Autoimmunity最新文献

Primary membranous nephropathy (pMN) is an autoimmune glomerular disease characterized by subepithelial immune complex deposition, involving IgG4 dominant autoantibodies targeting podocyte antigens. Although glomerular IgG3 deposition has been identified in some cases of pMN, its clinical significance remains unclear. This was a retrospective cohort study. One hundred and eighty-nine patients with biopsy-proven pMN from Tianjin Medical University General Hospital between July 2021 and December 2022 were retrospectively enrolled. Clinical, laboratory, pathological features, and treatment outcomes were compared between patients with and without glomerular IgG3 deposition. The primary endpoint of this study was the remission of proteinuria, including complete remission (CR) and partial remission (PR). The deposition of IgG3 was detected by direct immunofluorescence. Among the 189 patients with pMN, glomerular IgG subclasses were observed as follows: IgG1 in 167 patients (88.4%), IgG2 in 25 (13.2%), IgG3 in 44 (23.3%) patients, and IgG4 in 185 (97.9%) patients. Compared to those without glomerular IgG3 deposition, patients with IgG3 deposition were significantly younger, exhibited a lower level of anti-phospholipase A2 receptor (PLA2R) antibodies and a lower level of urinary protein. Pathologically, they showed less glomerular segmental sclerosis, less IgG1 deposition and a lower positivity rate of PLA2R expression. During a median follow-up of 20 months, Kaplan-Meier analysis showed that patients with IgG3 deposition achieved higher rates of both renal remission (log-rank, P = 0.005) and complete remission (log-rank, P = 0.011), particularly among those with stronger IgG3 staining. Multivariate Cox analysis identified IgG3 deposition was associated with cumulative remission (HR = 1.998, P = 0.020) and complete remission (HR = 1.065, P = 0.002), with high anti-PLA2R antibody level, and urinary protein identified as independent risk factors. Compared with patients without renal IgG3 deposition, patients with renal IgG3 deposition had higher levels of total IgG3 and IgG3 subclass anti-PLA2R antibodies in blood, but lower levels of total IgG1 and IgG1 subclass anti-PLA2R antibodies. The ability of blood anti-PLA2R antibodies to activate complement was slightly higher but without statistical significance. Within the cohort of the current study, patients with pMN with renal IgG3 deposition did not show more severe clinical manifestations, which might be related to the lower total autoantibody levels in the blood.

The pentraxin-3 (PTX3) protein can activate and modulate complement and immune cells. IgG anti-PTX3 antibodies are suggested to protect against lupus nephritis (LN). This study aimed to evaluate anti-PTX3 IgG antibody levels across three rheumatic diseases, investigate the linear epitopes of PTX3, and identify potential clinical associations in systemic lupus erythematosus (SLE). A subsequent aim was to examine neutrophil immunoregulatory effects of selected epitopes as synthesized peptides. Microarray-based linear epitope mapping of PTX3 was performed, and neutrophils isolated from blood of healthy blood donors (HBD) to assess potential peptide-mediated effects. Anti-PTX3 levels did not differ between patients with SLE and those with other rheumatic diseases or HBD but were significantly lower in active SLE than in clinically quiescent SLE. In SLE, 17 unique PTX3 antibody epitopes were identified, and epitope-specific antibodies were associated with complement consumption, active SLE, and LN. Epitope-based synthetic peptides can inhibit the neutrophil oxidative burst. In conclusion, anti-PTX3 antibodies in SLE show substantial epitope spreading compared to healthy individuals, while their levels are significantly lower in patients with active SLE. Some of these epitopes are associated with the clinical features of SLE. As peptides, selected PTX3 epitopes might exert immunomodulatory functions on neutrophils.

