Abstract Rationale The pulmonary microbiome has been shown to influence host immune responses across various lung diseases, but its role in sarcoidosis remains unclear. Sarcoidosis is a systemic granulomatous disease with heterogeneous clinical manifestations, so that predicting its course remains challenging. Understanding how airway microbial composition relates to radiographic severity and clinical outcomes may provide insight into disease mechanisms and help identify potential prognostic biomarkers. Methods Next-generation sequencing of the V3-V4 region of the 16S rRNA gene was performed on bronchoalveolar lavage fluid (BALF) samples obtained from 171 patients with sarcoidosis, and 137 samples with sufficient sequencing reads after quality control were included in the final analysis. Associations between BALF microbiome composition and Scadding stages were evaluated to assess cross-sectional relationships with disease severity. Disease progression was defined as new organ involvement or clinical deterioration during follow-up. Comparative analyses and Cox proportional hazards modeling (adjusted for age, sex, and smoking) identified bacterial genera associated with progression. A multivariable model using six genera independently associated with outcomes was evaluated by the area under the ROC curve (AUC). Kaplan-Meier analysis assessed progression-free survival (PFS; time to first progression) by model-based risk groups. Results Alpha diversity decreased with higher Scadding stage (Jonckheere-Terpstra test, P = 0.03), indicating reduced microbial diversity in advanced disease. Corynebacterium abundance was higher in Scadding stage 2-3. In the progression group (n = 26), Selenomonas and Cutibacterium increased, whereas Fusobacterium and Haemophilus were enriched in the non-progression group. The mean follow-up was 5.1 ± 2.7 years. Adjusted Cox models showed Selenomonas (HR 3.80, 95% CI 1.65-8.79), Cutibacterium (HR 2.89, 1.19-6.98), and Veillonella (HR 5.61, 1.90-16.6) associated with progression, while Fusobacterium (HR 0.20, 0.05-0.88), Haemophilus (HR 0.29, 0.10-0.89), and Streptococcus (HR 0.41, 0.18-0.96) linked to stability. The six-genera model demonstrated a strong ability to distinguish patients who experienced disease progression from those who did not during follow-up (AUC = 0.83). When patients were stratified into three model-based risk groups (low, intermediate, and high), the progression-free survival curves diverged clearly, and no progression events were observed in the low-risk group. Conclusions BALF microbiome composition was associated with radiographic pattern and clinical outcomes in sarcoidosis. Reduced diversity and enrichment of specific genera correlated with disease behavior. A six-genera model provided robust discrimination for identifying patients at risk of deterioration, supporting BALF microbiome profiling as a tool for risk stratification in sarcoidosis. This abstract is funded by: None
Nishimura et al. (Fri,) studied this question.