 ] . Kubagawa et al. found Fcmr KO mice would impair B cell tolerance as concomitantly producing autoantibodies of IgM/G [ 25 ] . Cd22 is an inhibitory receptor expressed in B cells involved in preventing autoimmune diseases and leukemia delevopment [ 26 ] . Therefore, these results need further exploration. Then, B cells in cluster 14 were identified as PCs based on specific markers ( Tnfrsf17 , Dnah3 , Prdm1 and Derl3 ), and these PCs were decreased in NASH. The cellular function of cluster 14 maybe related to ER stress and N-glycan biosynthesis. Cluster 14 mainly contained with Tnfrsf17 + B cells and the proportion of them was decreased in NASH. Indeed, Tnfrsf17 + B cells typically induce pro-inflammatory cytokines (e.g., IL-6, TNF-α) in autoimmune diseases, thereby activating chronic inflammatory responses. Levels et al. reported that Tnfrsf17 was upregulated in synovial tissue B cells from rheumatoid arthritis patients, where they promoted synovitis progression via the production of pathogenic autoantibodies [ 27 ] . Similarly, Kim et al found systemic lupus erythematosus patients exhibited increasing Tnfrsf17 expression on B cells, and enabled Tnfrsf17 + B cells to drive inflammatory progression by enhancing TLR9-triggered secretion of anti-dsDNA and ANA autoantibodies [ 28 ] .The role of Tnfrsf17 ⁺ PCs requires further investigation. Cluster 16, also a minor B cell group, was identified. In the same way, the cell function is activate, differentiate and regulate T cells. In our study, Klk1 mRNA was upregulated in lipotoxic B cells. Zhang et al. identified Klk1 inhibition in the inflamed prostates; exogenous Klk1 restored endothelial function and exerted anti-inflammatory, antifibrotic, and antioxidative stress effects in the rat chronic-inflamed prostate [ 29 ] . The mechanism of Klk1 + B cells remains unclear in NASH. Finally, the very small cluster 20 was enriched, and the cell function was inferred in dysregulation of apoptosis, NF-κB, TNF and chemokine. Apol7c mRNA was downregulated in lipotoxic B cells in our study. Uzureau et al. previously linked Apol7 knockdown to increased dendritic cell survival and Apol7c interaction with Bcl-xL [ 16 ] . But Apol7c + B cells were undefined in NASH. This study provides interesting insights into distinct B cell subsets and their potential roles in NASH, but several limitations exist. Firstly, The captured B cell number (1106 control, 581 NASH) limited resolution for rare subpopulations and assessment of biological variability. Secondly, While transcriptional clusters and potential functions were inferred via gene expression, pathway analysis, and in vitro assays, in vivo functional validation is lacking. Thirdly, The MCD diet model does not fully recapitulate human NAFLD metabolic features (e.g., obesity, insulin resistance), potentially limiting translational relevance. Future studies should incorporate robust functional validation and models/samples better reflecting human pathology. In summary, the composition of four undefined single-B cell subsets is altered in NASH. We identified a subgroup of Fcer2a + mature B cells, significantly reduced in NASH, which likely exerted anti-inflammatory or immunosuppressive effects. Declarations * Ethics approval and consent to participate The animal study was approved by the Institutional Animal Care and Use Committee of Shanghai East Hospital. * Consent for publication No human research participants in this study. * Availability of data and material The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Sequence data that support the findings of this study is available through GEO database (number GSE225786). * Competing interests The authors declare no conflicts of interest that pertain to this study. * Funding This study was supported by the National Natural Science Foundation of China (No. 82270604). * Authors' contributions Conceived the study design: S.Z.L. and M.Y.X. Performed the experiments and analysed the data: T.M., Z.Q.C., H.Y.L. and J.C.L. Analysed the scRNA-seq data set: H.Y.L., L.T and S.Z.L. Wrote the manuscript: M.Y.X.,J.C.L. and T.M. 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Kim J, Gross JA, Dillon SR, et al. Increased BCMA expression in lupus marks activated B cells, and BCMA receptor engagement enhances the response to TLR9 stimulation. Autoimmunity, 2011;44(2):69-81. Zhang M, Lin D, Luo C, et al. Tissue kallikrein protects rat prostate against the inflammatory damage in a chronic autoimmune prostatitis model via restoring endothelial function in a bradykinin receptor B2-dependent way. Oxid Med Cell Longev, 2022: 2022: 1247806. Additional Declarations No competing interests reported. Supplementary Files SupplFile.docx 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. 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1","display":"","copyAsset":false,"role":"figure","size":671969,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFour B cell subsets isolated from mouse livers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) t-SNE plots of B cells in liver tissue from control and NASH mice by scRNA-seq (each group, n=3). (B) Comparison of B cell percentage of NPCs or total B cells in each cluster between the control and NASH groups. (C) The t-SNE plots showed the expression levels of the B cell markers of \u003cem\u003eCd79a\u003c/em\u003e, \u003cem\u003eCd 19\u003c/em\u003e and \u003cem\u003eMs4α1.\u003c/em\u003e (D) Heatmap of the top 10 specific DEGs in 4 B cell clusters (3, 14, 16 and 20).\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/c8653a3b0e49b805fc66b874.jpg"},{"id":91958945,"identity":"026dd53c-bfde-483d-8b29-ca6a03ba24f4","added_by":"auto","created_at":"2025-09-23 07:38:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":742356,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics and biological functions of B cells in cluster 3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-D) Paired t-SNE plots (left) and violin plots (right) showed the expression levels of specific DEGs including \u003cem\u003eFcer2a \u003c/em\u003e(A),\u003cem\u003eCd22 \u003c/em\u003e(B),\u003cem\u003e Cr2\u003c/em\u003e (C) and \u003cem\u003eFcmr\u003c/em\u003e (D) in cluster 3. (E) GO analysis and KEGG pathway enrichment of B cells distributed in cluster 3.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/7ca657df68d8d5094cc29458.jpg"},{"id":91958919,"identity":"ffa6e356-9188-4bef-b5b2-96290fb60a5d","added_by":"auto","created_at":"2025-09-23 07:38:31","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":772916,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics and biological functions of B cells in cluster 14\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-D) Paired t-SNE plots (left) and violin plots (right) showed the expression levels of specific DEGs including \u003cem\u003eTnfrsf17 \u003c/em\u003e(A),\u003cem\u003e Dnah3 \u003c/em\u003e(B),\u003cem\u003ePrdm1\u003c/em\u003e (C) and \u003cem\u003eDerl3\u003c/em\u003e (D) in cluster 14. (E) GO analysis and KEGG pathway enrichment of B cells distributed in cluster 14.