Single-cell Analysis of TFH Cell Subsets in Allergic Rhinitis: Discovery of the GZMK+ TFH Cell Subset

Single-cell Analysis of TFH Cell Subsets in Allergic Rhinitis: Discovery of the GZMK+ TFH Cell Subset | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 23 January 2025 V1 Latest version Share on Single-cell Analysis of TFH Cell Subsets in Allergic Rhinitis: Discovery of the GZMK+ TFH Cell Subset Authors : Jiejun He , Yueqi Sun 0000-0002-2382-0429 , Yang Chen , Yinyan Lai 0000-0003-4553-4383 , Han Lei , Jianbo Shi , and Wenxiang Gao 0000-0002-5048-3907 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.173764981.10010245/v1 408 views 214 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background: Allergic rhinitis (AR) is a prevalent condition linked to IgE-mediated immune responses. T follicular helper (TFH) cells, particularly the TFH2 subset, have been implicated in the pathogenesis of AR due to their role in promoting IgE production. However, the number, functional gene expression, and differences among the three TFH subsets in AR patients remain unclear. Methods: This study recruited six AR patients and three healthy controls. Flow cytometry and single-cell sequencing were used to identify and analyze subsets of TFH cells. TFH1, TFH2, and TFH17 subsets were identified based on CXCR3 and CXCR6 expression. Functional gene expression in TFH subsets of AR patients and healthy controls was analyzed to explore differences in immune responses. Results: AR patients exhibited a significant increase in circulating TFH2 cells compared to healthy controls, correlating with disease severity. Additionally, precursor memory TFH cells were higher in AR patients. However, no significant differences were found in the expression of functional membrane molecules on TFH cells between the two groups. Single-cell RNA sequencing revealed nine TFH clusters with differential expression of functional genes, including a GZMK + TFH subset. The increased proportion of TFH1 and TFH2 subsets in AR compared to controls suggests their significant involvement in the pathogenesis of AR. Conclusions: Our study reveals increased TFH2 cells and differential TFH subset distributions in AR patients, especially the discovery of the GZMK + TFH subset, providing insights into TFH-mediated mechanisms in AR. These findings suggest potential therapeutic targets for AR treatment. Single-cell Analysis of TFH Cell Subsets in Allergic Rhinitis: Discovery of the GZMK + TFH Cell Subset Abstract Background: Allergic rhinitis (AR) is a prevalent condition linked to IgE-mediated immune responses. T follicular helper (TFH) cells, particularly the TFH2 subset, have been implicated in the pathogenesis of AR due to their role in promoting IgE production. However, the number, functional gene expression, and differences among the three TFH subsets in AR patients remain unclear. Methods: This study recruited six AR patients and three healthy controls. Flow cytometry and single-cell sequencing were used to identify and analyze subsets of TFH cells. TFH1, TFH2, and TFH17 subsets were identified based on CXCR3 and CXCR6 expression. Functional gene expression in TFH subsets of AR patients and healthy controls was analyzed to explore differences in immune responses. Results: AR patients exhibited a significant increase in circulating TFH2 cells compared to healthy controls, correlating with disease severity. Additionally, precursor memory TFH cells were higher in AR patients. However, no significant differences were found in the expression of functional membrane molecules on TFH cells between the two groups. Single-cell RNA sequencing revealed nine TFH clusters with differential expression of functional genes, including a GZMK + TFH subset. The increased proportion of TFH1 and TFH2 subsets in AR compared to controls suggests their significant involvement in the pathogenesis of AR. Conclusions: Our study reveals increased TFH2 cells and differential TFH subset distributions in AR patients, especially the discovery of the GZMK + TFH subset, providing insights into TFH-mediated mechanisms in AR. These findings suggest potential therapeutic targets for AR treatment. Keywords: Allergic rhinitis, T follicular helper cells, GZMK + TFH subset, Single-cell analysis. Key Points： 1. Novel identification of TFH2 cells in AR pathogenesis. 2. The precursor memory TFH cells (CCR7 high PD-1 low ) are elevated in AR and correlate positively with disease severity. 