Breast cancer (BC) remains a major cause of cancer-related mortality among women worldwide, with immune escape being a critical mechanism contributing to tumor progression and therapy resistance. Glutamine-fructose-6-phosphate transaminase 1 (GFPT1) has been implicated in cancer metabolism, yet its role in tumor immunity remains poorly understood. This study aimed to investigate whether GFPT1 promotes immune evasion in BC and to elucidate the underlying molecular mechanisms. A Transwell-based co-culture system with pre-activated human PBMCs was used to model immune‒tumor interactions. Flow cytometry was used to assess T cell subsets, and quantitative real-time PCR evaluated exhaustion markers. LDH release and cytokine levels were measured to evaluate cytotoxicity. Molecular interactions were examined through immunoprecipitation (IP), Co-IP, immunofluorescence, and Western blot. The results showed that GFPT1 was significantly overexpressed in BC tissues and cell lines, correlating with poor patient survival. Knockdown of GFPT1 enhanced CD8⁺ T-cell infiltration, cytotoxic activity, and pro-inflammatory cytokine release, while reducing the expression of exhaustion markers. GFPT1 physically interacted with OGT and regulated its expression. Mechanically, OGT mediated the O-GlcNAcylation of CD39 at Ser239, increasing its stability. CD39 overexpression rescued the immune-inhibitory phenotype after OGT knockdown. In vivo, GFPT1 silencing suppressed tumor growth. Overall, this study displayed the promoting effect of GFPT1 on the immune escape of BC, which provides new therapeutic targets for the immunotherapy of BC.

Systemic lupus erythematosus (SLE), characterized by immune dysregulation, urgently requires improved diagnostic tools and mechanistic insights. The role of interferon regulatory factor-1 (IRF-1) remains unclear. We integrated single-cell transcriptomes (scRNA-seq; GSE254176), 6 bulk transcriptomic datasets (1079 SLE patients, 137 controls, GSE72326 and GSE61635 were merged as training datasets, including 256 SLE patients and 50 controls), and clinical samples (70 SLE patients and 58 controls). IRF-1 dynamics in T-cell subsets were analyzed via clustering and pseudotemporal trajectory. Diagnostic genes were identified by intersecting single-cell-derived IRF-1-associated markers with SLE differential genes, followed by feature selection. Six machine learning models were trained and validated in four independent cohorts. scRNA-seq revealed significant downregulation of IRF-1 in T-cell subsets (central memory CD8⁺, Th17) during active SLE, with compensatory overexpression in remission-validated clinically. Cross-analysis identified four IRF-1-correlated diagnostic genes: CCR7, CD274, KLRB1, and NRCAM, that are enriched in MAPK signaling and immune receptor activity. Generalized linear model (GLM) and partial least squares (PLS) models achieved superior diagnostic accuracy across validation cohorts. Immune analysis revealed decreased numbers of resting CD4⁺ memory T cells and Tregs (P < 0.01), alongside expanded proinflammatory cells (M1/M2 macrophages, neutrophils; P < 0.01). IRF-1 regulates T-cell differentiation and contributes to SLE immune imbalance. The IRF-1-associated gene-based machine learning model provides a robust, noninvasive diagnostic tool.

Osteoarthritis (OA) is a chronic joint disorder characterized by cartilage degradation and accompanied by inflammatory processes. Inflammation and autophagy dysfunction have been associated with the pathogenesis of OA. However, the interplay between autophagy- and inflammation-related genes in the development of OA remains poorly understood. RNA sequencing data of OA samples and autophagy-related genes (ARGs) were obtained from public databases, while inflammation-related genes were extracted from published literature. Differentially expressed genes (DEGs) in the OA dataset were identified using the limma R package. Using WGCNA, we identified autophagy-related gene modules (WGCNA-ARGs), and differential expression analysis was conducted to detect differentially expressed inflammation-related genes (IDEGs). Subsequently, candidate genes were identified by intersecting DEGs, WGCNA-ARGs, and IDEGs. Four machine learning algorithms-LASSO, SVM, RF, and XGBoost-were employed to screen for biomarkers, with diagnostic performance evaluated by ROC curve analysis. The biological functions and therapeutic potential of the biomarkers were further explored through multiple approaches: enrichment analysis, immune infiltration analysis, chromosomal localization, regulatory network construction, and drug prediction. Finally, the expression levels of the biomarkers were validated in clinical samples using RT-qPCR.

