The maternal prenatal and offspring <scp>early‐life</scp> gut microbiome of childhood asthma phenotypes
Bibliographic record
Abstract
BACKGROUND: The infant fecal microbiome is known to impact subsequent asthma risk, but the environmental exposures impacting this association, the role of the maternal microbiome, and how the microbiome impacts different childhood asthma phenotypes are unknown. METHODS: Our objective was to identify associations between features of the prenatal and early-life fecal microbiomes and child asthma phenotypes. We analyzed fecal 16 s rRNA microbiome profiling and fecal metabolomic profiling from stool samples collected from mothers during the third trimester of pregnancy (n = 120) and offspring at ages 3-6 months (n = 265), 1 (n = 436) and 3 years (n = 506) in a total of 657 mother-child pairs participating in the Vitamin D Antenatal Asthma Reduction Trial. We used clinical data from birth to age 6 years to characterize subjects with asthma as having early, transient or active asthma phenotypes. In addition to identifying specific genera that were robustly associated with asthma phenotypes in multiple covariate-adjusted models, we clustered subjects by their longitudinal microbiome composition and sought associations between fecal metabolites and relevant microbiome and clinical features. RESULTS: Seven maternal and two infant fecal microbial taxa were robustly associated with at least one asthma phenotype, and a longitudinal gut microenvironment profile was associated with early asthma (Fisher exact test p = .03). Though mode of delivery was not directly associated with asthma, we found substantial evidence for a pathway whereby cesarean section reduces fecal Bacteroides and microbial sphingolipids, increasing susceptibility to early asthma. CONCLUSION: Overall, our results suggest that the early-life, including prenatal, fecal microbiome modifies risk of asthma, especially asthma with onset by age 3 years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".