3. The diversity and functions of TFH cell subsets, particularly the identification of the GZMK + TFH cell subset. 4. Integration of functional gene expression and disease correlation. 5. Analysis of TFH subsets in AR informs future targeted therapy research. Introduction Allergic rhinitis (AR) is a common global health issue primarily driven by an immunoglobulin E (IgE)-mediated hypersensitivity reaction. 1 It significantly impacts patients’ quality of life and imposes substantial economic burdens. 2 The reported prevalence ranges from 2% to 25% in children and 1% to over 40% in adults. In Europe, the prevalence of AR in adults is estimated to be between 17% and 28.5%. 3,4 The pathogenesis of AR is complex, with helper T cells (Th) playing a pivotal role in the immune response. In particular, the overactivation of Th2 cells has been recognized as a major contributor to AR-related inflammation. 5 However, recent attention has shifted toward the role of follicular helper T (TFH) cells in AR pathogenesis. 6–8 TFH cells, a specialized subset of CD4+ T cells, are critical in B-cell differentiation and antibody production. 9 It is now established that TFH cells expressing CXCR5 are closely linked to IgE production and asthma development. 11 Recent studies have shown a positive correlation between increased peripheral blood CCR7 + TFH2 cells and elevated sIgE levels in AR patients, indicating a preferential polarization of TFH2 cells toward promoting IgE production in these individuals. 12 Although studies have shown that TFH is closely related to the production of IgE, 10 The research on the functional subsets of TFH cells in different immune environments remains limited. Specifically, the differences in TFH cell subsets between AR patients and healthy individuals, as well as changes in the number and function of TFH cells in the peripheral blood of AR patients, have not been thoroughly investigated. Recent research by Saumya Kumar et al. indicated that Th1 and Th2 immune responses preferentially drive TFH1 and TFH2 cells to participate in humoral immunity within lymphoid tissues 13 , but whether there are functional differences in these three TFH subsets in the peripheral blood of AR patients remains unclear. With advances in flow cytometric sorting and single-cell sequencing technologies, 14 we are now better equipped to comprehensively investigate the alterations in the quantity, subsets, and functional genes of TFH cells and their subpopulations in AR patients. Here, we designed an experiment using single-cell sequencing technology to investigate the changes in functional genes, subsets, and cellular functions of TFH cells in the peripheral blood of AR patients. This study is helpful to understand the role and function of TFH cells in the pathogenesis of AR, and to better understand the occurrence and development of AR. Methods 2.1 Subjects All enrolled patients were older than 18 years. The diagnosis of AR was made and disease severity was evaluated based on the Allergic Rhinitis and its Impact on Asthma guidelines. 15 We had three groups of mild, moderate, and severe AR, plus a normal control, totaling nine patients (6 AR vs 3 Healthy), all allergic only to dust mites. Table 1 detailed patient info. For the circulating TFH cell correlation study, peripheral blood samples from AR and healthy subjects underwent cell flow sorting and 10x single cell sequencing. All participants had no oral hormone use in the prior month and no upper respiratory or systemic infections. 2.2 Isolation of PBMCs 30ml heparinized peripheral blood from all was collected. It was transferred to a 50 mL centrifuge tube, diluted with 30 mL PBS, and 2.5 mL Ficoll - Hypaque Solution (Meijingbio, China) added gently. After 400g centrifugation for 25 minutes, the PBMC layer was isolated, washed with HBBS, and the process repeated. 2.3 Flow Cytometry and Cytoflow Sorting of TFH Cells After PBMCs isolation, cells were stained with CD4 + and CD3 + antibodies and analyzed by flow cytometry. CD4 + T cells were flow-sorted, and CD127 + CD25 - cells were selected. CXCR5 + CD45RA - TFH cells were further sorted. TFH subsets were analyzed using monoclonal antibodies for CCR6, CXCR3, ICOS, PD1, and OX40. Cells were detected by fluorescence-activated cell sorting (FACS), and data were analyzed using FCS3.0 and Kaluza software. 