Bacterial communities co-develop with respiratory immunity early in life, linking dysbiosis to systemic monocyte signature and wheezing
Bibliographic record
Abstract
Early microbial colonization influences respiratory disease risk, yet mechanisms remain unclear. In a prospective birth cohort of 256 infants, we profiled bacterial, fungal, and viral communities in the upper airway and assessed local immune gene expression longitudinally and systemic gene expression at 1 year. Bacterial populations, not fungal or viral, correlated most strongly with immune development during the first 3 months, coinciding with composition shifts and immune-related gene expression changes, including interferon and adaptive immunity pathways. In contrast, the mycobiome and resident viruses showed no significant coevolution with host immunity. By 1 year, infants who previously wheezed displayed an upper airway microbiota enriched in Haemophilus influenzae and Moraxella , accompanied by a distinct local and systemic immune gene signature featuring elevated classical monocyte-related genes. These findings reveal a specific link between early-life bacterial dysbiosis, monocyte-related immunity, and wheezing onset, suggesting potential targets for early intervention in respiratory disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".