基于B细胞单细胞转录组测序的干燥综合征分子分型

doi:10.19723/j.issn.1671-167X.2025.06.004

摘要/Abstract

摘要：

目的: 通过无监督聚类的方法分析B细胞单细胞转录组数据，将干燥综合征(Sjögren syndrome, SS)患者区分为不同亚型，建立SS的分子分型框架；同时根据不同亚型特征基因集构建蛋白质-蛋白质相互作用(protein-protein interaction，PPI)网络以探索不同亚型的核心调控机制，为精准的分子分型提供依据，并揭示SS潜在的治疗靶点，同时探索不同亚型患者的自身抗体及B细胞亚群特点。方法: 从基因表达综合数据库(Gene Expression Omnibus，GEO)获取SS患者(n=24)和健康对照(n=4)单细胞转录组测序数据，构建B细胞图谱并识别SS患者与健康对照的B细胞差异基因。通过无监督聚类将SS患者区分为不同亚型，并通过富集分析其特征基因集推测其生物学过程或通路。利用相互作用基因/蛋白质检索工具(Search Tool for the Retrieval of Interacting Genes/Proteins，STRING)数据库和Cytoscape软件构建PPI网络，推断不同亚型特征基因集的核心功能和潜在的靶点。统计并分析不同亚型患者的自身抗体情况及B细胞亚群比例。结果: 将B细胞识别为8个细胞亚群，包括过渡B细胞、初始B细胞、记忆B细胞、双阴性B细胞1型、双阴性B细胞2型、VAV3⁺IRF1⁺B细胞、GP9⁺B细胞和浆细胞。使用FindAllMarkers功能识别出SS患者与健康对照的B细胞差异基因792个，通过对差异基因无监督聚类分析，将SS患者分为3个亚型。通过富集分析，按照其生物学过程或通路，将3个亚型分别命名为干扰素主导亚型、B细胞活化亚型、内质网应激亚型。针对每个亚型特异的基因表达特征，构建了PPI网络，并筛选出每个亚型中的核心枢纽蛋白。每个亚型拥有不同的B细胞亚群及自身抗体特征：干扰素主导亚型有着最高的初始B细胞和过渡B细胞比例，且抗干燥综合征抗原B (Sjögren syndrome antigen B, SSB)抗体阳性率最高；B细胞活化亚型有着最高的记忆B细胞和双阴性B细胞1型比例；内质网应激亚型则有着最高的VAV3⁺IRF1⁺B细胞比例。结论: 通过无监督聚类分析SS患者与健康对照的B细胞差异表达基因，成功将SS患者分为3个分子分型，各亚型表现出特征性的自身抗体谱和优势B细胞亚群，此分子分型框架揭示了SS的B细胞特征，为探索潜在治疗靶点和指导精准治疗提供了新的依据。

关键词: 干燥综合征, B淋巴细胞亚群, 单细胞测序, 聚类分析, 分子分类

Abstract:

Objective: To establish a molecular classification framework for Sjögren syndrome (SS) by stratifying patients into distinct subtypes through unsupervised clustering of B cell single-cell RNA sequencing (scRNA-seq). This study characterizes subtype-specific gene signatures to construct protein-protein interaction (PPI) networks, thereby elucidating core regulatory mechanisms and potential therapeutic targets. Concurrently, it defines the clinical heterogeneity of SS by profiling autoantibodies and B-cell subset distributions across subtypes. Methods: The scRNA-seq data from 24 SS patients and 4 healthy controls were obtained from the Gene Expression Omnibus (GEO) database. We constructed a B cell atlas and identified differential gene expression profiles between SS and healthy controls B cells. Unsupervised clustering was applied to stratify SS patients into different molecular subtypes. Functional enrichment analysis of subtype-specific gene signatures was performed to infer associated biological processes/pathways. PPI networks were constructed using the STRING database and Cytoscape software to identify core functions and potential therapeutic targets for subtype-specific genes. The prevalence of autoantibodies and proportions of B cell subsets were statistically analyzed across subtypes. Results: The B cells were classified into eight subsets: transitional B cell, naïve B cell, memory B cell, double negative 1 (DN1) B cell, double negative 2 (DN2) B cell, VAV3⁺IRF1⁺ B cell, GP9⁺ B cell, and plasma cell. The FindAllMarkers function identified 792 differentially expressed genes (DEGs) between the SS patients and healthy controls. Unsupervised clustering stratified patients into three subtypes: (1) Inter-feron-dominant subtype characterized by enrichment in type Ⅰ/Ⅱ interferon and non-canonical nuclear factor kappa-B (NF-κB) signaling pathways. This subtype showed the highest proportions of naïve B cells and transitional B cells, along with the highest anti-Sjögren syndrome antigen A (SSA)/Sjögren syndrome antigen B (SSB) positivity. (2) B cell activation subtype characterized by enrichment in Fc receptor and B cell receptor signaling pathways. This subtype exhibited the highest proportions of memory B cells and DN1 B cells. (3) Endoplasmic reticulum stress subtype characterized by enrichment in protein folding and endoplasmic reticulum-associated degradation pathways. This subtype was marked by the highest proportion of VAV3⁺IRF1⁺ B cells. PPI networks identified subtype-specific hub genes regulating these core functions. Conclusion: Stratification of SS patients through clustering of B cell DEGs successfully defined three molecular subtypes (interferon-dominant, B cell activation, and endoplasmic reticulum stress subtypes). Each subtype exhibits distinct autoantibody profiles and B cell subset distributions. This molecular typing framework advances our understanding of SS heterogeneity and provides actionable insights for targeted therapy development.