2.4 Preparation of Single Cell Suspension Cells in DMEM (ThermoFisher Scientific, Waltham, MA) were transported on ice, filtered through a 40µm strainer, and centrifuged at 300g for 6 minutes at 4°C. The pellet was resuspended in DMEM and kept on ice pre - staining. 2.5 Sequencing Library Construction Using the 10x Chromium Platform Approximately 15,000–20,000 cells were partitioned into droplets, with each cell tagged with a unique barcode. Full-length cDNA was prepared, and quantitative PCR was performed for NovaSeq 6000 sequencing. Sequence data were generated with ~50K read pairs per cell. 2.6 Single-cell RNA-seq Data Preprocessing Cell Ranger (v3.1.0) demultiplexed barcodes, mapped reads with STAR, and down - sampled for normalized data and a gene-cell matrix. Seurat (v3.1.1) processed the UMI count matrix. Low quality cells (UMI/gene numbers outside mean ± 2sd) and those with >10% mitochondrial gene counts were filtered. After QC, over 10000 cells remained. Seurat normalized library size. Top variable genes were identified. PCA reduced dimensionality. Cells were clustered and visualized with t-SNE. Likelihood ratio test found differentially expressed genes. SingleR with the ‘Human Primary Cell Atlas’ identified cell types. Seurat’s FindMarkers function identified DEGs (P 0.58). 2.7 Statistical Analysis All statistical analyses were carried out with GraphPad Prism Software 5.0 (GraphPad Software). Expression data are presented in dot plots. Symbols represent individual samples, horizontal bars represent medians, and error bars show interquartile ranges. The Mann-Whitney U test was used for between-group comparisons. Cell-culture data are expressed as means 6 SEMs and analyzed by using the unpaired Student t test, unless specifically stated. For categorical data, x2 or Fisher exact tests were performed. Spearman rank correlation analysis was used to analyze the associations. P values of less than .05 were considered statistically significant. Results 3.1 The Circulating TFH2 Cells Were Higher in AR Patients and Increased with The Severity of the Disease Flow cytometry was performed to sort circulating CD4 + T cells from AR patients and normal PBMCs, and TFH cells were analyzed (Figure 1A). TFH cells were classified into three subsets based on surface markers: TFH1 (CXCR3 + CCR6 − ), TFH2 (CXCR3 - CCR6 − ), and TFH17 (CXCR3 - CCR6 + ). 16 Our results showed no significant differences in the proportions of total TFH, TFH1, and TFH17 cells between AR patients and controls. However, TFH2 cells were significantly elevated in AR patients (Figure 1B). Furthermore, TFH2 expression positively correlated with AR severity. Among six AR patients, those with moderate and severe symptoms had higher TFH2 levels than mild AR patients and controls (Figure 1C), while no significant differences in TFH1 and TFH17 proportions were observed across these groups. These data indicate that circulating TFH2 cells may be linked to AR severity and progression. We also found no significant difference in the positive expression rates of ICOS, PD1, and OX40 on cTFH cells between the AR and normal groups(Figure S1A,B), indicating that TFH cells may not directly induce the TH2 immune response through TH2-specific inflammatory membrane molecules, but rather through other mechanisms. 3.2 The Circulating Precursor Memory TFH Cells Were Higher in AR Patients Than Normal Group Except for TFH1, TFH2, and TFH17, cTFH cells also include activated CCR7 low PD-1 high and resting CCR7 high PD-1 low subsets (Figure 2A). 17 Resting cTFH cells, or precursor memory TFH, recirculate through blood like central memory T cells (T CM ) and possess developmental plasticity. Activated cTFH cells likely originate from GCs. 18 In our study, CCR7 high PD-1 low TFH cells were significantly elevated in AR patients compared to controls (26.02% ± 1.28 vs. 21.59% ± 1.43, P<0.05). Furthermore, these cells were more abundant in moderate and severe AR cases than in mild cases (29.62% ± 2.33 vs. 23.41% ± 1.63, P<0.05) (Figure 2B), suggesting their potential as markers of AR progression. 3.3 Diversity of TFH Subsets in AR Patients by Single Cell Sequencing We analyzed TFH cells from AR patients and normal controls using single-cell sequencing. UMAP analysis separated the two groups into 9 clusters (Figure 3A and B). Significant differences were observed between groups: cluster 1 was mainly expressed in controls, while clusters 2, 3, and 8 were more abundant in AR patients. Clusters 4, 5, and 6 also showed higher expression in AR patients, and cluster 7 was predominantly expressed in controls. Cluster 9 showed a similar distribution in both groups, with AR patients slightly dominant ( Figure 3C, D and E). These results indicate that clusters 1 and 7 are likely associated with normal immune responses. Clusters expressed in AR (clusters 2-6, 8) are linked to specific immune response characteristics, potentially correlating with disease onset and severity. Cluster 9 likely represents a general TFH cell subset that is not influenced by disease states. 