Critical reviews in immunology · 2026
Single-Cell Transcriptomic Analysis Reveals ISG15 as a Key Regulator of Macrophage-Mediated Inflammation Driving Primary Sjögren's Syndrome Progression.
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Chao Yajing, Dong Jian, Chen Kunting, Fu Yalu
Аннотация
OBJECTIVES: Primary Sjögren's syndrome (pSS) is characterized by molecular heterogeneity and immune-metabolic dysregulation. This study aimed to identify diagnostic biomarkers and characterize monocyte-macrophage differentiation trajectories in pSS.
METHODS: Bulk RNA-seq data were first batch-corrected and subjected to differential expression analysis, immune infiltration profiling, and weighted gene co-expression network analysis (WGCNA) to identify key gene modules. For single-cell RNA-seq, 42,157 salivary gland cells were clustered and annotated; Monocle3 pseudotime analysis reconstructed the monocyte-macrophage differentiation trajectory, and CellChat quantified intercellular signaling networks. Candidate immune-metabolism biomarkers were then screened by integrating WGCNA results with three machine-learning algorithms, LASSO regression, SVM-RFE, and random forest, and validated in the external GSE84844 cohort. Finally, functional relevance was tested in PMA-induced THP-1 macrophages by knocking down ISG15 and measuring effects on NF-κB activation and secretion of TNF-α and IL-1β.
RESULTS: Pseudotime analysis delineated a monocyte-to-macrophage differentiation axis and pinpointed 182 dynamic marker genes. Integrated machine-learning and network analysis highlighted four immune-metabolism genesISG15, OAS1, LAP3, and PARP9each achieving AUC > 0.80 in the GSE84844 validation set. In vitro, ISG15 knockdown markedly attenuated NF-κB activation and reduced TNF-α/IL-1β release, confirming its pivotal role in pSS-associated inflammation.
CONCLUSIONS: This integrated transcriptomic analysis highlights key monocyte-macrophage trajectories and identifies four robust immune-metabolism biomarker candidates for pSS diagnosis. Functional validation of ISG15 suggests it plays a pivotal role in driving macrophage-mediated inflammatory responses in pSS.
METHODS: Bulk RNA-seq data were first batch-corrected and subjected to differential expression analysis, immune infiltration profiling, and weighted gene co-expression network analysis (WGCNA) to identify key gene modules. For single-cell RNA-seq, 42,157 salivary gland cells were clustered and annotated; Monocle3 pseudotime analysis reconstructed the monocyte-macrophage differentiation trajectory, and CellChat quantified intercellular signaling networks. Candidate immune-metabolism biomarkers were then screened by integrating WGCNA results with three machine-learning algorithms, LASSO regression, SVM-RFE, and random forest, and validated in the external GSE84844 cohort. Finally, functional relevance was tested in PMA-induced THP-1 macrophages by knocking down ISG15 and measuring effects on NF-κB activation and secretion of TNF-α and IL-1β.
RESULTS: Pseudotime analysis delineated a monocyte-to-macrophage differentiation axis and pinpointed 182 dynamic marker genes. Integrated machine-learning and network analysis highlighted four immune-metabolism genesISG15, OAS1, LAP3, and PARP9each achieving AUC > 0.80 in the GSE84844 validation set. In vitro, ISG15 knockdown markedly attenuated NF-κB activation and reduced TNF-α/IL-1β release, confirming its pivotal role in pSS-associated inflammation.
CONCLUSIONS: This integrated transcriptomic analysis highlights key monocyte-macrophage trajectories and identifies four robust immune-metabolism biomarker candidates for pSS diagnosis. Functional validation of ISG15 suggests it plays a pivotal role in driving macrophage-mediated inflammatory responses in pSS.