Key words: Sjögren syndrome, B-lymphocyte subsets, Single-cell sequencing, Cluster analysis, Molecular typing

中图分类号:

R593.2

林文灏, 谢阳, 王芳晴, 王淑盈, 刘香君, 胡凡磊, 贾园. 基于B细胞单细胞转录组测序的干燥综合征分子分型[J]. 北京大学学报（医学版）, 2025, 57(6): 1032-1041.

Wenhao LIN, Yang XIE, Fangqing WANG, Shuying WANG, Xiangjun LIU, Fanlei HU, Yuan JIA. Single-cell RNA sequencing of B cells reveals molecular typing in Sjögren syndrome[J]. Journal of Peking University (Health Sciences), 2025, 57(6): 1032-1041.

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参考文献 29

1	中华医学会风湿病学分会. 干燥综合征诊断及治疗指南[J]. 中华风湿病学杂志, 2010, 14(11): 766- 768.
2	Nocturne G , Mariette X . B cells in the pathogenesis of primary Sjögren syndrome[J]. Nat Rev Rheumatol, 2018, 14(3): 133- 145. doi: 10.1038/nrrheum.2018.1
3	Blair PA , Noreña LY , Flores-Borja F , et al. CD19(+)CD24(hi)CD38(hi) B cells exhibit regulatory capacity in healthy individuals but are functionally impaired in systemic lupus erythematosus patients[J]. Immunity, 2010, 32(1): 129- 140. doi: 10.1016/j.immuni.2009.11.009
4	Arvidsson G , Czarnewski P , Johansson A , et al. Multimodal single-cell sequencing of B cells in primary Sjögren ' s syndrome[J]. Arthritis Rheumatol, 2024, 76(2): 255- 267. doi: 10.1002/art.42683
5	Hubbard EL , Bachali P , Kingsmore KM , et al. Analysis of transcriptomic features reveals molecular endotypes of SLE with clinical implications[J]. Genome Med, 2023, 15(1): 84. doi: 10.1186/s13073-023-01237-9
6	Zhao J , Wei K , Shi Y , et al. Identification of immunological characterization and anoikis-related molecular clusters in rheumatoid arthritis[J]. Front Mol Biosci, 2023, 10, 1202371. doi: 10.3389/fmolb.2023.1202371
7	Zeng D , Yu Y , Qiu W , et al. Immunotyping the tumor microenvironment reveals molecular heterogeneity for personalized immunotherapy in cancer[J]. Adv Sci, 2025, 12(25): 2417593. doi: 10.1002/advs.202417593
8	Korsunsky I , Millard N , Fan J , et al. Fast, sensitive and accurate integration of single-cell data with Harmony[J]. Nat Methods, 2019, 16(12): 1289- 1296. doi: 10.1038/s41592-019-0619-0
9	Slovin S , Carissimo A , Panariello F , et al. Single-cell RNA sequencing analysis: A step-by-step overview[J]. Methods Mol Biol, 2021, 2284, 343- 365.
10	Butler A , Hoffman P , Smibert P , et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species[J]. Nat Biotechnol, 2018, 36(5): 411- 420. doi: 10.1038/nbt.4096
11	Szklarczyk D , Kirsch R , Koutrouli M , et al. The STRING database in 2023: Protein-protein association networks and functional enrichment analyses for any sequenced genome of interest[J]. Nucleic Acids Res, 2023, 51(D1): D638- D646. doi: 10.1093/nar/gkac1000
12	Shannon P , Markiel A , Ozier O , et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks[J]. Genome Res, 2003, 13(11): 2498- 2504. doi: 10.1101/gr.1239303
13	Bader GD , Hogue CWV . An automated method for finding mole-cular complexes in large protein interaction networks[J]. BMC Bioinformatics, 2003, 4, 2. doi: 10.1186/1471-2105-4-2
14	Tarn JR , Howard-Tripp N , Lendrem DW , et al. Symptom-based stratification of patients with primary Sjögren ' s syndrome: Multi-dimensional characterisation of international observational cohorts and reanalyses of randomised clinical trials[J]. Lancet Rheumatol, 2019, 1(2): e85- e94. doi: 10.1016/S2665-9913(19)30042-6
15	Soret P , Le Dantec C , Desvaux E , et al. A new molecular classification to drive precision treatment strategies in primary Sjögren ' s syndrome[J]. Nat Commun, 2021, 12(1): 3523. doi: 10.1038/s41467-021-23472-7
16	Broeren MGA , Wang JJ , Balzaretti G , et al. Proteogenomic analysis of the autoreactive B cell repertoire in blood and tissues of patients with Sjögren ' s syndrome[J]. Ann Rheum Dis, 2022, 81(5): 644- 652. doi: 10.1136/annrheumdis-2021-221604
17	Yang Y , Zhang Y , Liu K , et al. IFI27, a potential candidate molecular marker for primary Sjogren ' s syndrome[J]. Clin Rheumatol, 2025, 44(5): 1949- 1960. doi: 10.1007/s10067-025-07409-9
18	Mohammadnezhad L , Shekarkar Azgomi M , La Manna MP , et al. B-cell receptor signaling is thought to be a bridge between primary Sjogren syndrome and diffuse large B-cell lymphoma[J]. Int J Mol Sci, 2023, 24(9): 8385. doi: 10.3390/ijms24098385
19	Takai T . Roles of Fc receptors in autoimmunity[J]. Nat Rev Immunol, 2002, 2(8): 580- 592. doi: 10.1038/nri856
20	Cavalcanti GV , de Oliveira FR , Bannitz RF , et al. Endoplasmic reticulum stress in the salivary glands of patients with primary Sjögren ' s syndrome, associated Sjögren ' s syndrome, and non-Sjögren ' s sicca syndrome: A comparative analysis and the influence of chloroquine[J]. Adv Rheumatol, 2025, 65(1): 2. doi: 10.1186/s42358-024-00430-7
21	Yin Y , Wang Y , Yu X , et al. Overactivation of XBP1 in plasma cells implies worse survival through innate immunity in esophageal squamous cell carcinoma[J]. Cancer Lett, 2024, 597, 217045. doi: 10.1016/j.canlet.2024.217045
22	Zhou D , Yu X , Yu K , et al. Integrated analysis identifies upregulated SAMD9L as a potential biomarker correlating with the severity of primary Sjögren ' s syndrome[J]. J Inflamm Res, 2023, 16, 3725- 3738. doi: 10.2147/JIR.S413581
23	Zhang R , Alt FW , Davidson L , et al. Defective signalling through the T- and B-cell antigen receptors in lymphoid cells lacking the vav proto-oncogene[J]. Nature, 1995, 374(6521): 470- 473. doi: 10.1038/374470a0
24	Sun M , Wei Y , Zhang C , et al. Integrated DNA methylation and transcriptomics analyses of lacrimal glands identify the potential genes implicated in the development of Sjögren ' s syndrome-related dry eye[J]. J Inflamm Res, 2023, 16, 5697- 5714. doi: 10.2147/JIR.S440263
25	Zhang X , Chen W , Gao Q , et al. Rapamycin directly activates lysosomal mucolipin TRP channels independent of mTOR[J]. PLoS Biol, 2019, 17(5): e3000252. doi: 10.1371/journal.pbio.3000252
26	杜晶晶, 董兴红, 高洁, 等. 原发性干燥综合征患者抗SSB与其他实验室参数相关性研究[J]. 检验医学与临床, 2023, 20(16): 2395- 2399.
27	Feng R , Zhao J , Sun F , et al. Comparison of the deep immune profiling of B cell subsets between healthy adults and Sjögren ' s syndrome[J]. Ann Med, 2022, 54(1): 472- 483. doi: 10.1080/07853890.2022.2031272
28	Chizzolini C , Guery JC , Noulet F , et al. Extrafollicular CD19(low)CXCR5 (-) CD11c (-) double negative 3 (DN3) B cells are significantly associated with disease activity in females with systemic lupus erythematosus[J]. J Transl Autoimmun, 2024, 9, 100252. doi: 10.1016/j.jtauto.2024.100252
29	Nayak RC , Chang KH , Singh AK , et al. Nuclear Vav3 is required for polycomb repression complex-1 activity in B-cell lymphoblastic leukemogenesis[J]. Nat Commun, 2022, 13(1): 3056. doi: 10.1038/s41467-022-30651-7