3.4 GZMK + TFH cells were found in the TFH cell subset We further analyzed the top 5 expressed genes in each TFH cluster, revealing significant differences across the 9 clusters (Figure 4A-I). We observed that clusters 5 and 6 were enriched for genes linked to cytotoxic effector functions, such as GZMK, CCL5, GNLY, etc. (Figures 4E,F). Recent studies have shown that in allergic and chronic recurrent airway inflammatory diseases, pathogenic CD8 + memory T cell subsets can promote the infiltration of other type 2 inflammatory cells, including eosinophils, through GZMK. The level of GZMK is positively correlated with disease severity, and GZMK has been proposed as a potential biomarker for predicting the recurrence of nasal polyps or comorbid asthma 19 . Based on these findings, we hypothesize that the GZMK + TFH cell subset play a key pathogenic role in AR and may be crucial in its immune regulation and progression. 3.5 Proportional Distribution, Gene Expression, and Functional Profiles of TFH Subsets in AR and Normal Groups We analyzed TFH subsets based on CXCR3 and CCR6 expression. Cluster 5 corresponded to TFH1 (CXCR3 + CCR6 - ), cluster 9 to TFH17 (CXCR3 - CCR6 + ), and clusters 7 and 8 to TFH2 (CXCR3 - CCR6 -) (Figure 5A). UMAP showed TFH17 was the most abundant subset in both groups, followed by TFH2, with TFH1 and TFH2 proportions higher in AR patients (Figure 5B-D). Differential gene analysis revealed increased expression of TFH activation and TH2-type inflammation-related genes (FOS, JUN, NFKBIA), T cell differentiation genes (CD69), and AR regulatory genes (TNFAIP3, DUSP1) in AR patients. In contrast, normal group genes (XIST, HIST1H4C) were linked to sex differences and chromatin maintenance (Figure 5E). These findings highlight the role of TFH1 and TFH2 in AR pathogenesis. GO and KEGG analyses (Figure S2A,B) showed that AR TFH cells were enriched in immune-related pathways, such as T cell activation and translation initiation, while normal TFH cells were linked to processes like protein targeting and mRNA degradation. AR TFH cells also showed enrichment in immune pathways, including antigen presentation and TH17 differentiation. No significant differences in molecular functions were found. These results highlight the unique differentiation and immune function of TFH cells in AR. Discussion More and more research suggests that antigen-specific IgE responses are primarily dependent on TFH cells, rather than Th2 cells 20 . TFH cells are closely linked to IgE production and contribute to the pathogenesis of allergic rhinitis (AR) and allergic asthma. 21 TFH cells are classified into three subsets: TFH1, TFH2, and TFH17, each with functions related to their corresponding T cell subsets. 22 However, the roles of these subsets in AR remain unclear. Understanding the dynamics of TFH subsets could provide significant insights into AR pathogenesis and progression. In this study, we analyzed the proportions and functional gene changes of TFH subsets in AR patients and healthy controls. TFH2 subsets were significantly elevated in AR patients and correlated with disease severity, aligning with the increased levels of atopic IgE in moderate to severe AR, Consistent with previous studies. 23 Notably, flow cytometry revealed no significant changes in the expression of TH2 functional membrane molecules on TFH2 cells, suggesting that TFH2 primarily influences B cells indirectly rather than driving a direct TH2 response. Single-cell sequencing identified nine TFH cell clusters with distinct functional gene profiles. Exccept for cluster 7, which was more abundant in the healthy control group, all other clusters exhibited higher expression n AR patients, particularly clusters 2 and 3. Further analysis of gene expression in different cell clusters revealed that clusters 5 and 6 were enriched with genes associated with cytotoxic effector functions, such as GZMK, CCL5, NKG7, GNLY. Previous studies have indicated that the expression of granzyme (GZM) is a