Immune-mediated glomerulonephritis (IMGN) is a major cause of kidney failure worldwide, yet the precise roles of T cells in its pathogenesis remain poorly understood. However, existing studies lack a comprehensive understanding of the characteristics and functional roles of IMGN T cells in the human context. Addressing this gap is crucial for advancing targeted therapies. By integrating single-cell RNA sequencing (sc-RNA-seq) data from three primary IMGN types-IgA nephropathy (IgAN), lupus nephritis (LN), and membranous nephropathy (MN)-we identified T cell subtype alterations at single-cell resolution. Utilizing advanced sc-RNA-seq computational pipelines, we constructed gene co-expression networks (GCNs), inferred T-cell differentiation trajectories, and assessed metabolic and intercellular signaling features. IMGN kidneys presented expanded T-cell compartments, with significant enrichment of cytotoxic natural killer T (NKT) cells and GZMK⁺ effector memory T (GZMK⁺ Tem) cells. Notably, LTB⁺ memory T cells (LTB⁺ Tm) were selectively elevated in IgAN and LN patients. A coexpression module centered on RGS1 was significantly correlated with 24-h proteinuria (p < 0.001). Metabolic profiling revealed subtype-specific disruptions in the glutathione (GSH) and 3-phospho-D-glyceroyl phosphate (3PD) pathways. Interaction analysis highlighted endothelial cells, mesangial cells, and fibroblasts as key mediators of pathogenic T-cell activation via defined ligand‒receptor pairs. This study provides the first comprehensive single-cell atlas of human IMGN T cells, revealing disease-specific T-cell states, metabolic signatures, and activation mechanisms. Our findings offer new insights into human renal immunopathology and identify promising therapeutic targets for IMGN.

Epstein-Barr virus (EBV) and cytomegalovirus (CMV) are herpesviruses presumed to trigger autoimmunity. This study assessed the association between acute EBV/CMV infection and antinuclear antibody (ANA) seropositivity. We retrospectively reviewed immunocompetent patients with serologically confirmed acute EBV or CMV who were admitted to the Sheba Medical Center (2019-2023). ANA was tested during the differential diagnosis. Patients with autoimmune/neoplastic diseases were excluded. Among 52 patients (56% female, mean age 42 ± 16.8), CMV patients were older than EBV patients (48 ± 15.3 vs. 25 ± 5.5, p < 0.005). ANA was positive in 79% of CMV and 29% of EBV cases (p < 0.005). Positivity was higher in males than in females (87% vs. 48%, p < 0.05). In CMV, 94% of males and 65% of females were ANA-positive (p < 0.05). No autoimmune diseases were diagnosed during a partial (hospital-based) 1-5 year follow-up. In our cohort, ANA seropositivity was observed more frequently in acute CMV infection and was more common among male patients regardless of age. These results warrant further research into the immunological mechanisms underlying ANA production in CMV infections. Given the unclear clinical significance of ANA seropositivity in the context of acute CMV or EBV infection, routine ANA testing in these patients is generally unnecessary and may lead to unwarranted investigations.

Studies have found that there is tertiary lymphoid structure (TLS) in IgA nephropathy (IgAN), and the existence of TLS has an impact on renal function, creatinine, and proteinuria in patients. We aim to explore the potential molecular mechanisms and therapeutic targets of TLS in IgA nephropathy by bioinformatics methods, hoping to provide treatment methods. The datasets GSE226840, GSE237120, and GSE116626 from the Gene Expression Omnibus (GEO) database were employed to investigate the potential therapeutic targets of TLS in IgAN. The R was used to obtain the differentially expressed genes (DEGs) of three datasets, and the Venny was used to intersect the above three parts of the DEGs to obtain the common DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on obtained genes using Metascape. Protein-Protein interaction (PPI) network was constructed. The intersection of the above common differential genes and IgAN differential genes was obtained by Venny tool. The Nephroseq platform was used to screen core genes and explore their relationship with clinical features. Meanwhile, CIBERSORT was utilized to further delve into the correlation between core genes and immune cells. 92 TLS-related genes and 486 IgAN related genes were obtained, and 6 common genes were obtained after crossing the two genes. The intersection genes were verified by Nephroseq, and CDKN1A, CD83, DUSP6, and CD48 were identified as core genes. At the same time, there were differences in the composition of immune cells between the disease group and the control group when the immune infiltration analysis was performed. And by further analyzing the correlation between core genes and immune cells, the study found that the four genes were positively correlated with T cells, B cells, plasma cells, and other immune cells. By exploring the relationship between core genes and clinical features, CDKN1A and DUSP6 were negatively correlated with Glomerular Filtration Rate (GFR) and positively correlated with proteinuria in IgAN patients. CD48 was negatively correlated with GFR and positively correlated with Blood Urea Nitrogen (BUN). The four genes highly associated with TLS and IgAN were screened using GEO database in study. And CDKN1A, CD83, DUSP6 and CD48 may provide potential therapeutic targets for the treatment of TLS in IgAN. At the same time, studies have found that T cells, B cells, and macrophages may be involved in the formation of TLS in IgAN.

