Evidence map›Paper›PMID 39242646›Full record

ArticleScientific reports2024

Untargeted metabolomic analysis of human milk from healthy mothers reveals drivers of metabolite variability.

Zachary C Holmes, Katariina Koivusaari, Claire E O'Brien, Katherine V Richeson, Leila I Strickland

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zachary C Holmes *BIOMILQ, Inc., Research Triangle Park, NC, USA.
Katariina Koivusaari *BIOMILQ, Inc., Research Triangle Park, NC, USA.
Claire E O'BrienBIOMILQ, Inc., Research Triangle Park, NC, USA.
Katherine V RichesonBIOMILQ, Inc., Research Triangle Park, NC, USA.
Leila I StricklandBIOMILQ, Inc., Research Triangle Park, NC, USA. leila.strickland@biomilq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the human milk metabolome can help inform infant nutrition and health. Untargeted metabolomics was used to study breast milk from 31 healthy participants to assess the shared metabolites in milk from participants with various backgrounds and understand how different demographic, health, and environmental factors impact the milk metabolome. Breast milk samples were analyzed by four separate UPLC-MS/MS methods. Metabolite Set Enrichment Analysis was used to study the most and least variable metabolites. The associations between participant factors and the metabolome were assessed with redundancy analyses. Among all 31 participants and between each untargeted UPLC-MS/MS method, 731 metabolites were detected, of which 389 were shared among all participants. Of the shared metabolites, lactose was the least and lactobionate the most variable metabolite. In the biological super pathway analysis, xenobiotics were the most variable metabolites. Infant age, maternal age, number of live births, and pre-pregnancy BMI were associated with the milk metabolome. In conclusion, the most variable metabolites originate from environmental exposures while the well-conserved core metabolites are linked to cell metabolism or are crucial for infant nutrition and osmoregulation. Understanding the variability of the breast milk metabolome can help identify components that are crucial for infant nutrition, growth, and development.

Indexed as

MetabolomeMetabolomicsMilk, HumanAdultFemaleHumansInfantLactoseMothersTandem Mass SpectrometryYoung AdultLactose

Identifiers

PMID39242646
PMCPMC11379717

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.