Evidence map›Paper›PMID 32315306›Full record

ArticlePloS one2020

Novel approach to visualize the inter-dependencies between maternal sensitization, breast milk immune components and human milk oligosaccharides in the LIFE Child cohort.

Loris Michel, Maya Shevlyakova, Ellen Ní Cléirigh, Erik Eckhardt, Sebastien Holvoet, Sophie Nutten, Norbert Sprenger, Antje Körner, Mandy Vogel, Chiara Nembrini and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 38% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

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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

12 authors at 2 institutions in 2 countries.

Loris MichelNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Maya ShevlyakovaNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Ellen Ní CléirighNestlé Development Centre Nutrition, Askeaton, Ireland.
Erik EckhardtNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Sebastien HolvoetNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Sophie NuttenNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Norbert SprengerNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Antje KörnerFaculty of Medicine, LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.
Mandy VogelFaculty of Medicine, LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.
Chiara NembriniNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Wieland KiessFaculty of Medicine, LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.
Carine BlanchardNestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.ORCID 0000-0002-3377-290X
Nestlé (Switzerland) · CHLeipzig University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous studies have shown that specific components of breast milk, considered separately, are associated with disease status in the mother or the child using univariate analyses. However, very few studies have considered multivariate analysis approaches to evaluate the relationship between multiple breast milk components simultaneously.

aimHere we aimed at visualizing breast milk component complex interactions in the context of the allergy status of the mother or the child.

methodsMilk samples were collected from lactating mothers participating in the Leipziger Forschungszentrum für Zivilisationskrankheiten (LIFE) Child cohort in Leipzig, Germany. A total of 156 breast milk samples, collected at 3 months after birth from mother/infant pairs, were analyzed for 51 breast milk components. Correlation, principal component analysis (PCA) and graphical discovery analysis were used.

resultCorrelations ranging from 0.40 to 0.96 were observed between breast milk fatty acid and breast milk phospholipids levels and correlations ranging from 0 to 0.76 between specific human milk oligosaccharides (HMO) were observed. No separation of the data based on the risk of allergy in the infants was identified using PCA. When graphical discovery analysis was used, dependencies between maternal plasma immunoglobulin E (IgE) level and the breast milk immune marker transforming growth factor-beta 2 (TGF-ß2), between TGF-ß2, breast milk immunoglobulin A (IgA) and TGF-ß1 as well as between breast milk total protein and birth weight were observed. Graphical discovery analysis also exemplifies a possible competition for the fucosyl group between 2'FL, LNFP-I and 3'FL in the HMO group. Additionally, dependencies between immune component IgA and specific HMO (6'SL and blood group A antigen tetraose type 5 or PI-HMO) were identified.

conclusionGraphical discovery analysis applied to complex matrices such as breast milk composition can aid in understanding the complexity of interactions between breast milk components and possible relations to health parameters in the mother or the infant. This approach can lead to novel discoveries in the context of health and diseases such as allergy. Our study thus represents the first attempt to visualize the complexity and the inter-dependency of breast milk components.

Indexed as

AdultBreast FeedingChildCohort StudiesDermatitis, Allergic ContactFemaleHumansImmunoglobulin AImmunoglobulin EInfantLactationMethacrylatesMilk, HumanMilk HypersensitivityOligosaccharidesPrincipal Component AnalysisImmunoglobulin AImmunoglobulin EMethacrylatesOligosaccharidesTransforming Growth Factors

Identifiers

PMID32315306
PMCPMC7173766
OpenAlexW3017028598

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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.