Background: Dermatomyositis (DM) is a systemic autoimmune inflammatory disorder that affects primarily skin, muscle and lung, frequently associated with interstitial lung disease (ILD). The objective of this study is to investigate the association between serum cytokines and clinical severity in patients with DM-ILD. Methods: Serum samples of 30 healthy controls, 14 DM patients without ILD and 40 DM patients with ILD were collected. Serum S100A8/A9 levels were analyzed by enzyme-linked immunosorbent assay (ELISA) and levels of interleukins were measured by cytometric beads array (CBA). Then we performed multivariate logistic regression analysis to determine factors independently associated with ILD development. Results: Serum IL-4, IL-6 and S100A8/A9 levels were significantly higher in DM patients with ILD than those in healthy controls (p = 0.0013, 0.0017 and < 0.0001, respectively). Serum IL-10 level of patients was dramatically lower than that in controls (p = 0.0001).

Dermatomyositis and rheumatoid arthritis are inflammatory diseases that affect the skeletal muscles and joints, respectively. A common systemic complication of these diseases is interstitial lung disease (ILD), which leads to a poor prognosis and increased mortality. However, the mechanism for the initiation and development of ILD in patients with dermatomyositis is currently unknown. In the present study, we used 16S rRNA high-throughput sequencing to profile the bacterial community composition of bronchoalveolar lavage fluid of patients with dermatomyositis associated with ILD (DM-ILD; shortened to DM below), rheumatoid arthritis associated with ILD (RA-ILD; shortened to RA below) and healthy controls (N) aiming to understand the differences in their lung microbiota and to predict gene function. We found that there were more operational taxonomic units (OTUs) in the lung microbiota of both RA and DM compared to N, although there was no significant difference in the number of OTUs between RA and DM. Similarly, the diversity in alphaproteobacteria differed between RA and DM compared to N, but not between RA and DM. The lung microbiota of RA, DM and N was mainly comprised of five phyla: Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria and Fusobacteria, with 10 dominant genera. Despite the similarity in microbiota composition, we also identified 41 OTUs of lung microbiota that differed among RA, DM and N. Additionally, linear discriminant analysis effect size and linear discriminant analysis genus scores confirmed that 31 microbial biomarkers were clearly distinguished among RA, DM and N. The functional and metabolic alterations of the lung microbiota among RA, DM and N were predicted using PICRUST, and differentially abundant KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were identified. Research on the lung microbiota of patients with DM and RA may open new opportunities for developing biomarkers to identify high-risk patients.

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Background: Dermatomyositis (DM) is a systemic autoimmune inflammatory disorder that affects primarily skin, muscle and lung, frequently associated with interstitial lung disease (ILD). The objective of this study is to investigate the association between serum cytokines and clinical severity in patients with DM-ILD. Methods: Serum samples of 40 DM-ILD patients and 30 healthy controls were collected. Expressions of S100A8/A9 were analyzed by enzyme-linked immunosorbent assay (ELISA) and interleukins were analyzed by cytometric beads array (CBA). Results: Serum IL-4, IL-6 and S100A8/A9 were observably higher in DM-ILD than those in healthy controls ( p = 0.0013, 0.0017 and < 0.0001, respectively). Serum IL-10 level of patients was dramatically lower than that in controls ( p = 0.0001). IL-4 ( r = 0.1171, p = 0.0040), IL-6 ( r = 0.1174, p = 0.0040) and IL-10 ( r = -0.1829, p = 0.0003) were significantly correlated with S100A8/A9 in DM-ILD patients. S100A8/A9 was significantly correlated with high-resolution computed tomography (HRCT) ( r = 0.1642, p = 0.0157) and lung function (DLCO%: r = -0.2066, p = 0.0061, FVC%: r = -0.2156, p = 0.0050). Conclusions: Serum level of S100A8/A9 may be a valuable marker for assessing the clinical severity of DM-ILD patients. Serum IL-4, IL-6 and IL-10 levels were highly correlated with S100A8/A9, so these cytokines may play a synergistic effect on the progression of DM-ILD. Keywords : Dermatomyositis, Interstitial lung disease, S100A8/A9, Interleukin

Background: Transbronchial cryobiopsy (TBCB) has been widely used to diagnose interstitial lung disease (ILD). Existing reports on TBCB in ILD are mostly single-center prospective or retrospective studies but rarely multicenter prospective real-world studies. We explored the diagnostic efficiency and safety of TBCB in ILD in a real world setting. Methods: A prospective, multicenter, real-world study was conducted to analyze the data of patients with unclarified ILD who underwent TBCB in 20 hospitals in China from October 2018 to October 2019. The results of the pathological and multidisciplinary discussion (MDD) diagnosis and complications related to TBCB were then analyzed.Results: A total of 373 patients were enrolled in this study, including 194 males and 179 females, with an average age of 52.6±12.4 years. None of the patients had severe hemorrhaging, and the incidence of Original Article pneumothorax was 4.8%. The proportions of definitive, possible, and unclassified pathological diagnoses were 62.5%, 5.6%, and 31.9%, respectively. The overall diagnostic yield of MDD was 63.5%. There were 237 patients with a definitive diagnosis of MDD and 136 patients with an unclarified MDD diagnosis.The cooling gas pressure, freezing durations, number of specimens, maximum lengths of specimens, and specimen sizes varied significantly between the definitive and unclarified MDD diagnoses.Conclusions: In China, the application of TBCB in ILD is generally safe, and its diagnostic efficiency is acceptable. Using a 1.9-mm cryoprobe to collect five samples would achieve a better positive diagnostic rate for TBCB in ILD, without a significant increase in complication risk.