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IntroductionImmune cells are involved in the onset and progression of Sjögren’s syndrome (SS). This study explored the causal relationship between immune signature cells and SS, which has not been fully elucidated.MethodsWe conducted univariate, multivariate, and bidirectional Mendelian randomization to investigate the causal relationship between 731 immunological feature characteristic cells and SS pairs and explore the interaction of immune cells in SS.ResultsAfter false discovery rate correction, six immune cells were significantly associated with SS risk. Among them, four contributed to SS (CD24 on memory B cell, CD27 on IgD + CD24 + B cell, CD28 on CD39+ secreting CD4 Treg cell, and CD80 on CD62L + mDC); two appeared to reduce SS risk (CD3 on CD39 + CD8 + T cell and CD38 on IgD + CD38 + B cell). Pleiotropy and heterogeneity were not observed. Three immune cells exerted independent effects for SS (CD27 on IgD + CD24 + B cell, CD80 on CD62L + mDC, and CD38 on IgD + CD38 + B cell); two were risk factors (CD27 on IgD + CD24 + B cell and CD80 on CD62L + mDC); and one was a protective factor (CD38 on IgD + CD38 + B cell). Twenty-three immune cells showed a reverse causal relationship with SS.ConclusionThese findings demonstrate the influence of immune cells on SS risk and the effects of SS on immune cells, providing new clues for further research on the mechanisms underlying SS.

ObjectiveSystemic sclerosis (SSc) is a chronic autoimmune disease characterized by fibrosis. The challenge of early diagnosis, along with the lack of effective treatments for fibrosis, contribute to poor therapeutic outcomes and high mortality of SSc. Therefore, there is an urgent need to identify suitable biomarkers for early diagnosis of SSc.MethodsThree skin gene expression datasets of SSc patients and healthy controls were downloaded from Gene Expression Omnibus (GEO) database (GSE130955, GSE58095, and GSE181549). GSE130955 (48 early diffuse cutaneous SSc and 33 controls) were utilized to screen differentially expressed genes (DEGs) between SSc and normal skin samples. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) were performed to identify diagnostic genes and construct a diagnostic prediction model. The results were further validated in GSE58095 (61 SSc and 36 controls) and GSE181549 (113 SSc and 44 controls) datasets. Receiver operating characteristic (ROC) curves were applied for assessing the level of diagnostic ability. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to verify the diagnostic genes in skin tissues of out cohort (10 SSc and 5 controls). Immune infiltration analysis were performed using CIBERSORT algorithm.ResultsA total of 200 DEGs were identified between SSc and normal skin samples. Functional enrichment analysis revealed that these DEGs may be involved in the pathogenesis of SSc, such as extracellular matrix remodeling, cell-cell interactions, and metabolism. Subsequently, two critical genes (ENHO and NOX4) were identified by LASSO and SVM-RFE. ENHO was found down-regulated while NOX4 was up-regulated in skin of SSc patients and their expression levels were validated by above three datasets and our cohort. Notably, these differential expressions were more pronounced in patients with diffuse cutaneous SSc than in those with limited cutaneous SSc. Next, we developed a novel diagnostic model for SSc using ENHO and NOX4, which demonstrated strong predictive power in above three cohorts and in our own cohort. Furthermore, immune infiltration analysis revealed dysregulated levels of various immune cell subtypes within early SSc skin specimens, and a negative correlation was observed between the levels of ENHO and Macrophages M1 and M2, while a positive correlation was observed between the levels of NOX4 and Macrophages M1 and M2.ConclusionThis study identified ENHO and NOX4 as novel biomarkers that can be serve as a diagnostic prediction model for early detection of SSc and play a potential role in the pathogenesis of the disease.

ObjectiveSystemic sclerosis (SSc) is a chronic systemic disease characterized by immune dysregulation and fibrosis for which there is no effective treatment. Animal models are crucial for advancing SSc research. Tree shrews are genetically, anatomically, and immunologically closer to humans than rodents. Thus, the tree shrew model provides a unique opportunity for translational research in SSc.MethodsIn this study, a SSc tree shrew model was constructed by subcutaneous injection of different doses of bleomycin (BLM) for 21 days. We assessed the degree of inflammation and fibrosis in the skin and internal organs, and antibodies in serum. Furthermore, RNA sequencing and a series of bioinformatics analyses were performed to analyze the transcriptome changes, hub genes and immune infiltration in the skin tissues of BLM induced SSc tree shrew models. Multiple sequence alignment was utilized to analyze the conservation of selected target genes across multiple species.ResultsSubcutaneous injection of BLM successfully induced a SSc model in tree shrew. This model exhibited inflammation and fibrosis in skin and lung, and some developed esophageal fibrosis and secrum autoantibodies including antinuclear antibodies and anti-scleroderma-70 antibody. Using RNA sequencing, we compiled skin transcriptome profiles in SSc tree shrew models. 90 differentially expressed genes (DEGs) were identified, which were mainly enriched in the PPAR signaling pathway, tyrosine metabolic pathway, p53 signaling pathway, ECM receptor interaction and glutathione metabolism, all of which are closely associated with SSc. Immune infiltration analysis identified 20 different types of immune cells infiltrating the skin of the BLM-induced SSc tree shrew models and correlations between those immune cells. By constructing a protein-protein interaction (PPI) network, we identified 10 hub genes that were significantly highly expressed in the skin of the SSc models compared to controls. Furthermore, these genes were confirmed to be highly conserved in tree shrews, humans and mice.ConclusionThis study for the first time comfirmed that tree shrew model of SSc can be used as a novel and promising experimental animal model to study the pathogenesis and translational research in SSc.