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/51f08c5e1d17b5335ddcb704.jpg"},{"id":91958906,"identity":"9df798a3-0027-4cf6-925e-02da67e2d76b","added_by":"auto","created_at":"2025-09-23 07:38:31","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":703750,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics and biological functions of B cells in cluster 16\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-C) Paired t-SNE plots (left) and violin plots (right) showed the expression levels of specific DEGs including \u003cem\u003eKlk1 \u003c/em\u003e(A),\u003cem\u003e Chdh \u003c/em\u003e(B) and \u003cem\u003eDntt \u003c/em\u003e(C) in cluster 16. (D) GO analysis and (E) KEGG pathway enrichment of B cells distributed in cluster 16.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/6a04c89c3e0742a1f4e1ec6b.jpg"},{"id":91960298,"identity":"a94525da-adf4-4044-bc65-6d74ef1016ff","added_by":"auto","created_at":"2025-09-23 07:46:31","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":698871,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristics and biological functions of B cells in cluster 20\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-C) Paired t-SNE plots (left) and violin plots (right) showing the expression levels of specific DEGs including \u003cem\u003eApol7c \u003c/em\u003e(A),\u003cem\u003e Lad1 \u003c/em\u003e(B) and \u003cem\u003eArhgap22\u003c/em\u003e (C) in cluster 20. (D) GO analysis and (E) KEGG pathway enrichment of B cells distributed in cluster 20.\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/426af99acce3fd1b90ee5da1.jpg"},{"id":91958909,"identity":"dd367779-44ee-4294-88e6-f69cf0759597","added_by":"auto","created_at":"2025-09-23 07:38:31","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":933980,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of cluster-specific DEGs and presence of\u0026nbsp;\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eFcer2a\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e⁺ B cells in NASH livers.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mRNA expressions of highly specific DEGs in each B cell cluster through hepatocytes-B cells coculture. GM12878 B cells cultured in CM-PA (from PA-treated HepG2) or CM-BSA (BSA-treated). The mRNA expressions of\u003cstrong\u003e \u003c/strong\u003e(A) \u003cem\u003eFcer2a\u003c/em\u003e,\u003cem\u003e Cd22\u003c/em\u003e,\u003cem\u003e Cr2 \u003c/em\u003eand \u003cem\u003eFcmr \u003c/em\u003eof cluster 3; (B) \u003cem\u003eTnfrsf17\u003c/em\u003e,\u003cem\u003e Dnah3\u003c/em\u003e,\u003cem\u003e Prdm1\u003c/em\u003e and \u003cem\u003eDerl3\u003c/em\u003e of cluster 14; (C) \u003cem\u003eChdh\u003c/em\u003e, \u003cem\u003eDntt\u003c/em\u003e and \u003cem\u003eKlk1\u003c/em\u003e of cluster 16; (D) \u003cem\u003eApol7c\u003c/em\u003e,\u003cem\u003e Lad1\u003c/em\u003e and \u003cem\u003eArhgap22\u003c/em\u003e of cluster 20 were examined by qRT-PCR. The presence of \u003cem\u003eFcer2a\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells in NASH livers was evaluated by IF staining. Two groups were established of NASH and control mice (each group, n=3). (E-F) Representative images and calculation of IF staining for Fcer2α (green IF) and Cd79a (red IF) in liver tissues (×400). Two groups were established of mild NAFLD and advanced NASH patients (each group, n=3). Representative images and calculation of (G-H) H\u0026amp;E staining and (I-J) IF staining for Fcer2α (green IF) and Cd79a (red IF) of liver tissues from patient (×400). DAPI (blue) was used for nuclear staining. DAPI (blue) was used for nuclear staining.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/23973efb7172392c39ad53b0.jpg"},{"id":91958935,"identity":"a6bbbb27-122d-4d70-a613-10df9dca4e9f","added_by":"auto","created_at":"2025-09-23 07:38:32","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":541402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFcer2α\u003c/strong\u003e\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/em\u003e\u003c/sup\u003e\u003cstrong\u003e B cells attenuated inflammation in the lipotoxic environment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) The mRNA expression of IL-10 and IL-35 in ov-\u003cem\u003eFcer2α\u003c/em\u003e B cells (ov-\u003cem\u003eFcer2α\u003c/em\u003e) versus control (ov-NC) cultured in CM-PA from PA-treated HepG2 cells (each group, n=3). (C-E) The mRNA levels of pro-inflammatory cytokines (IFN-γ, TNF-α, IL-17) of T cells and (F-G) Representative IF EdU staining (×400) and semi-quantification of T cells coculturing with ov-\u003cem\u003eFcer2α\u003c/em\u003e and ov-NC B cell groups in CM-PA (each group, n=3).\u003c/p\u003e","description":"","filename":"Fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/6af5262bcbe30c30b36ccc32.jpg"},{"id":92642361,"identity":"ca62565a-aa7e-45a0-be36-117a6785ec93","added_by":"auto","created_at":"2025-10-02 08:47:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6181477,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/00b13289-b872-498f-94f8-a5b8e9c6c2ed.pdf"},{"id":91958864,"identity":"00820af9-911a-4ff3-858c-17fc1cab6d9f","added_by":"auto","created_at":"2025-09-23 07:38:29","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":266193,"visible":true,"origin":"","legend":"","description":"","filename":"SupplFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7607404/v1/67cd5c1abae7143fd0128e71.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSingle-Cell Transcriptomic Landscape of Intrahepatic B Cells in NASH\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNon-alcoholic fatty liver disease (NAFLD) affects approximately 38% of the global population and represents the most prevalent chronic liver disease worldwide \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Up to 20% of NAFLD cases progress to non-alcoholic steatohepatitis (NASH), which is characterized by sustained hepatocellular injury, chronic inflammation, and fibrogenesis, ultimately predisposing patients to cirrhosis, hepatocellular carcinoma, and liver-related mortality \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEmerging evidence implicates hepatic B cells in the pathogenesis of NASH, particularly through modulation of the B cell\u0026ndash;activating factor axis and promotion of oxidative stress \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Nevertheless, the precise mechanisms by which B cells contribute to NASH remain incompletely understood. Single-cell RNA sequencing (scRNA-seq), a powerful tool enabling transcriptomic profiling at single-cell resolution, has recently been leveraged to unravel novel immune cell heterogeneity and functional states in NASH \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. For instance, Barrow et al. identified three distinct hepatic B cell clusters, including mature B cells, immature B cells, and metabolically active subsets enriched in mitochondrial genes \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In parallel, Kotsiliti et al. reported increased intestinally derived activated B cells in both murine and human NASH, accompanied by elevated IgA levels and enhanced FcRg⁺ myeloid cell activity, which correlated positively with fibrosis severity \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. These findings underscore the multifaceted roles of B cells in shaping the immunopathological landscape of NASH.