Defining the role of the human intestinal microbiota in childhood asthma and atopic disease
Bibliographic record
Abstract
Asthma is a chronic inflammatory atopic disease of the airways affecting one in ten children in Westernized countries. The microflora hypothesis of allergic disease proposes the intestinal microbiota as a potential mechanistic link connecting environmental exposures to changes in the developing immune system. Further, animal model studies allude to an early life critical window, during which the immune system is most vulnerable to compositional and functional changes in the intestinal microbiota. We conducted an epidemiological assessment of early life environmental factors associated with atopy and wheezing at age 1 year and preschool-age asthma in children enrolled in the Canadian Healthy Infant Longitudinal Development (CHILD) Study (n = 2,695). Here, we identified early life microflora hypothesis related variables (e.g. pre- and post-natal antibiotic exposure, gestational age, and birth mode) as risk and protective factors for asthma and atopic disease. Informed by this epidemiological assessment, we used 16S ribosomal RNA sequencing and quantitative polymerase chain reaction to analyze the 3-month and 1-year fecal microbiota of one-year-old CHILD Study subjects positive or negative for atopy and wheezing (n = 319) and among this same cohort, those who were diagnosed with preschool-age asthma or non-atopic non-wheezing controls (n = 76). The fecal microbiota of atopic wheezing subjects compared to controls showed decreases in the abundances of four gut bacterial genera, Faecalibacterium, Lachnospira, Rothia, and Veillonella, combined with a reduction in fecal acetate at the 3-month time point only. Further, we found shifts in the relative abundances of two bacterial taxa in the 3-month fecal microbiota of preschool-age asthmatic children compared to controls; Lachnospira remained decreased among asthmatic children and Clostridium neonatale was increased in asthmatics. Quartile analysis at 3-months revealed a negative association between the ratio of these two bacteria (Lachnospira/Clostridium neonatale) and asthma risk. Altogether, this research highlights environmental factors that may be contributing to gut bacterial alterations in subjects with asthma or atopic disease. Additionally, these microbial alterations were no longer present by 1-year of age, suggesting the first 100 days of life as the critical window during which taxa-specific gut bacterial dysbiosis is associated with asthma and atopic disease in humans.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 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".