ArticleAnnals of clinical microbiology and antimicrobials2026
Metagenomic-based quantification of Pseudomonas aeruginosa burden links microbiome collapse to mortality in severe community-acquired pneumonia.
Article in Annals of clinical microbiology and antimicrobials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSevere community-acquired pneumonia (sCAP) remains a major cause of mortality in critically ill patients, Pseudomonas aeruginosa (P. aeruginosa) is a frequent pathogen associated with poor prognosis in this population. While metagenomic next-generation sequencing (mNGS) is widely used for pathogen detection, its value in quantifying pathogen abundance and linking it to lung microbiome alterations remains unclear.
objectivesThis study investigated the association between P. aeruginosa abundance quantified by mNGS and lung microbiome alterations and clinical outcomes in sCAP patients.
methodsThis multicenter retrospective study included 130 patients with sCAP caused by P. aeruginosa from five hospitals (September 2021-June 2025). Patients were stratified into low, medium, and high abundance groups according to mNGS-derived reads per ten million (RPTM) values of P. aeruginosa. Lung microbiome diversity and community structure were analyzed, and differences between groups were assessed using appropriate statistical methods. The association between P. aeruginosa abundance and clinical outcomes was evaluated using correlation analysis, sankey diagram, receiver operating characteristic curve, grey zone analysis and logistic regression.
resultsA total of 130 patients with sCAP due to P. aeruginosa were stratified into low, medium, and high abundance groups based on mNGS-derived RPTM value. Microbial diversity decreased progressively with increasing abundance, and community structures differed significantly among groups (all P < 0.05). P. aeruginosa became increasingly dominant, accounting for up to 95.99% of the microbiota in the high abundance group. Higher P. aeruginosa abundance was associated with increased disease severity, including longer mechanical ventilation, prolonged hospital stay, and higher 28-day mortality. Sankey diagram showed a progressive decline in treatment effectiveness and an increase in mortality with increasing P. aeruginosa abundance. P. aeruginosa_RPTM showed moderate predictive value for mortality (AUC = 0.761, Sens = 69.40%, Spec = 75.30%, cutoff: 41122, grey zone: 2287-220339) and remained independently associated with 28-day mortality in multivariable analysis [2.219 (1.509 to 3.262), P < 0.001].
conclusionIn patients with sCAP, higher P. aeruginosa_RPTM measured by mNGS was associated with reduced lung microbiome diversity and unfavorable clinical outcomes. RPTM-based risk stratification may help identify patients at increased risk of poor prognosis.
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