\u003c/p\u003e\u003cp\u003eHere, we performed scRNA-seq of liver nonparenchymal cells (NPCs) from NASH and control mice to systematically dissect intrahepatic B cell heterogeneity. We identified four transcriptionally distinct B cell subsets and observed marked compositional changes in NASH. Notably, Fcer2α⁺ mature B cells were significantly reduced, suggesting a loss of their potential anti-inflammatory capacity. In addition, we characterized Tnfrsf17\u0026thinsp;+\u0026thinsp;plasmacytes, Klk1⁺ B cells, and Apol7c⁺ B cells, each exhibiting unique transcriptional signatures and functional enrichment patterns, thereby revealing previously unrecognized B cell subsets with potential contributions to NASH pathogenesis. Collectively, these findings provide new insights into B cell biology in fatty liver disease and establish a framework for exploring their functional relevance as potential immunotherapeutic targets.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eHuman Samples\u003c/h2\u003e\u003cp\u003eA total of six NAFLD patients were enrolled. All patients underwent biopsy confirming NAFLD diagnosis based on pathological steatosis scores. Patients were divided into two groups: mild NAFLD and advanced NASH (n\u0026thinsp;=\u0026thinsp;3 per group). Cohort details are provided in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Written informed consent was obtained from all participants, and the study was approved by the ethics committee of Shanghai East Hospital.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eNASH mouse model\u003c/h3\u003e\n\u003cp\u003eTwelve C57BL/6N mice (8 weeks of age, male) were fed with a standard diet (control group) or a methionine-choline deficient diet (MCD, NASH group) for 6 weeks (n\u0026thinsp;=\u0026thinsp;6 per group). Three pairs were used for scRNA-seq and three pairs for immunofluorescence staining.\u003c/p\u003e\n\u003ch3\u003eHistological identification of NASH patients and mice\u003c/h3\u003e\n\u003cp\u003eHuman liver tissue sections were prepared and stained with hematoxylin-eosin (H\u0026amp;E). Mouse liver tissue sections were stained with H\u0026amp;E, Masson's trichrome (Masson) and Oil Red O (ORO). Immunohistochemistry (IHC) for liver macrophages was performed using an anti-mouse F4/80 antibody, and F4/80-positive cells were counted. Steatohepatitis, lipid droplets, fibrosis and inflammatory infiltration of liver were assessed by light microscopy (Leica Microsystems, Wetzlar, Germany). Images were analyzed using Image J 1.8.0 software (National Institutes of Health, USA). NASH activity scores were evaluated by a pathologist based on established criteria \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, considering steatosis, inflammation, and ballooning degeneration.\u003c/p\u003e\n\u003ch3\u003escRNA-seq and data analysis\u003c/h3\u003e\n\u003cp\u003eLiver tissues from NASH and control mice (n\u0026thinsp;=\u0026thinsp;3 per group) were subjected to scRNA-seq (Sinotech Genomics Co. Ltd., Shanghai, China) as our previous research \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Details on single-cell suspension preparation, transcriptome processing, library construction, and sequencing are provided in the supplemental file. Clustering was performed using t-distributed stochastic neighborhood embedding (t-SNE). Feature plots, violin plots and heatmap were used to visualize the expression of the differentially expressed genes (DEGs). Specific marker genes for each cluster were identified using the FindAllMarkers function (Wilcoxon test; criteria: |log2-fold change| \u0026gt;0.25, min. percentage\u0026thinsp;\u0026gt;\u0026thinsp;0.25) in Seurat 3.0. Cell type annotation for the cell subpopulations was performed using the built-in mouse RNA-sequencing reference dataset within the R package Single R 1.4.1. B cells were identified based on the expression of cluster of differentiation 79a (\u003cem\u003eCd79a\u003c/em\u003e), cluster of differentiation 19 (\u003cem\u003eCd19\u003c/em\u003e) and membrane spanning 4-domains α l (\u003cem\u003eMs4α1\u003c/em\u003e). The average of logFC (avg-logFC) and the percentage of FC (pct_FC) represented the enrichment of the DEGs in corresponding cluster. To explore the related function and signal pathways of DEGs, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed by Cluster Profiler package. GO analysis contained biological process (BP), cellular component (CC) and molecular function (MF).\u003c/p\u003e\n\u003ch3\u003eCell line and culture\u003c/h3\u003e\n\u003cp\u003eFor cell culture, HepG2 cells, GM12878 cells and Jurkat cell lines were obtained from the Shanghai Cell Bank in the Chinese Academy of Sciences. HepG2 cells (human hepatocellular carcinoma cell line) were cultured in Dulbecco's Modified Eagle Medium (DMEM, Gibco, CA, USA) with 10% Fetal Bovine Serum (FBS, Gibco) and 1% penicillin-streptomycin (Invitrogen, Carlsbad, CA). GM12878 cells (human B lymphocyte line) were cultured in complete Roswell Park Memorial Institute-1640 (RPMI-1640, Gibco) containing 15% FBS and 1% penicillin-streptomycin. Jurkat cells (human T lymphocyte line) were cultured in RPMI-1640 with 10% FBS (Gibco). All cells were grown at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eB cell line (GM12878 cells) transfection\u003c/h2\u003e\u003cp\u003eThe pCMV-MCS-3flag vector (HANBIO, Shanghai, China) and the full-length fragments of \u003cem\u003eFcer2α\u003c/em\u003e were double digested and ligated with T4 DNA ligase (Takara, Kyoto, Japan). After construction, the plasmids were verified by sequencing. GM12878 cells (1\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/well) in 6-well plates were transfected with \u003cem\u003eFcer2α\u003c/em\u003e overexpression plasmid (ov-\u003cem\u003eFcer2α\u003c/em\u003e) or negative control plasmid (ov-NC) using Lipofectamine 3000 (Invitrogen, Carlsbad, US) for 48 h in accordance with the manufacturer's instructions.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eB cells-hepatocytes coculture\u003c/h3\u003e\n\u003cp\u003eTo assess the effects of hepatocyte-derived factors on B cells in lipotoxic environment, HepG2 cells were incubated for 24 hours with serum-free DMEM containing either bovine serum albumin (BSA, BioFroxx; CM-BSA group) or palmitic acid (PA, 200 \u0026micro;mol/L, Sigma; CM-PA group). The conditioned medium (CM) was collected and filtered (0.22 \u0026micro;m). GM12878 cells (2\u0026times;10⁵ cells/well in 6-well plates) were cultured for 24 hours with a 1:1 mixture of CM (CM-BSA or CM-PA) and RPMI-1640 complete medium.\u003c/p\u003e\u003cp\u003eTo verify the function of \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells in a lipotoxic environment, ov-\u003cem\u003eFcer2α\u003c/em\u003e or ov-NC GM12878 cells were established. After 24 hours, transfected cells were treated with CM-PA (1:1 with RPMI-1640) for an additional 24 hours. Then, GM12878 cells were harvested for RNA extraction.