What question did this study set out to answer?

The research aims to identify changes in the upper respiratory tract microbiome and metabolome in asthmatic children and their links to lung function.

February 20, 2026Open Access

Microbial and metabolomic profiling of the upper respiratory tract in children with asthma

Key Points

The research aims to identify changes in the upper respiratory tract microbiome and metabolome in asthmatic children and their links to lung function.
Observed children with asthma aged 6 years and above for microbiome and metabolome changes.
Collected throat swabs for analysis using 16S rDNA sequencing and liquid chromatography-mass spectrometry.
Compared results with age-matched healthy controls.
Significant differences in microbiome diversity were noted among control, chronic, and acute asthma groups.
Lower URT microbiota abundance correlated with reduced lung function metrics (FVC% and FEV1%).
L-carnitine identified as a potential biomarker for asthma with high sensitivity and specificity.

Abstract

Background This study aimed to investigate characteristic changes in the upper respiratory tract (URT) microbiome and metabolome in children with asthma and explore their associations with lung function. Methods Children with asthma aged 6 years and above admitted to the Children’s Hospital of Soochow University from December 2022 to December 2023 comprised the study group. Age-matched healthy children undergoing physical examinations in the Department of Child Health were recruited as controls. Throat swabs were collected for microbiome detection using 16S rDNA sequencing and metabolomics analysis using liquid chromatography-mass spectrometry (LC–MS). Results (1) Significant differences in alpha and beta diversity were observed among the control group (H), chronic persistent asthma group (CA), and acute exacerbation group (AA). In both CA and AA groups, FVC% predicted (FVC%/Pred) and FEV1% predicted (FEV1%/Pred) were negatively correlated with URT microbiota abundance. Actinobacillus abundance was positively correlated with FEV1%/Pred, FEV1/FVC, FEF25%/Pred, FEF50%/Pred, and FEF75%/Pred. (2) Metabolite differences between CA and AA groups were analyzed, and the top 5 differential metabolites were evaluated for their accuracy as asthma assessment biomarkers. L-carnitine showed an AUC 0.9, with a sensitivity of 85.7% and specificity of 85%. Other differential metabolites, including monoisobutyl phthalate, 4-hexyl-2,5-dimethyloxazole, and dibutyl phthalate, correlated with several lung function indices. The most relevant differential metabolic pathways included arginine biosynthesis, alanine-aspartate–glutamate metabolism, central carbon metabolism in cancer, and D-amino acid metabolism. Conclusion The URT microbiota in asthmatic children exhibits alterations in composition, structure, and diversity, with lower diversity in acute asthma compared to chronic persistent asthma. At the genus level, some microbiota ( Actinobacillus , Fusobacterium ) were correlated with FEV1%/Pred, FEV1/FVC, FEF25%/Pred, FEF50%/Pred, FEF75%/Pred. The differential metabolite L-carnitine may be a potential biomarker for asthma assessment.

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