Allergy · 2026
Stool and Airway Microbiome Signatures Associated With Treatment Response to Dupilumab in Severe Asthma: Findings From the PRISM Study.
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Yie Ga-Eun, Kim Eunse, Pham Duong Duc, Lee Chae Eun, Song Heui, Kim Yoon-Keun, Kang Chil-Sung, Kwon Hyouk-Soo, Song Woo-Jung, Cho You Sook, Lee Sei Won, Ban Ga-Young, Lee Taehoon, Kim Min-Hye, Ahn Kyung-Min, Lee Sang Min, Bhavsar Pankaj K, Adcock Ian M, Chung Kian Fan, Won Sungho, Kim Tae-Bum
Аннотация
BACKGROUND: Severe asthma is characterized by persistent airway inflammation and heterogeneous responses to biologic therapies. Growing evidence implicates the gut-lung axis in asthma pathophysiology; however, few studies have concurrently characterized gut and airway microbiomes in relation to treatment response in severe asthma.
METHODS: We profiled microbiomes of stool bacteria (STB), stool-derived extracellular vesicles (STE), and exhaled breath condensate (EBC) from 48 patients with severe asthma receiving dupilumab. Microbial composition, alpha diversity, and predicted functional profiles were compared across sample types and longitudinally according to treatment response. Associations between microbial features and asthma-related clinical markers were also evaluated.
RESULTS: Distinct taxonomic and predicted functional signatures were identified across biological compartments. EBC samples were enriched in Proteobacteria, including Pseudomonas, and exhibited a higher predicted abundance of pathways related to two-component systems and bacterial secretion systems. EBC microbial diversity was positively associated with baseline sputum eosinophil levels (p = 0.018), whereas stool microbial richness demonstrated a time-dependent association with blood eosinophil counts after treatment (p for interaction = 0.023). Treatment responders exhibited lower abundances of Lachnospira (STB q = 0.046; STE q = 0.042) and Escherichia-Shigella (STE q = 0.038), and a higher relative abundance of the Oscillospiraceae NK4A214 group (STB q = 5.5 × 10-7, STE q = 1.4 × 10-8) in stool-derived profiles.
CONCLUSION: Gut and airway-derived microbiomes appear to play complementary roles in severe asthma. Stool-derived microbial features may reflect systemic inflammatory signals associated with treatment response, whereas airway-derived microbial profiles reflect local airway inflammation. Integrating multi-compartment microbiome data may improve the understanding of heterogeneity in biologic treatment response among patients with severe asthma.
METHODS: We profiled microbiomes of stool bacteria (STB), stool-derived extracellular vesicles (STE), and exhaled breath condensate (EBC) from 48 patients with severe asthma receiving dupilumab. Microbial composition, alpha diversity, and predicted functional profiles were compared across sample types and longitudinally according to treatment response. Associations between microbial features and asthma-related clinical markers were also evaluated.
RESULTS: Distinct taxonomic and predicted functional signatures were identified across biological compartments. EBC samples were enriched in Proteobacteria, including Pseudomonas, and exhibited a higher predicted abundance of pathways related to two-component systems and bacterial secretion systems. EBC microbial diversity was positively associated with baseline sputum eosinophil levels (p = 0.018), whereas stool microbial richness demonstrated a time-dependent association with blood eosinophil counts after treatment (p for interaction = 0.023). Treatment responders exhibited lower abundances of Lachnospira (STB q = 0.046; STE q = 0.042) and Escherichia-Shigella (STE q = 0.038), and a higher relative abundance of the Oscillospiraceae NK4A214 group (STB q = 5.5 × 10-7, STE q = 1.4 × 10-8) in stool-derived profiles.
CONCLUSION: Gut and airway-derived microbiomes appear to play complementary roles in severe asthma. Stool-derived microbial features may reflect systemic inflammatory signals associated with treatment response, whereas airway-derived microbial profiles reflect local airway inflammation. Integrating multi-compartment microbiome data may improve the understanding of heterogeneity in biologic treatment response among patients with severe asthma.