\u003c/p\u003e\n\u003ch3\u003eB cells-T cells coculture\u003c/h3\u003e\n\u003cp\u003eB cell-T cell interactions were assessed using a Transwell coculture system (0.4 \u0026micro;m pore polyester membrane, Corning Inc., Corning, NY, USA). GM12878 cells (2.5\u0026times;10⁵) transfected with either ov-\u003cem\u003eFcer2α\u003c/em\u003e or ov-NC plasmids and pre-conditioned with CM-PA were seeded in the upper chamber of 24-well plates. Jurkat cells (5\u0026times;10⁵) were placed in the lower chamber. After 24 h coculture at 37\u0026deg;C/5% CO₂, Jurkat cells were harvested for parallel analyses: (1) Total RNA was extracted for qPCR quantification of pro-inflammatory cytokine. (2) EdU⁺ cell proliferation assessment. All conditions were run in technical triplicates with three independent biological replicates.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEdU cell proliferation assay\u003c/h2\u003e\u003cp\u003eCellular proliferation was quantified using the Click-iT EdU-594 kit (Servicebio, Wuhan, China) according to the manufacturer's protocol. Briefly, cells were pulsed with 10 \u0026micro;M EdU for 2 h prior to fixation. After washing with PBS, cells were fixed with 4% paraformaldehyde (15 min), permeabilized with 0.5% Triton X-100 (20 min), and incubated with click reaction solution containing fluorescent dye iF594 for 30 min protected from light. Nuclei were counterstained with Hoechst 33342 staining solution (1 \u0026micro;g/mL, 10 min). Images were acquired on a TCS SP8 CARS fluorescence microscope (Leica Microsystems) and analyzed using ImageJ (v1.8.0) to calculate the EdU⁺/Hoechst⁺ ratio.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eQuantitative real-time PCR (qRT-PCR)\u003c/h2\u003e\u003cp\u003eQRT-PCR used the SYBR Green PCR Kit (Yeasen Biotech Co. Ltd., Shanghai, China). The primers were showed (Sangon Biotech Co., Ltd., Shanghai, China, Table S2).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eImmunofluorescence (IF) assay\u003c/h2\u003e\u003cp\u003eIF staining of liver tissues was examined employing of anti-Cd79a (as B cell marker), anti-Fcer2α and anti-Tnfrsf17 at a 1:200 dilution (Table S3). Nucleus were stained with DAPI. Images were captured (TCS SP8 CARS fluorescence microscope, Leica Microsystems), and relative percentage of positive cell area was calculated.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eFor scRNA-seq, wilcoxon test and Bonferroni correction built in Seurat package (version 4.0) of R software were used to analyze DEGs; fisher exact test and false discovery rate correction were performed on GO and KEGG data using ClusterProfiler package. In qRT-PCR and IF experiments, differences between 2 groups were analyzed with unpaired Student\u0026rsquo;s t test (\u003cem\u003ep-\u003c/em\u003evalue\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was statistically different).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eIdentification of single-B cell clusters in livers of NASH mice\u003c/h2\u003e\u003cp\u003eThe NASH activity score, degree of liver fibrosis and lipid deposition, as well as the percentage of F4/80-positive area, were markedly higher in the livers of MCD-fed mice compared with controls (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), confirming the successful establishment of the NASH model. Nonparenchymal cells (NPCs) isolated from liver tissues of NASH and control mice were subjected to scRNA-seq, as described previously \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. B cells were identified based on the expression of canonical markers Cd79a, Cd19, and Ms4a1 (CD20) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). A total of 1,106 and 581 B cells were obtained from control and NASH livers, respectively, revealing a significant reduction in both the absolute number and proportion of B cells in NASH.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further characterize B cell alterations, t-SNE analysis was applied to cluster single B cells. Four subsets (clusters 3, 14, 16, and 20) were identified, each displaying distinct abundance patterns between control and NASH groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The proportions of clusters 3 and 14 within NPCs were decreased in NASH, whereas cluster 20 was increased (cluster 3: 10.45% vs. 14.64%; cluster 14: 3.72% vs. 5.80%; cluster 20: 2.12% vs. 1.44%; NASH vs. control, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Notably, the distribution of clusters 3, 14, and 16 within the total B cell population remained largely unchanged, except for cluster 20, which was enriched in NASH (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). An unsupervised heatmap highlighted the top 10 differentially expressed genes (DEGs) for each subset, based on relative expression intensity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe characteristics of a cluster of\u003c/b\u003e \u003cb\u003eFcer2α\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003emature B cells\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe proportion of cluster 3 B cells was markedly reduced in NASH. Notably, cluster 3 represented the predominant B cell population among the four subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). This cluster was defined by enriched expression of Fcer2α, complement receptor 2 (Cr2), IgM Fc receptor (Fcmr), and Cd22, along with six additional differentially expressed genes (Cxcr5, Bank1, B3gnt5, Serpinb1a, Zfp318, and Ighd), as visualized by t-SNE and violin plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;D; Table S4). Fcer2α (also known as Cd23), a low-affinity IgE receptor, is highly expressed on mature B cells, particularly the B2 subset. Cr2 (Cd21) expression is dynamically regulated during B lymphopoiesis and coincides with B cell maturation \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Fcmr (also termed TOSO/FAIM3), selectively expressed by lymphocytes, modulates B cell receptor (BCR) signaling through interactions with spleen tyrosine kinase \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Cd22 (Siglec-2), another classical B cell marker, is also frequently used in identifying malignant B cells \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Approximately 60% of cluster 3 B cells expressed Fcer2α, supporting its designation as the most specific marker gene for this cluster (Table S4), thereby identifying it as a mature B cell subset.