Specific gut microbiota taxa exert definitive causal effects on childhood asthma, with two immune cell phenotypes serving as crucial intermediate mediators linking gut microbiota dysbiosis to childhood asthma development.
Key Findings
Results
Mendelian randomization analysis confirmed significant causal associations between seven gut microbiota taxa and childhood asthma, with four taxa showing robust causal effects.
Genetic data from 196 gut microbiota taxa were retrieved from the MiBioGen consortium
Bidirectional MR analysis was performed to verify causal associations
Reverse MR analysis was conducted to rule out reverse causality, and no reverse causal relationship was detected
Four of the seven taxa exhibited 'robust causal effects' as distinguished from the broader set of significant associations
Results
A total of 25 immune cell types showed statistically significant effects on childhood asthma risk.
Immune cell phenotype data came from 731 immune cell phenotypes retrieved from the MRC-IEU OpenGWAS database
MR analysis was used to establish causal links between immune cell phenotypes and childhood asthma
These 25 immune cell types were identified from the broader pool of 731 phenotypes analyzed
Results
The CD64 phenotype on CD14-CD16 immune cells mediated the causal effect of s_Paraprevotella_unclassified on childhood asthma.
This was identified as one of two key immune cell-mediated pathways via mediation analysis
CD14-CD16 cells are a monocyte/innate immune cell subset
This finding links a specific gut microbial taxon to childhood asthma through a defined immune cell intermediary
Results
The CD45 phenotype on HLA-DR T cells mediated the association of s_Bacteroides_thetaiotaomicron with childhood asthma.
This was the second of two key immune cell-mediated pathways identified by mediation analysis
HLA-DR T cells represent an activated T cell subset
Bacteroides thetaiotaomicron was also identified as enriched in the asthma group in clinical metagenomic sequencing
Results
Clinical metagenomic sequencing revealed distinct gut microbial signatures between children with asthma and healthy controls, with the asthma group characterized by enriched Bacteroides and healthy controls by predominant Akkermansia and Lachnospiraceae.
Fecal samples from childhood asthma patients and healthy controls were subjected to metagenomic sequencing for microbial species identification and functional annotation
LEfSe (Linear discriminant analysis effect size) was used to screen differential gut microbiota taxa
The clinical findings were described as 'consistent with the MR findings'
Alpha diversity analysis showed a trend of higher microbial species abundance in children with asthma without statistical significance
Results
KEGG functional analysis indicated that differential microbial pathways between asthma and control groups were primarily enriched in glucose metabolism, genetic information processing, and immune regulation.
KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis was used for microbial functional pathway annotation
This analysis was applied to metagenomic sequencing data from the clinical cohort
Three main functional categories distinguished the groups: glucose metabolism, genetic information processing, and immune regulation
Results
The abundance of ten virulence factors (mrkl, mrkJ, mrkA, mrkB, mrkC, mrkD, mrkF, mrkH, impF, and hcp/tssD) was significantly elevated in the childhood asthma group.
Virulence factor abundance was quantified using Python-based bioinformatics analysis with Virulence Factor Database (VFDB) annotation
Ten specific virulence factors were identified as significantly more abundant in children with asthma
The mrk gene cluster (mrkA through mrkH variants) represents type 3 fimbriae-related virulence factors
impF and hcp/tssD are associated with type VI secretion systems
What This Means
This research suggests that specific bacteria living in the gut play a causal role in the development of childhood asthma, and that this connection works partly through the immune system. Using a genetic analysis technique called Mendelian randomization — which uses naturally occurring genetic differences to test cause-and-effect relationships — the researchers found that seven types of gut bacteria causally influence childhood asthma risk. Critically, they identified two specific immune cell types that act as 'middlemen' in this process: one immune cell marker (CD64 on CD14-CD16 cells) links a bacterium called Paraprevotella to asthma, and another marker (CD45 on HLA-DR T cells) links Bacteroides thetaiotaomicron to asthma. These genetic findings were supported by stool sample analysis from real children with and without asthma, which found that asthmatic children had more Bacteroides bacteria while healthy children had more Akkermansia and Lachnospiraceae.
The clinical stool analysis also revealed that children with asthma carried significantly higher levels of microbial virulence factors — molecules that help bacteria cause harm — including a cluster of ten specific factors. Additionally, the functional capabilities of bacteria in asthmatic children's guts differed from healthy children in areas related to sugar metabolism, genetic processing, and immune regulation. While alpha diversity (the overall variety of species) trended higher in asthmatic children, this difference did not reach statistical significance.
This research suggests that the gut microbiome influences childhood asthma risk through specific immune pathways, offering potential targets for prevention or treatment strategies aimed at modifying gut bacteria. The identification of distinct microbial signatures — including harmful bacteria enriched in asthmatic children and potentially protective bacteria more common in healthy children — could inform future probiotic or dietary interventions, though further research would be needed to test whether changing these bacteria actually reduces asthma risk.
Shi R, Yang Z, Zhou X, Xu D, Xue W, An L, et al.. (2026). Immune Cell-Mediated Causal Link Between Gut Microbiota Traits and Childhood Asthma: Evidence From Mendelian Randomization and Metagenomic Sequencing.. The clinical respiratory journal. https://doi.org/10.1111/crj.70227