IgG4-related disease (IgG4-RD) is a systemic autoimmune disease with unclear pathogenesis. We performed single-cell RNA-seq and surface proteome analyses on 61,379 PBMCs from 9 treatment-naive IgG4-RD patients and 7 age- and sex-matched healthy controls. Integrative analyses were performed for altered gene expression in IgG4-RD, and flow cytometry and immunofluorescence were used for validation. We observed expansion of plasmablasts with enhanced protein processing and activation, which correlated with the number of involved organs in IgG4-RD. Increased proportions of CD4 ⁺ cytotoxic T lymphocytes (CTLs), CD8 ⁺ CTLs-GNLY (granulysin), and γδT cells with enhanced chemotaxis and cytotoxicity but with suppressed inhibitory receptors characterize IgG4-RD. Prominent infiltration of lymphocytes with distinct compositions were found in different organs of IgG4-RD patients. Transcription factors (TFs), including PRDM1/XBP1 and RUNX3, were upregulated in IgG4-RD, promoting the differentiation of plasmablasts and CTLs, respectively. Monocytes in IgG4-RD have stronger expression of genes related to cell adhesion and chemotaxis, which may give rise to profibrotic macrophages in lesions. The gene activation pattern in peripheral immune cells indicated activation of multiple interaction pathways between cell types, in part through chemokines or growth factors and their receptors. Specific upregulation of TFs and expansion of plasmablasts and CTLs may be involved in the pathogenesis of IgG4-RD, and each of these populations are candidate targets for therapeutic interventions in this disease.

Anti-melanoma differentiation-associated gene 5 (anti-MDA5) antibody-positive dermatomyositis (DM) complicated by rapidly progressive interstitial lung disease (RP-ILD) has a high incidence and poor prognosis. The objective of this study was to establish a model for the prediction and early diagnosis of anti-MDA5⁺ DM-associated RP-ILD based on clinical manifestations and imaging features. A total of 103 patients with anti-MDA5⁺ DM were included. The patients were randomly split into training and testing sets of 72 and 31 patients, respectively. After image analysis, we collected clinical, imaging, and radiomics features from each patient. Feature selection was performed first with the minimum redundancy and maximum relevance (mRMR) algorithm and then with the best subset selection method. The final remaining features comprised the radscore. Then, a clinical model and imaging model were constructed with the selected independent risk factors for the prediction of non-RP-ILD and RP-ILD. We also combined these models in different ways and compared their predictive abilities. A nomogram was also established. The predictive performances of the models were assessed based on receiver operating characteristic curves, calibration curves, discriminability, and clinical utility. : The analyses showed that 2 clinical factors, dyspnea (p = 0.000) and duration of illness in months (p = 0.001), and 3 radiomics features (p = 0.001, 0.044, 0.008, separately) were independent predictors of non-RP-ILD and RP-ILD. However, no imaging features were significantly different between the two groups. The radiomics model built with the 3 radiomics features performed worse than the clinical model and showed areas under the curve (AUCs) of 0.805 and 0.754 in the training and test sets, respectively. The clinical model demonstrated a good predictive ability for RP-ILD in MDA5⁺ DM patients, with an AUC, sensitivity, specificity, and accuracy of 0.954, 0.931, 0.837, and 0.847 in the training set and 0.890, 0.875, 0.800, and 0.774 in the testing set, respectively. The combination model built with clinical and radiomics features performed slightly better than the clinical model, with an AUC, sensitivity, specificity, and accuracy of 0.994, 0.966, 0.977, and 0.931 in the training set and 0.890, 0.812, 1.000, and 0.839 in the testing set, respectively. The calibration curve and decision curve analyses showed satisfactory consistency and clinical utility of the nomogram. Our results suggest that the combination model built with clinical and radiomics features could reliably predict the occurrence of RP-ILD in MDA5⁺ DM patients.

In this study, the available data from published randomized, controlled trials (RCTs) of the use of intestinal microecological regulators as adjuvant therapies to relieve the disease activity of rheumatoid arthritis (RA) are systematically compared. An English literature search was performed using PubMed, Embase, Scopus, Web of Science and the Cochrane Central Registry of Controlled Trials and supplemented by hand searching reference lists. Three independent reviewers screened and assessed the quality of the studies. Among the 2355 citations identified, 12 RCTs were included. All data were pooled using a mean difference (MD) with a 95% CI. The disease activity score (DAS) showed a significant improvement following microecological regulators treatment (MD (95% CI) of −1.01 (−1.81, −0.2)). A borderline significant reduction in the health assessment questionnaire (HAQ) scores was observed (MD (95% CI) of −0.11 (−0.21, −0.02)). We also confirmed the known effects of probiotics on inflammatory parameters such as the C-reactive protein (CRP) (MD −1.78 (95% CI −2.90, −0.66)) and L-1β (MD −7.26 (95% CI −13.03, −1.50)). No significant impact on visual analogue scale (VAS) of pain and erythrocyte sedimentation rate (ESR) reduction was observed. Intestinal microecological regulators supplementation could decrease RA activity with a significant effect on DAS28, HAQ and inflammatory cytokines. Nevertheless, these findings need further confirmation in large clinical studies with greater consideration of the confounding variables of age, disease duration, and individual medication regimens.

Idiopathic inflammatory myopathies (IIMs) are heterogeneous autoimmune diseases for which robust molecular classifiers are lacking. In this retrospective cross‐sectional study, we profiled immunoglobulin G (IgG) subclass‐specific N ‐glycosylation in IIMs and investigated their associations with clinical phenotypes and histopathological features. Using liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) with an electron‐transfer/higher energy collisional dissociation‐stepped collision energy higher energy collisional dissociation (EThcD‐sceHCD) fragmentation strategy, we analyzed plasma samples from 145 patients with IIMs and 52 age‐ and sex‐comparable healthy controls (HCs). Compared with HCs, patients with IIMs showed increased core fucosylation and significant alterations in 13 site‐specific IgG glycopeptides. Unsupervised clustering identified three glycosylation‐defined endotypes with muscle‐, cutaneous‐, and joint‐dominant phenotypes, each characterized by distinct glycoform patterns, clinical manifestations, and serological profiles. Specific IgG2 glycoforms were associated with markers of muscle injury and membrane attack complex (C5b‐9) deposition, suggesting a link between IgG glycosylation and complement‐mediated tissue damage. A seven‐glycopeptide multinomial logistic regression model and endotype‐specific nomograms were developed for exploratory cluster assignment, with moderate discrimination in the internal validation cohort (macro‐averaged area under the curve [macro‐AUC], 0.74). These findings identify IgG subclass‐specific N ‐glycosylation as a molecular layer underlying IIM heterogeneity beyond conventional clinical classification and provide a glycoproteomic framework for biomarker‐driven stratification, histopathological interpretation, and future mechanistic investigation.