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGene Ontology (GO) enrichment analysis revealed biological processes (BP) associated with B cell activation, B cell differentiation, and lymphocyte differentiation; cellular components (CC) enriched for nuclear chromatin, major histocompatibility complex (MHC) protein complex, and ribonucleoprotein granules; and molecular functions (MF) including MHC protein complex binding, transcriptional co-regulator activity, and transcriptional co-activator activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). KEGG pathway analysis further demonstrated significant enrichment in Th1/Th2/Th17 cell differentiation and BCR signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eTogether, these findings indicate that NASH is associated with a depletion of mature Fcer2α⁺ B cells. Functionally, this subset appears to be involved in the suppression of inflammatory responses, likely through regulation of B cell activation and cross-talk with other immune cell differentiation pathways in the NASH microenvironment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe characteristics of a cluster of\u003c/b\u003e \u003cb\u003eTnfrsf17\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eplasmacytes (PCs)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe proportion of cluster 14 B cells was also reduced in NASH (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Cluster 14 distinctly expressed \u003cem\u003eAsns\u003c/em\u003e, \u003cem\u003ePycr1\u003c/em\u003e, \u003cem\u003eDnm3\u003c/em\u003e, \u003cem\u003eCcr10\u003c/em\u003e and other 6 DEGs [TNF receptor superfamily 17(\u003cem\u003eTnfrsf17\u003c/em\u003e), dynein axonemal heavy chain 3(\u003cem\u003eDnah3\u003c/em\u003e), \u003cem\u003eCpeb3\u003c/em\u003e, PR domain-containing protein 1(\u003cem\u003ePrdm1\u003c/em\u003e), \u003cem\u003eDerlin-3\u003c/em\u003e(Derl3) and \u003cem\u003eSelenom\u003c/em\u003e], as revealed by t-SNE and violin plot analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026ndash;D; Table S5). Among these, four DEGs (Tnfrsf17, Dnah3, Prdm1, and Derl3) were expressed in more than 50% of B cells in this cluster (Table S5). \u003cem\u003eTnfrsf\u003c/em\u003e17, encoding for B cell maturation antigen, is a receptor involved in B cell activating factor affecting on cells \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e and predominates on plasmablasts and PCs \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003ePrdm1-IRF4\u003c/em\u003e signaling activation would encode \u003cem\u003eBlimp1\u003c/em\u003e in B lineage cells and initiate PCs differentiation \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003eDerl3\u003c/em\u003e was enriched in PCs of the B cells \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003eDnah3\u003c/em\u003e is a spermatogenesis related gene; its role in B cells is still unclear. Nearly 72% of cluster 14 cells expressed Tnfrsf17, ranking fifth in pct-FC values (Table S5), thereby establishing Tnfrsf17 as the defining marker gene of this cluster and identifying it as a plasma cell subset.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGO enrichment analysis highlighted BP related to endoplasmic reticulum (ER) stress responses, including unfolded and misfolded protein processing; CC enriched in the ER chaperone complex, ER lumen, and rough ER; and MF associated with ribonucleoprotein complex binding and unfolded protein binding (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). KEGG pathway analysis revealed significant enrichment in ER protein processing and N-glycan biosynthesis pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eCollectively, these findings identify an intrahepatic Tnfrsf17⁺ plasma cell subset that is reduced in NASH. Functionally, this population may represent a transitional stage from mature B cells to plasma cells and could contribute to disease progression through dysregulated ER stress responses and aberrant glycosylation pathways.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe characteristics of a cluster of\u003c/b\u003e \u003cb\u003eKlk1\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eB cells\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe proportion of cluster 16 B cells was comparable between NASH and control groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Cluster 16 specifically expressed \u003cem\u003eKlk1\u003c/em\u003e (kallikrein related peptidase 1), \u003cem\u003eChdh\u003c/em\u003e (choline dehydrogenase), \u003cem\u003eDntt\u003c/em\u003e (terminal deoxynucleotidyl transferase), \u003cem\u003ePaqr5\u003c/em\u003e and other six DEGs (\u003cem\u003eGm21762\u003c/em\u003e, \u003cem\u003eKlk1b27\u003c/em\u003e, \u003cem\u003eCd209d\u003c/em\u003e, \u003cem\u003eObscn\u003c/em\u003e, \u003cem\u003eAtp2a1\u003c/em\u003e and \u003cem\u003eSmim5\u003c/em\u003e),as revealed by t-SNE and violin plot analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u0026ndash;C; Table S6). Among them, three genes\u0026mdash;Klk1, Chdh, and Dntt\u0026mdash;were expressed in more than 55% of B cells within this cluster (Table S6). \u003cem\u003eKlk1\u003c/em\u003e (tissue kallikrein), a widespread serine protease, typically inhibits kallistatin activity \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Nearly 71% of cells in cluster 16 expressed Klk1, with the highest pct-FC value among all DEGs (Table S6), thereby establishing Klk1 as the defining marker gene of this cluster.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGO enrichment analysis indicated BP related to T cell activation, differentiation, and regulation; CC associated with lysosomes, lytic vacuoles, and the MHC protein complex; and MF including enzyme activator activity, primary active transmembrane transporter activity, and cytokine receptor activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). KEGG pathway analysis further revealed significant enrichment in antigen processing and presentation, BCR signaling, and Th17 cell differentiation pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eTaken together, these data identify a hepatic Klk1⁺ B cell subset in NASH that may participate in immune regulation by shaping antigen presentation, BCR signaling, and T cell differentiation, thereby suggesting a potential role in modulating cross-talk between B cells and other immune populations in the diseased liver.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe characteristics of a cluster of very few\u003c/b\u003e \u003cb\u003eApol7c\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eB cells\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe proportion of cluster 20 B cells, which represented the smallest subset, was further reduced in NASH (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).Cluster 20 specifically expressed of \u003cem\u003eApol7c\u003c/em\u003e (apolipoproteins L7c), \u003cem\u003eLad1\u003c/em\u003e (leukocyte adhesion deficiency 1), \u003cem\u003eArhgap22\u003c/em\u003e (Rho GTPase activating protein 22), \u003cem\u003eArhgap28\u003c/em\u003e and other 6 DEGs (\u003cem\u003eGm10851\u003c/em\u003e, \u003cem\u003eIl12b\u003c/em\u003e, \u003cem\u003eH2-M2\u003c/em\u003e, \u003cem\u003eDnah2\u003c/em\u003e, \u003cem\u003eAvpi1\u003c/em\u003e and \u003cem\u003eLpar3\u003c/em\u003e),as revealed by t-SNE and violin plot analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;C; Table S7). Three major DEGs (\u003cem\u003eApol7c\u003c/em\u003e, \u003cem\u003eLad1\u003c/em\u003e, \u003cem\u003eArhgap22\u003c/em\u003e) were enriched in \u0026gt;50% B cells of this cluster (Table S7). \u003cem\u003eApol7c\u003c/em\u003e (in mouse, or \u003cem\u003eApol1\u003c/em\u003e in human) was found to bind Bcl-xL (anti-apoptosis) to mediate cell death \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. The functions of these DEGs were unclear in B cells and NASH. Notably, 57% of cluster 20 cells expressed Apol7c, which also exhibited the highest pct-FC (Table S7), establishing Apol7c as the defining marker gene of this cluster.