key cytotoxic function of CD8 + T cells, forming the basis for their anti-tumor and anti-viral activities. Ryuichi Aoyagi et al. detected GZMK + TFH cells with cytotoxic characteristics in patient with IgG4-related disease (IgG4-RD), a ondition which pathogenesis involves Th2 cells, Treg cells, cTFH cells, and CD4 + CTLs 24 . Moreover, recent studies by Qi Hai, Zhang Luo, Wang Jianbin, and Liu Xin have shown that GZMK could serve as a biomarker for predicting the recurrence of nasal polyps or comorbid asthma, suggesting that GZMK may directly participate in the type 2 inflammatory response and the pathogenesis of polyp development 19 . Therefore, we hypothesize that GZMK + TFH cells contribute to the progression of AR. Based on CXCR3 and CCR6 expression, TFH subsets can be classified into TFH1, TFH2, and TFH17. The proportions of TFH1 and TFH2 were elevated in AR patients, consistent with flow cytometry results. These findings suggest the existence of previously unrecognized TFH subsets, which may have functional implications in AR pathogenesis. Differential gene analysis also revealed significant upregulation of FOS and CD69 in AR patients. The FOS gene family encodes leucine zipper proteins that form the AP-1 transcription factor complex, regulating cell proliferation, differentiation, and TGF-beta-mediated signaling. 25 Increased FOS expression may enhance TH2 inflammation in AR. CD69, a marker of T cell activation and differentiation, further suggests that TFH cells in AR exert a stronger influence on immune responses. These changes indicate a heightened ability of TFH cells to promote immune activation in AR patients. These findings highlight the critical role of TFH subsets, particularly TFH2, in AR pathogenesis through their impact on IgE production and immune regulation. Future research with larger cohorts and in vitro studies is essential to confirm these observations and explore the mechanistic roles of TFH subsets in AR progression and immune modulation. Conclusion In conclusion, our study found that the proportion of TFH2 cells in peripheral blood of AR patients increased, especially in patients with moderate to severe AR. However, no significant difference in the expression of partial functional membrane molecules of TFH cells between two groups. The single cell sequencing results of TFH showed that there were 9 TFH clusters in AR and control groups, and the proportion of clusters between the two groups was significantly different. The functional gene expression of 9 clusters of cells is also different, with clusters 5 and 6 are more abundant in AR and enriched with genes associated with cytotoxic effector functions, suggesting that the GZMK + TFH subset potentially participates in the progression of AR. Supervised classification of TFH cells based on CXCR3 and CCR6 markers revealed that the proportion of TFH1 and TFH2 subsets was slightly higher in AR patients compared to the control group. Elucidating the the changes in the cell proportions and functional gene expression of TFH cell subsets in AR could provide novel insights into therapeutic strategies for AR and help identify potential targets. In particular, TFH2 cells warrant further investigation to validate their predictive value in the diagnosis and monitoring of AR progression. References 1. An G, Pw H, G R, Gk S. Allergic rhinitis. Lancet (London, England) . 2011;378(9809). doi:10.1016/S0140-6736(11)60130-X2. Ponda P, Carr T, Rank MA, Bousquet J. Nonallergic Rhinitis, Allergic Rhinitis, and Immunotherapy: Advances in the Last Decade. J Allergy Clin Immunol Pract . 2023;11(1):35-42. doi:10.1016/j.jaip.2022.09.0103. Wang XD, Zheng M, Lou HF, et al. 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Demographic summary of subjects in single-cell sequencing study Healthy controls AR P valuae b Total subjects, n 3 6 - Gender, male/female 1/2 4/2 Age (range) a 24.33±3.21 24.66±4.62 0.449 History of smoking (%) 0 1(3) 0.325 SPT to Der p Negative Positive - Specific IgE to Der p (IU/ml) 0.18±0.092 51.22±27.72 0.01 a Mean ± SD. b Wilcoxon rank sum test was conducted for Age, History of smoking (%), Specific IgE to Der p (IU/ml). Figure Legends FIGURE 1 The expression of TFH in healthy people(Normal) and allergic rhinitis (AR) patients in peripheral blood. (A) We separated PBMC from healthy people(n=14), AR patients(n=36) respectively.CD3 + CD4 + T cells were isolated. Then CD45 + CXCR5 + TFH cells were further obtained by flow