Metagenomic next-generation sequencing reveals airway microbial dysbiosis and functional alterations in Legionella pneumophila pneumonia.
Legionella pneumonia (LP), primarily caused by Legionella pneumophila, is a clinically important subtype of community-acquired pneumonia (CAP) associated with substantial morbidity and mortality. However, the microbial characteristics and functional profiles of LP remain insufficiently understood.
In this study, metagenomic next-generation sequencing (mNGS) was used to compare airway microbial communities between patients with LP and those with non-Legionella CAP.
A total of 60 patients were included, comprising 23 patients with LP patients and 37 patients with non-Legionella CAP patients. Airway microbial diversity and composition differed between groups, although the between-group effect size was modest and residual confounding could not be excluded. The LP group showed higher relative abundance of Legionella pneumophila and selected opportunistic species, whereas several oral commensal-associated species were relatively enriched in non-Legionella CAP. In the pooled 60-patient cohort, selected microbial species were associated with inflammatory and clinical severity markers; these associations were not disease-specific and do not imply causality. Inferred functional profiles also differed between groups. Exploratory machine-learning models showed high internal discriminatory performance, with XGBoost yielding the highest mean AUC, but the small cohort and lack of external validation limit conclusions regarding diagnostic utility.
In this small retrospective cohort, LP was associated with differences in airway microbial composition and inferred functional potential compared with a heterogeneous non-Legionella CAP group. Because the study was observational, the groups differed in important clinical characteristics, and the pooled association analyses were not disease-specific, the findings should be considered exploratory and hypothesis-generating. The reproducibility and diagnostic value of microbiota-derived features require confirmation in larger, prospectively collected, independent cohorts.
In this study, metagenomic next-generation sequencing (mNGS) was used to compare airway microbial communities between patients with LP and those with non-Legionella CAP.
A total of 60 patients were included, comprising 23 patients with LP patients and 37 patients with non-Legionella CAP patients. Airway microbial diversity and composition differed between groups, although the between-group effect size was modest and residual confounding could not be excluded. The LP group showed higher relative abundance of Legionella pneumophila and selected opportunistic species, whereas several oral commensal-associated species were relatively enriched in non-Legionella CAP. In the pooled 60-patient cohort, selected microbial species were associated with inflammatory and clinical severity markers; these associations were not disease-specific and do not imply causality. Inferred functional profiles also differed between groups. Exploratory machine-learning models showed high internal discriminatory performance, with XGBoost yielding the highest mean AUC, but the small cohort and lack of external validation limit conclusions regarding diagnostic utility.
In this small retrospective cohort, LP was associated with differences in airway microbial composition and inferred functional potential compared with a heterogeneous non-Legionella CAP group. Because the study was observational, the groups differed in important clinical characteristics, and the pooled association analyses were not disease-specific, the findings should be considered exploratory and hypothesis-generating. The reproducibility and diagnostic value of microbiota-derived features require confirmation in larger, prospectively collected, independent cohorts.
Authors
Zhang Zhang, Zou Zou, Wu Wu, Xu Xu, Ren Ren, Liu Liu, Sun Sun, Liu Liu, Yu Yu, Yu Yu, Ding Ding
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