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGO enrichment analysis revealed BP related to interferon-γ response, antigen processing and presentation, and regulation of leukocyte adhesion; CC associated with lysosomes, lytic vacuoles, and membrane ruffles; and MF including enzyme activator activity, actin filament binding, and cytokine receptor activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). KEGG pathway analysis further demonstrated enrichment in apoptosis, NF-κB, TNF, and chemokine signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eThese findings identify a rare intrahepatic Apol7c⁺ B cell subset that is diminished in NASH. Functionally, this subset may be involved in apoptotic regulation and proinflammatory signaling through NF-κB, TNF, and chemokine pathways, suggesting a potential contribution to the inflammatory milieu of the diseased liver.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe expressions of 4 sets of DEGs in each B cell cluster through hepatocytes-B cells coculture study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo further investigate the expressions of four sets of high specific DEGs in each cluster through hepatocytes-B cells coculture systems to understand whether lipotoxic hepatocytes mediating the inhibitory immune effect on B cells. GM12878 B cells were cultured in conditioned medium (CM) from HepG2 cells stimulated with 200\u0026micro;M PA (CM-PA) or BSA (CM-BSA). The mRNA of \u003cem\u003eFcer2α\u003c/em\u003e, \u003cem\u003eCd22\u003c/em\u003e, \u003cem\u003eCr2\u003c/em\u003e and \u003cem\u003eFcmr\u003c/em\u003e of cluster 3 were unifiedly downregulated in GM12878 cells incubated in the CM-PA versus CM-BSA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). In cluster 14, the mRNA of \u003cem\u003eTnfrsf17\u003c/em\u003e, \u003cem\u003ePrdm1\u003c/em\u003e and \u003cem\u003eDerl3\u003c/em\u003e were consistently downregulated in CM-PA group compared with CM-BSA, except for \u003cem\u003eDnah3\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Compared to CM-BSA, CM-PA exhibited a downregulated effect on \u003cem\u003eChdh\u003c/em\u003e, whereas an unregulated effect on \u003cem\u003eDntt\u003c/em\u003e and \u003cem\u003eKlk1\u003c/em\u003e in cluster 16 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). In cluster 20, CM-PA coculture resulted in lower mRNA levels of \u003cem\u003eApol1 (Apol7c)\u003c/em\u003e and \u003cem\u003eArhgap22\u003c/em\u003e compared to CM-BSA, except for \u003cem\u003eLad1\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). These findings indicate that downregulation of \u003cem\u003eFcer2α\u003c/em\u003e and \u003cem\u003eTnfrsf17\u003c/em\u003e in B cells contributes to NASH progression.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePresence of\u003c/b\u003e \u003cb\u003eFcer2α\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eB cells subpopulation in NASH mice livers\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo determine the alteration of \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells in NASH, we assessed the percentage of \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eCd79a\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e cells in liver tissues of NASH mice by IF staining (n\u0026thinsp;=\u0026thinsp;3 per group). \u003cem\u003eCd79a\u003c/em\u003e served as a B cell marker. Nuclei were visualized by DAPI (blue IF). The portal area of liver tissues contained abundant \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e (green IF) \u003cem\u003eCd79a\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e (red IF) cells in control mice, but contained rare \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eCd79a\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e cells in NASH mice (NASH vs control group: 23.64\u0026thinsp;\u0026plusmn;\u0026thinsp;10.88% vs 64.92\u0026thinsp;\u0026plusmn;\u0026thinsp;6.87%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE-F). Then we checked the percentage of \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eCd79a\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e cells in liver tissues of NASH patients by IF staining. Mild NAFLD and advanced NASH was distinguished through H\u0026amp;E staining of liver tissues from patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG-H). IF staining of human liver tissues showed a substantial decrease in \u003cem\u003eFcer2α\u003c/em\u003e⁺\u003cem\u003eCd79a\u003c/em\u003e⁺ cells in advanced NASH patients compared to mild NAFLD controls (advanced NASH vs mild NAFLD group: 9.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63% vs 26.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.93%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI-J). These findings, consistent with scRNA-seq results, suggested the diminished \u003cem\u003eFcer2α\u003c/em\u003e⁺ B cell subgroup was involved in NASH pathogenesis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFcer2α\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eB cells could attenuate inflammation in NASH\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe further aimed to clarify the function of \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells in NASH. Given that \u003cem\u003eFcer2α\u003c/em\u003e⁺ B cells constituted the predominant hepatic B cell subset yet were significantly reduced in the livers of NASH, we established \u003cem\u003eFcer2α\u003c/em\u003e overexpressing (ov-\u003cem\u003eFcer2α\u003c/em\u003e) and the control (ov-NC) GM12878 cells in a lipotoxic model (cocultured in CM-PA from HepG2 cells). In lipotxic environment, \u003cem\u003eFcer2α-\u003c/em\u003eoverexpressing B cells exhibited enhanced anti-inflammatory capacity, secreting 2.76-fold more IL-10 and 1.96-fold more IL-35 versus ov-NC cells (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-B).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThen KEGG pathway analysis implicated the \u003cem\u003eFcer2α\u003c/em\u003e signaling of B cells mainly regulated T cell differentiation; we next cocultured T cells (Jurkat cells) with ov-\u003cem\u003eFcer2α\u003c/em\u003e or ov-NC B cells (GM12878 cells) in the lipotoxic CM-PA. While coculturing with ov-\u003cem\u003eFcer2α\u003c/em\u003e B cells in the lipotoxic CM-PA, suppressed T cell-driven inflammation occurred, as reducing IFN-γ, TNF-α, and IL-17 secretion of T cells (ov-\u003cem\u003eFcer2α\u003c/em\u003e group vs. ov-NC group by IFN-γ: 61.07\u0026thinsp;\u0026plusmn;\u0026thinsp;4.40%, TNF-α: 54.90\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12%, IL-17: 69.