Examining the relationship between maternal body size, gestational glucose tolerance status, mode of delivery and ethnicity on human milk microbiota at three months post-partum
Bibliographic record
Abstract
Abstract Background Few studies have examined how maternal body mass index (BMI), mode of delivery and ethnicity affect the microbial composition of human milk and none have examined associations with maternal metabolic status. Given the high prevalence of maternal adiposity and impaired glucose metabolism, we systematically investigated the associations between these maternal factors in women ≥20 years and milk microbial composition and predicted functionality by V4-16S ribosomal RNA gene sequencing (NCT01405547; https://clinicaltrials.gov/ct2/show/NCT01405547 ). Demographic data, weight, height, and a 3-h oral glucose tolerance test were gathered at 30 (95% CI: 25–33) weeks gestation, and milk samples were collected at 3 months post-partum ( n = 113). Results Multivariable linear regression analyses demonstrated no significant associations between maternal characteristics (maternal BMI [pre-pregnancy, 3 months post-partum], glucose tolerance, mode of delivery and ethnicity) and milk microbiota alpha-diversity; however, pre-pregnancy BMI was associated with human milk microbiota beta-diversity (Bray-Curtis R 2 = 0.037). Women with a pre-pregnancy BMI > 30 kg/m 2 (obese) had a greater incidence of Bacteroidetes (incidence rate ratio [IRR]: 3.70 [95% CI: 1.61–8.48]) and a reduced incidence of Proteobacteria (0.62 [0.43–0.90]) in their milk, compared to women with an overweight BMI (25.0–29.9 kg/m 2 ) as assessed by multivariable Poisson regression. An increased incidence of Gemella was observed among mothers with gestational diabetes who had an overweight BMI versus healthy range BMI (5.96 [1.85–19.21]). An increased incidence of Gemella was also observed among mothers with impaired glucose tolerance with an obese BMI versus mothers with a healthy range BMI (4.04 [1.63–10.01]). An increased incidence of Brevundimonas (16.70 [5.99–46.57]) was found in the milk of women who underwent an unscheduled C-section versus vaginal delivery. Lastly, functional gene inference demonstrated that pre-pregnancy obesity was associated with an increased abundance of genes encoding for the biosynthesis of secondary metabolites pathway in milk (coefficient = 0.0024, P FDR < 0.1). Conclusions Human milk has a diverse microbiota of which its diversity and differential abundance appear associated with maternal BMI, glucose tolerance status, mode of delivery, and ethnicity. Further research is warranted to determine whether this variability in the milk microbiota impacts colonization of the infant gut.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".