期刊
FEBS OPEN BIO
卷 12, 期 1, 页码 258-269出版社
WILEY
DOI: 10.1002/2211-5463.13334
关键词
bronchoalveolar lavage fluid; dermatomyositis; interstitial lung disease; microbiome; rheumatoid arthritis
资金
- Role of Airway Flora Imbalance in Patients with Bronchiectasis and the Effect of Azithromycin Intervention [2015QDMS01]
- Shanghai Health and Family Planning Commission Clinical Research Project [20184Y0189]
- study on the Diagnosis and Treatment strategy of Interstitial Lung Disease Associated with Connective Tissue in Diagnostic Bronchoscopy [PYI-17-009]
Dermatomyositis and rheumatoid arthritis are inflammatory diseases that commonly lead to interstitial lung disease (ILD). Analysis of the lung microbiota composition in patients with these conditions revealed differences in diversity compared to healthy controls, with several unique microbial biomarkers distinguishing between the diseases. Predicted functional and metabolic alterations in the lung microbiota between rheumatoid arthritis, dermatomyositis, and healthy controls may lead to the development of biomarkers for identifying high-risk patients.
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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