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC-E) and diminishing T cell proliferation (EdU⁺ cells in ov-\u003cem\u003eFcer2α\u003c/em\u003e group vs. ov-NC group: 11.55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86% vs. 25.76\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF-G). Therefore, \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e B cells could attenuate lipotoxicity driven inflammation by enhancing anti-inflammatory factor secretion and inhibiting T cell proliferation.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eNAFLD is projected to become the primary cause of end-stage liver disease and is associated with increased risks of cardiovascular disease and type 2 diabetes \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. NASH prevalence is approximately 4.76% globally and represents the second leading etiology for liver transplantation in the US, with incidence rising \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. The mechanisms underlying NASH are multifactorial and remain incompletely understood.\u003c/p\u003e\u003cp\u003eB cells are classified B1 and B2 subsets based on surface markers. They participate in NAFLD via cytokines/antibodies secretion and inflammation activation. High-fat diet induced NASH mice showed B cell accumulation expressing inflammatory cytokines and activating T cells \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Barrow et al. demonstrated intrahepatic B2 cell accumulation in NASH mice livers. expressing proinflammatory genes and secreting IL-6 and TNF-α to promote inflammation and fibrogenesis \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRecent scRNA-seq studies confirm B cell heterogeneity in NASH. Through sc-RNAseq, Barrow et al identified 3 specific clusters of B cells \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Xiong et al supported a B cells subset highly expressed Cxcl12/Cxcr4 with a fibrogenic function by sc-RNAseq analysis in NASH \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Deczkowska et al found a reduction of hepatic B cells in MCD induced NASH mice through scRNA-seq \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. In our study, 21 major clusters of single-NPC were found based on cell-specific markers between MCD induced NASH and control mice livers by scRNA-seq analysis. Four single-B cell clusters were characterized. The total B cell percentage decreased significantly in NASH livers, consistent with previous report \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eInterestingly, B cells of cluster 3 (the major cluster) was mature B cells. The cellular function of cluster 3 consisted of B cells activation and differentiation, and lymphocyte differentiation. Importantly, cluster 3 mainly contained with \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells and the proportion of them was decreased in NASH. \u003cem\u003eFcer2α\u003c/em\u003e is also known as a marker for B regulatory cells with inhibition function of inflammation \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Our study proved \u003cem\u003eFcer2α\u003c/em\u003e mRNA downregulation in lipotoxic B cells, and fewer portal \u003cem\u003eFcer2α\u003c/em\u003e⁺ B cells in NASH patients/mice versus controls. Functional study showed \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e B cells alleviated NASH by enhancing anti-inflammatory factor secretion and inhibiting T cell proliferation. Ge et al. similarly found \u003cem\u003eCD20\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e\u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e\u003cem\u003eIL10V\u003c/em\u003e Breg cells exert immunosuppressive effects \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Therefore, we speculated that decreasing \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e mature B cells distributed in cluster 3 perhaps play an inhibition of inflammatory role in NASH. In cluster 3, \u003cem\u003eCr2\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/Fcmr\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/Cd22\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells were also seen, this set of genes (\u003cem\u003eCd22\u003c/em\u003e, \u003cem\u003eCr2\u003c/em\u003e and \u003cem\u003eFcmr\u003c/em\u003e) were consistently downregulated in lipotoxic B cells. Allman et al. proposed that \u003cem\u003eCr2\u003c/em\u003e was highly expressed on B cells and selected by BCR signaling during transition and maturation \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Kubagawa et al. found \u003cem\u003eFcmr\u003c/em\u003e\u003csup\u003e\u003cem\u003eKO\u003c/em\u003e\u003c/sup\u003e mice would impair B cell tolerance as concomitantly producing autoantibodies of IgM/G \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003eCd22\u003c/em\u003e is an inhibitory receptor expressed in B cells involved in preventing autoimmune diseases and leukemia delevopment \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Therefore, these results need further exploration.\u003c/p\u003e\u003cp\u003eThen, B cells in cluster 14 were identified as PCs based on specific markers (\u003cem\u003eTnfrsf17\u003c/em\u003e, \u003cem\u003eDnah3\u003c/em\u003e, \u003cem\u003ePrdm1\u003c/em\u003e and \u003cem\u003eDerl3\u003c/em\u003e), and these PCs were decreased in NASH. The cellular function of cluster 14 maybe related to ER stress and N-glycan biosynthesis. Cluster 14 mainly contained with \u003cem\u003eTnfrsf17\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells and the proportion of them was decreased in NASH. Indeed, \u003cem\u003eTnfrsf17\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells typically induce pro-inflammatory cytokines (e.g., IL-6, TNF-α) in autoimmune diseases, thereby activating chronic inflammatory responses. Levels et al. reported that \u003cem\u003eTnfrsf17\u003c/em\u003e was upregulated in synovial tissue B cells from rheumatoid arthritis patients, where they promoted synovitis progression via the production of pathogenic autoantibodies \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Similarly, Kim et al found systemic lupus erythematosus patients exhibited increasing \u003cem\u003eTnfrsf17\u003c/em\u003e expression on B cells, and enabled \u003cem\u003eTnfrsf17\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells to drive inflammatory progression by enhancing TLR9-triggered secretion of anti-dsDNA and ANA autoantibodies \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e.The role of \u003cem\u003eTnfrsf17\u003c/em\u003e⁺ PCs requires further investigation.