Interstitial lung disease (ILD) is a group of diffuse parenchymal infiltrating diseases of different etiologies. The neutrophil-to-lymphocyte ratio (NLR) can reflect ILD's existence, progression, and prognosis and is currently regarded as a promising biological marker. This meta-analysis assessed elevated NLR levels in ILD for their predictive value. From inception to July 27, 2022, the Scopus, Cochrane Library, Web of Science, Embase, and PubMed databases were checked thoroughly. We used the weighted mean difference (WMD) and 95% confidence interval (CI) to compare blood NLR values between groups. We examined the relationship between poor prognoses and elevated NLR concentrations in ILD patients using odds ratios (ORs) and 95% CI. After initially including 443 studies, 24 were ultimately analyzed. Fifteen studies(ILD:n = 2,912, Non-ILD: n = 2,868) revealed that the NLR values in the ILD group were relatively high (WMD = 0.61, 95% CI 0.43-0.79, p = 0.001). Eight articles (with poor prognoses: n = 407, without poor prognoses: n = 340) indicated that ILD patients with poor prognoses had higher NLR values (WMD = 1.33, 95% CI 0.32-2.33, p = 0.01). This distinction was especially noticeable in patients with the connective tissue disease (CTD)associated with ILD subgroup (WMD = 3.53, 95% CI 1.54-5.51, p = 0.0005). The pooled OR for increased NLR levels forecasting poor prognoses of ILD was 1.09 (95% CI 1.03-1.15, p = 0.0008). Increasing blood NLR values have clinical significance and application value for detecting ILD and predicting its poor prognosis, especially in CTD patients.

B cells can be polarized to express various cytokines. The roles of IFNγ and IL-10, expressed respectively by B effector 1 (Be1) and Bregs, have been established in pathogen clearance, tumor growth, autoimmunity and allograft rejection. However, the in vivo role of B cell IL-4, produced by Be2 cells, remains to be established. We developed B-IL-4/13 iKO mice carrying a tamoxifen-inducible B cell-specific deletion of IL-4 and IL-13. After alloimmunization, B-IL-4/13 iKO mice exhibited decreased IL-4+ Th2 cells and IL-10+ Bregs without impact on Th1, Tregs, or CD8 T cell responses. B-IL-4/13 iKO mice rejected islet allografts more rapidly, even when treated with tolerogenic anti-TIM-1 mAb. In ovalbumin-induced allergic airway disease (AAD), B-IL-4/13 iKO mice had reduced inflammatory cells in BAL, and preserved lung histology with markedly decreased infiltration by IL-4+ and IL-5+ CD4+ T cells. Hence, B cell IL-4 is a major driver of Th2 responses in vivo which promotes allograft survival, and conversely, worsens AAD.

Background: The purpose of this study is to analyze the distribution of myositis-specific autoantibodies (MSAs) and myositis-associated autoantibodies (MAAs) in patients with idiopathic inflammatory myopathies (IIMs) in southwest China and to explore the relevance between each subtype, each clinical feature, and to explore the relevance between the laboratory indexes. Methods: For this study, 200 patients with IIMs were tested for myositis autoantibodies. Clinical manifestations and laboratory metrics were collected and the correlations between autoantibodies and clinical phenotypes were analyzed. Results: MSAs were found in 73.5% of the patients. The most frequently MSAs were anti-MDA5 (26.8%), followed by anti-ARS (18.5%). Anti-Ro52 was the most prevalent in MAAs (46.2%). Interstitial lung disease (ILD) and arthralgia were more frequent in anti-MDA5 and anti-Jo-1 positive groups (each p < 0.05). Anti-TIF1-γ and anti-NXP2 were associated with dysphagia (each p < 0.05). Different antibody subtypes were associated with laboratory indicators of response to muscle damage and immune status. Logistic regression showed that anti-MDA5 and anti-Jo-1 were independent risk factors for ILD (OR = 4.542, p = 0.004; OR = 4.290, p = 0.018, respectively) and arthralgia (OR = 7.856, p = 0.000; OR = 5.731, p = 0.004, respectively), whereas anti-TIF1-γ and anti-NXP2 were independent risk factors for dysphagia (OR = 4.521, p = 0.009; OR = 6.889, p = 0.017, respectively). Conclusions: Different antibody subtypes were associated with specific clinical features. Anti-MDA5 and anti-Jo-1 were independent risk factors for ILD and arthralgia. Anti-TIF1-γ and anti-NXP2 were independent risk factors for dysphagia. [ABSTRACT FROM AUTHOR]