Ankylosing Spondylitis (AS) and Systemic Sclerosis (SSc) are both autoimmune diseases, albeit with distinct anatomical targets. AS primarily affects the spine and sacroiliac joints, triggering inflammation and eventual fusion of the vertebrae. SSc predominantly impacts the skin and connective tissues, leading to skin fibrosis, thickening, and potential damage to vital organs such as the lungs, heart, and kidneys. Despite their differing anatomical manifestations, inflammation serves as a pivotal factor in both conditions. Exploring the causes of the different pathogenesis of inflammation in AS and SSc could provide new insights into their treatment. We selected RNA-seq profiles of peripheral blood mononuclear cells (PBMCs) from the GEO datasets GSE73754 and GSE19617. DEGs were identified using the Limma R package with an adjusted p-value cutoff of < 0.05. Gene Ontology pathway analysis, SVM recursive feature elimination, and Gene Set Enrichment Analysis (GSEA) were conducted to analyze the DEGs. CIBERSORT was applied to estimate immune cell composition and its correlation with hub genes. Single-cell RNA sequencing data from peripheral blood mononuclear cells in the GSE194315 dataset were included to support differential expression analysis and biomarker identification. Additionally, single-cell RNA sequencing data from bone marrow blood samples were utilized to further validate these findings, offering complementary insights into biomarker expression across distinct sample types. A total of 762 DEGs were identified between AS patients and controls, and 441 DEGs between SSc patients and controls. Both conditions showed enrichment in the Natural killer cell mediated cytotoxicity pathway. ZSWIM6 and CCL3L3 were identified as potential biomarkers in AS and SSc, with significant diagnostic capabilities demonstrated by ROC analysis. Correlation analysis revealed associations between these biomarkers and specific immune cell types. The study utilizing ZSWIM6 and CCL3L3 as potential biomarkers provides deep insights into the distinct molecular mechanisms of SSc and AS. These findings lay the foundation for future research on targeted therapies and enhance our understanding of immune cell interactions in these autoimmune diseases.

Background: Exosomes derived from cancer-associated fibroblasts (CAFs) can affect tumor microenvironment (TME) of thyroid cancer (TC). The cAMP response element binding protein 1 (CREB1) acts as a transcription factor to participate in cancer development. Currently, we aimed to explore the molecular mechanism of exosome-associated CREB1 and C-C motif chemokine ligand 20 (CCL20) in TC.

Methods: The mRNA and protein levels were examined via RT-qPCR and western blot. Gene interaction was analyzed using ChIP and dual-luciferase reporter assays. Cell migration, invasion and proliferation were assessed by wound healing, transwell and EdU assays. Exosomes were characterized by morphology observation and western blot. The proliferation and apoptosis of CD8⁺ T cells were detected by immunofluorescence and flow cytometry. In vivo assays were performed by establishing xenograft models.

Results: CREB1 was highly expressed in TC. CREB1 positively interacted with CCL20 in TC. CREB1 facilitated TC cell migration, invasion and proliferation via targeting CCL20. CCL20 expression was reduced by transferring CAFs-secreted exosomes sheltering CREB1 downregulation. Exosomal CREB1 knockdown receded cell progression and enhanced CD8⁺ T function by mediating CCL20. CAFs-associated exosomal CREB1 downregulation inhibited tumorigenesis through affecting CCL20.

Conclusion: CAFs-derived exosomes accelerated the malignant behaviors and immune evasion in TC by carrying CREB1 to up-regulate CCL20.