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Items	Anti-SSA antibodies positive rate (positive/total)	Anti-SSB antibodies positive rate (positive/total)
GROUP1	100.00% (6/6)	100.00% (6/6)
GROUP2	66.67% (8/12)	8.33% (1/12)
GROUP3	60.00% (3/5)	40.00% (2/5)
P value	0.322	< 0.001

B cell subset	GROUP1	GROUP2	GROUP3	GROUP1 vs. GROUP2	GROUP1 vs. GROUP3	GROUP2 vs. GROUP3
DN1/%, $\bar x \pm s$	1.01±0.38	3.66±3.63	1.33±0.49	< 0.001	0.329	0.004
DN2/%, $\bar x \pm s$	4.85±2.39	6.51±3.74	6.65±5.72	0.553	0.792	0.879
Memory/%, $\bar x \pm s$	11.6±3.51	28.01±11.75	16.75±7.80	< 0.001	0.247	0.104
Naive/%, $\bar x \pm s$	65.03±12.20	51.80±13.53	55.61±13.01	0.041	0.177	0.574
VAV3⁺IRF1⁺B cell/%, $\bar x \pm s$	9.46±7.67	5.29±1.38	12.62±5.16	0.124	0.329	< 0.001
Transitional/%, $\bar x \pm s$	8.10±2.53	4.72±1.64	7.04±0.83	< 0.001	0.329	< 0.001

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