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Maternal Factors and Human Milk Oligosaccharide Composition in the CHILD Cohort

2017· article· en· W2970505621 on OpenAlexafffundabout
Bianca Robertson, Lars Bode, Atul Sharma, Allan B. Becker, Piush J. Mandhane, Padmaja Subbarao, Stuart E. Turvey, Diana L. Lefebvre, Malcolm R. Sears, Meghan B. Azad

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsMcMaster UniversityUniversity of British ColumbiaUniversity of AlbertaChildren's Hospital Research Institute of ManitobaUniversity of ManitobaManitoba HealthUniversity of TorontoGeorge & Fay Yee Centre for Healthcare Innovation
FundersCanadian Institutes of Health ResearchResearch Manitoba
KeywordsInterquartile rangeMedicineLactationBreast milkBreastfeedingParity (physics)CohortBreast feedingPregnancyAnimal sciencePhysiologyInternal medicineBiologyPediatricsBiochemistry

Abstract

fetched live from OpenAlex

Rationale Accumulating evidence suggests that human milk oligosaccharides (HMOs) impact infant health. However, which maternal factors influence HMO composition is largely unknown. Methods We analyzed 427 breast milk samples from the Canadian Healthy Infant Longitudinal Development (CHILD) study by rapid high‐throughput HPLC to determine associations between HMO composition and maternal age, ethnicity, parity, secretor blood group status, method of delivery and milk collection time postpartum. Milk samples were collected at 4 months postpartum (median 16 weeks, interquartile range 14–19 weeks). Spearman correlations, t‐tests and multivariable linear regression were used to evaluate relationships between HMO composition and maternal factors. Results Maternal secretor blood group status, lactation time postpartum, and parity were significantly and independently associated with total HMO concentration. Secretor mothers, expressing an active FUT2 gene, had increased levels of total HMOs when compared to non‐secretors (mean 15,908 ± 1,513 vs. 8.935 ± 2,796 nmol/mL, p<0.001). Non‐secretor status was more common among Asian vs. Caucasian mothers (40% vs. 26%, p=0.04). Total HMO level decreased with increasing time postpartum (adjusted b: −66 nmol/L per week; 95%CI −113, −19; p=0.006), although some individual HMOs increased, including: 3′‐fucosyllactose (3′FL, Spearman r = +0.15), 3′‐sialyllactose (3′SL, +0.18), lacto‐N‐fucopentaose‐III (LNFPIII, +0.12), and especially disialyllacto‐N‐tetraose (DSLNT, +0.28) (all p<0.02). Furthermore, total HMO levels increased with parity (adjusted b: +529 nmol/mL per child; 95%CI 173, 884; p<0.01). In contrast, maternal age and method of delivery were not significantly associated with total HMO level. Conclusion Our data suggest that both genetic and non‐genetic maternal factors influence HMO composition. Whether these associations have implications for infant health remains to be investigated. Support or Funding Information This study was funded by Research Manitoba and supported by the Canadian Institutes of Health Research and the Allergy, Genes and Environment Network of Centres of Excellence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.846

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.025
GPT teacher head0.307
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations3
Published2017
Admission routes3
Has abstractyes

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