A microbiome–metabolome signature associated with pediatric severe asthma
Abstract
Background Severe asthma is a heterogeneous condition encompassing multiple phenotypes. Understanding lung-specific mechanisms in children with severe asthma may enable the development of more precise therapeutic strategies. We previously reported that immune components in bronchoalveolar lavages (BALs) differentiate children with severe asthma from non-asthmatic disease-controls and, frequent from non-frequent exacerbators, among children with severe asthma. Objective To identify a local signature of severe asthma using complementary multi-omics analyses of BALs. A secondary objective was to evaluate whether bacterial taxa and metabolites discriminate severe asthma subtypes associated with distinct phenotypes or endotypes. Methods BAL microbiome and metabolome were investigated in 20 children with severe asthma and 10 non-asthmatic children using 16S rRNA gene amplicon sequencing and liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS), respectively. Data were analysed separately and through integrative multi-omics approaches. Results Compared with controls, BALs from children with severe asthma showed increased alpha-diversity, higher relative abundances of Actinobacteriota , Streptococcus , Moraxella , Corynebacterium , Tropheryma , and Treponema , and an altered polyamine pathway characterized by reduced arginine and increased spermine and spermidine levels. Integrated analyses revealed significant associations between Streptococcus and both spermine and spermidine. Independently, each dataset discriminated severe asthma phenotypes, notably exacerbation frequency and co-occurring atopic dermatitis. Unsupervised clustering of microbiome profiles identified four distinct clusters that may reflect severe asthma endotypes. Conclusions This study identifies a distinct airway microbiome–metabolome signature associated with pediatric severe asthma. Enrichment of specific bacterial taxa, particularly Streptococcus , together with altered polyamine metabolic pathway, highlights microbial–metabolic interactions potentially involved in disease pathophysiology. The ability of microbiome and metabolome profiles to independently and jointly discriminate clinical phenotypes underscores the relevance of multi-omics approaches for diagnosis and follow-up of severe asthma. Our findings support the importance of airway-level profiling to improve mechanistic understanding of severe asthma and inform on future targeted therapeutic strategies.
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BibTeX
@article{briard2026microbiomemetabolome,
title = {{A microbiome–metabolome signature associated with pediatric severe asthma}},
author = {Mélanie Briard and Blanche Guillon and Eric Venot and Marta Grauso and Christelle Hennequet-Antier and Aurélia Bruneau and François Fenaille and Florence Castelli and Muriel Thomas and Guillaume Lezmi and Maria Leite-De-Moraes and Karine Adel-Patient and Vinciane Saint-Criq},
journal = {PLoS ONE},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0358560},
url = {https://hal.inrae.fr/hal-05759588v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A microbiome–metabolome signature associated with pediatric severe asthma
AU - Mélanie Briard
AU - Blanche Guillon
AU - Eric Venot
AU - Marta Grauso
AU - Christelle Hennequet-Antier
AU - Aurélia Bruneau
AU - François Fenaille
AU - Florence Castelli
AU - Muriel Thomas
AU - Guillaume Lezmi
AU - Maria Leite-De-Moraes
AU - Karine Adel-Patient
AU - Vinciane Saint-Criq
PY - 2026
DA - 2026/09/18
JO - PLoS ONE
DO - 10.1371/journal.pone.0358560
UR - https://hal.inrae.fr/hal-05759588v1
AB - Background Severe asthma is a heterogeneous condition encompassing multiple phenotypes. Understanding lung-specific mechanisms in children with severe asthma may enable the development of more precise therapeutic strategies. We previously reported that immune components in bronchoalveolar lavages (BALs) differentiate children with severe asthma from non-asthmatic disease-controls and, frequent from non-frequent exacerbators, among children with severe asthma. Objective To identify a local signature of severe asthma using complementary multi-omics analyses of BALs. A secondary objective was to evaluate whether bacterial taxa and metabolites discriminate severe asthma subtypes associated with distinct phenotypes or endotypes. Methods BAL microbiome and metabolome were investigated in 20 children with severe asthma and 10 non-asthmatic children using 16S rRNA gene amplicon sequencing and liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS), respectively. Data were analysed separately and through integrative multi-omics approaches. Results Compared with controls, BALs from children with severe asthma showed increased alpha-diversity, higher relative abundances of Actinobacteriota , Streptococcus , Moraxella , Corynebacterium , Tropheryma , and Treponema , and an altered polyamine pathway characterized by reduced arginine and increased spermine and spermidine levels. Integrated analyses revealed significant associations between Streptococcus and both spermine and spermidine. Independently, each dataset discriminated severe asthma phenotypes, notably exacerbation frequency and co-occurring atopic dermatitis. Unsupervised clustering of microbiome profiles identified four distinct clusters that may reflect severe asthma endotypes. Conclusions This study identifies a distinct airway microbiome–metabolome signature associated with pediatric severe asthma. Enrichment of specific bacterial taxa, particularly Streptococcus , together with altered polyamine metabolic pathway, highlights microbial–metabolic interactions potentially involved in disease pathophysiology. The ability of microbiome and metabolome profiles to independently and jointly discriminate clinical phenotypes underscores the relevance of multi-omics approaches for diagnosis and follow-up of severe asthma. Our findings support the importance of airway-level profiling to improve mechanistic understanding of severe asthma and inform on future targeted therapeutic strategies.
SN - 1932-6203
SN - 1932-6203
ER -