Severe asthma in children is a heterogeneous condition with multiple phenotypes and endotypes. The authors aimed to identify a local airway signature of pediatric severe asthma by applying complementary multi-omics analyses to bronchoalveolar lavage (BAL) fluid. The rationale was that lung-specific microbial and metabolic features might better distinguish severe asthma subtypes and inform more precise therapeutic approaches.
BAL samples were analyzed from two groups: 20 children with severe asthma and 10 non-asthmatic disease-control children. The report describes a paired approach using microbial community profiling and untargeted metabolomics on the same BAL specimens. Further demographic, treatment, or sampling details beyond group sizes were not reported in the abstract.
Microbial community composition in BAL was assessed by 16S rRNA gene amplicon sequencing. Compared with non-asthmatic controls, BALs from children with severe asthma exhibited increased alpha-diversity and shifts in taxonomic composition. Specifically, relative abundances were higher for Actinobacteriota and several genera, including Streptococcus, Moraxella, Corynebacterium, Tropheryma, and Treponema. These taxonomic enrichments characterize an airway microbiome pattern associated with pediatric severe asthma in this cohort.
Metabolomic profiling of BAL fluid was performed using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). The metabolome of severe asthma patients showed perturbations in the polyamine pathway: arginine levels were reported as reduced, while downstream polyamines spermine and spermidine were increased relative to controls. The altered polyamine signature indicates a metabolic shift in the airway environment of children with severe asthma.
The study integrated microbial and metabolomic datasets to identify associations between taxa and metabolites. Integrated analyses revealed significant relationships between the abundance of Streptococcus and elevated levels of both spermine and spermidine. These findings suggest potential microbial–metabolic interactions in the airway that may be relevant to disease pathophysiology.
Independently, each dataset (microbiome alone and metabolome alone) was able to discriminate clinical features within the severe asthma group. Notably, both the microbial and the metabolic profiles distinguished patients by exacerbation frequency and by the presence of co-occurring atopic dermatitis. This indicates that either domain of omics data can capture clinically meaningful heterogeneity among children with severe asthma.
Unsupervised clustering of the microbiome profiles identified four distinct clusters among the study participants. The authors propose that these clusters may correspond to different severe asthma endotypes. The abstract does not provide the detailed characteristics of each cluster or how they map to clinical or immunological features beyond the suggestion that they reflect endotypic diversity.
This study identifies a distinct airway microbiome–metabolome signature associated with pediatric severe asthma. Enrichment of specific bacterial taxa—particularly Streptococcus—combined with alterations in the polyamine metabolic pathway (reduced arginine, increased spermine and spermidine) points to microbial–metabolic interactions that may participate in disease mechanisms. The capacity of microbiome and metabolome profiles to independently and jointly discriminate clinical phenotypes supports the relevance of multi-omics approaches for diagnosis, endotyping, and potentially for monitoring disease course in pediatric severe asthma.
The abstract provides core findings and the principal methods (16S rRNA sequencing and LC-HRMS) but does not report several details in the source text available here, including participant demographics, medication or treatment status, timing and method of BAL collection, statistical effect sizes, correction for multiple testing, or external validation. Any such methodological or quantitative specifics were not reported in the abstract and therefore are not included here.
Overall, the reported results underscore a linked microbial and metabolic airway signature in pediatric severe asthma and highlight candidate taxa and metabolites—most notably Streptococcus and the polyamine pathway—that warrant further mechanistic and clinical investigation.