\u003c/p\u003e\u003cp\u003eCluster 16, also a minor B cell group, was identified. In the same way, the cell function is activate, differentiate and regulate T cells. In our study, \u003cem\u003eKlk1\u003c/em\u003e mRNA was upregulated in lipotoxic B cells. Zhang et al. identified Klk1 inhibition in the inflamed prostates; exogenous Klk1 restored endothelial function and exerted anti-inflammatory, antifibrotic, and antioxidative stress effects in the rat chronic-inflamed prostate \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. The mechanism of \u003cem\u003eKlk1\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells remains unclear in NASH. Finally, the very small cluster 20 was enriched, and the cell function was inferred in dysregulation of apoptosis, NF-κB, TNF and chemokine. \u003cem\u003eApol7c\u003c/em\u003e mRNA was downregulated in lipotoxic B cells in our study. Uzureau et al. previously linked \u003cem\u003eApol7\u003c/em\u003e knockdown to increased dendritic cell survival and \u003cem\u003eApol7c\u003c/em\u003e interaction with Bcl-xL \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. But \u003cem\u003eApol7c\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e B cells were undefined in NASH.\u003c/p\u003e\u003cp\u003eThis study provides interesting insights into distinct B cell subsets and their potential roles in NASH, but several limitations exist. Firstly, The captured B cell number (1106 control, 581 NASH) limited resolution for rare subpopulations and assessment of biological variability. Secondly, While transcriptional clusters and potential functions were inferred via gene expression, pathway analysis, and \u003cem\u003ein vitro\u003c/em\u003e assays, \u003cem\u003ein vivo\u003c/em\u003e functional validation is lacking. Thirdly, The MCD diet model does not fully recapitulate human NAFLD metabolic features (e.g., obesity, insulin resistance), potentially limiting translational relevance. Future studies should incorporate robust functional validation and models/samples better reflecting human pathology.\u003c/p\u003e\u003cp\u003eIn summary, the composition of four undefined single-B cell subsets is altered in NASH. We identified a subgroup of \u003cem\u003eFcer2a\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e mature B cells, significantly reduced in NASH, which likely exerted anti-inflammatory or immunosuppressive effects.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e* Ethics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal study was approved by the Institutional Animal Care and Use Committee of Shanghai East Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;* Consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo human research participants in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e* Availability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eSequence data that support the findings of this study is available through GEO database (number GSE225786).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e* Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest that pertain to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e* Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (No. 82270604).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e* Authors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceived the study design: S.Z.L. and M.Y.X.\u003c/p\u003e\n\u003cp\u003ePerformed the experiments and analysed the data: T.M., Z.Q.C., H.Y.L. and J.C.L.\u003c/p\u003e\n\u003cp\u003eAnalysed the scRNA-seq data set: H.Y.L., L.T and S.Z.L.\u003c/p\u003e\n\u003cp\u003eWrote the manuscript: M.Y.X.,J.C.L. and T.M.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.Sequence data that support the findings of this study is available through GEO database (number GSE225786).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllen AM, Lazarus JV, Younossi ZM, Healthcare and socioeconomic costs of NAFLD: a global framework to navigate the uncertainties. 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Oxid Med Cell Longev, 2022: 2022: 1247806.\u003c/li\u003e\n\u003c/ol\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":"Non-alcoholic steatohepatitis, B cell, single-cell RNA sequencing, Fcer2α","lastPublishedDoi":"10.21203/rs.3.rs-7607404/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7607404/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo understand the heterogeneity of single-B cell responses to Non-alcoholic steatohepatitis (NASH), we performed Single-cell RNA sequencing (scRNA-seq) on single-B cells isolated from control and MCD-fed mice livers. Subsequent analyses included \u0026nbsp;clustering, identification of differentially expressed genes (DEGs) and enrichment analysis. The expressions of high specific DEGs were validated using quantitative real-time PCR (qRT-PCR), immunofluorescence staining and function study. Four single-B cell clusters (3, 14, 16 and 20) were identified. The total number and proportion of B cells significantly decreased in NASH mice livers. In cluster 3, the decreasing \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e mature B cells were supposed with anti-inflammatory role associated with B cell activation and differentiation of other immune cells in NASH. The DEGs (\u003cem\u003eFcer2α\u003c/em\u003e,\u003cem\u003e Cd22\u003c/em\u003e, \u003cem\u003eCr2 \u003c/em\u003eand \u003cem\u003eFcmr\u003c/em\u003e) of cluster 3 were consistently downregulated in B cells cocultued with lipotoxic hepatocytes. And the portal area of livers contained fewer \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e\u003cem\u003e+ \u003c/em\u003e\u003c/sup\u003eB cells in NASH patients and mice compared with controls. \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e B cells attenuated\u0026nbsp;lipotoxicity-driven inflammation\u0026nbsp;by\u0026nbsp;enhancing anti-inflammatory factor (IL-10, IL-35) secretion and\u0026nbsp;inhibiting T cell inflammatory factor (IFN-γ, TNF-α, IL-17) production and proliferation. The other 3 clusters (14, 16 and 20) contained small numbers of single-B cell. \u003cem\u003eTnfrsf17\u003c/em\u003e\u003csup\u003e\u003cem\u003e+ \u003c/em\u003e\u003c/sup\u003eplasmacytes (PCs) of cluster 14 were identified with the effect related to endoplasmic reticulum stress and N-Glycan biosynthesis. \u003cem\u003eKlk1\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e \u003c/em\u003eB cells of cluster 16 were implicated in regulating immune response in NASH. \u003cem\u003eApol7c\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e \u003c/em\u003eB cells of cluster 20 participated in apoptosis, NF-κB, TNF and chemokine pathway in NASH. Thus, a subgroup of \u003cem\u003eFcer2α\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e mature B cells, diminished in NASH, likely exerted anti-inflammatory or immunosuppressive effects.\u003c/p\u003e","manuscriptTitle":"Single-Cell Transcriptomic Landscape of Intrahepatic B Cells in NASH","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 07:38:18","doi":"10.21203/rs.3.rs-7607404/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":"a50635e9-d58d-4819-89b6-2bd28cac1202","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-02T08:39:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 07:38:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7607404","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7607404","identity":"rs-7607404","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}