separation. TFH cells can be further classified into three major subsets: CXCR3 + CCR6 – type 1 TFH (TFH1), CXCR3 – CCR6 – type 2 TFH (TFH2), and CXCR3 - CCR6 + type 17 TFH (TFH17). (B) The percentage of total TFH, TFH1, TFH2, TFH17 within CD4 +T cells in healthy people and AR patients respectively. The percentage of TFH2 cells were significant increase in AR group than normal. In Figure 1B, data are presented as means ± SDs. (C) The percentage of total TFH, TFH1, TFH2, TFH17 within CD4+T cells in healthy individuals and in AR patients of varying severity. FIGURE 2 The precursor memory TFH cells in healthy people(Normal)and AR patients in peripheral blood. (A)We separated CCR7 low PD-1 high CD127 + CD25 + precursor memory TFH by flow cytometry. (B)Then we found the percentage of precursor memory TFH cells were significant increase in the AR group than normal. In Figure 3 B data are presented as means ± SDs. FIGURE 3 Single cell RNA sequencing of peripheral blood TFH in healthy people(Normal) and patients with AR(AR) . (A) U-MAP reduction analysis of TFH in two sample. Colors indicate unbiased cell classification via graph-based clustering. Each dot represents an individual cell. Normal group cells were presented as navy blue and AR group cells were presented as pink. (B) There are total 9 sub-class of cells in Normal group and AR. Clustering and cell-type assignment of U-MAP plot revealed cellular heterogeneity with each cell-types identified and color-coded. (C) and (D) Composition proportion of each subgroup in 9 sub-class of cells (Normal VS AR). (E) Proportion of 9 sub-class of cells of TFH cells in the two groups. FIGURE 4 U-MAP analysis and corresponding violin plot of the nine cluster of TFH top 5 gene. Colors indicate unbiased cell classification via graph-based clustering. Each dot represents an individual cell (A-I). The clusters 1 to 9 of U-MAP plot revealed cellular heterogeneity with each cell-types identified and color-coded. FIGURE 5 Single cell RNA sequencing of TFH subsets (TFH1, TFH2, TFH17) in healthy people (Normal) and allergy rhinitis (AR). (A) TFH sub-set identified through CXCR3 and CCR6. Color scheme is based on z-score distribution from –2.0 (grey) to 2.0 (red). According to the expression of CXCR3 and CCR6, we defined the 5th cluster of TFH as TFH1(CXCR3 + CCR6 - );The 7th, 8th cluster as TFH2 (CXCR3 - CCR6 - ) and the 9th cluster as TFH17 (CXCR3 - CCR6 + ) . The subsequent analysis of TFH1, TFH2 and TFH17 will also be followed according to this cluster principle. (B) The U-MAP of TFH1, TFH2, TFH17 in Normal group and AR. Clustering and cell-type assignment of U-MAP plot revealed cellular heterogeneity with each cell-types identified and color-coded. (C) and (D) Composition proportion of TFH1, TFH2, TFH17 in Normal VS AR. (E) Heat map reports scaled expression [log TPM (transcripts per million) values] of discriminative gene sets for TFH1, TFH2, TFH17 between Normal and AR. Color scheme is based on z-score distribution from –2.0 (grey) to 2.0 (red). Head margin color bars represent the Normal and AR group respective cell subset. TFH1:cluster 5 TFH2:cluster 7, 8 TFH17:cluster 9 Information & Authors Information Version history V1 Version 1 23 January 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Jiejun He The First Affiliated Hospital of Sun Yat-sen University View all articles by this author Yueqi Sun 0000-0002-2382-0429 The Seventh Affiliated Hospital Sun Yat-sen University View all articles by this author Yang Chen First Affiliated Hospital of Nanchang University View all articles by this author Yinyan Lai 0000-0003-4553-4383 The First Affiliated Hospital of Sun Yat-sen University View all articles by this author Han Lei The First Affiliated Hospital of Sun Yat-sen University View all articles by this author Jianbo Shi The First Affiliated Hospital of Sun Yat-sen University View all articles by this author Wenxiang Gao 0000-0002-5048-3907 [email protected] The First Affiliated Hospital of Sun Yat-sen University View all articles by this author Metrics & Citations Metrics Article Usage 408 views 214 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Jiejun He, Yueqi Sun, Yang Chen, et al. Single-cell Analysis of TFH Cell Subsets in Allergic Rhinitis: Discovery of the GZMK+ TFH Cell Subset. Authorea . 23 January 2025. DOI: https://doi.org/10.22541/au.173764981.10010245/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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