Evidence map›Paper›PMID 38249448›Full record

ArticleFrontiers in microbiology2023

Influence of perinatal and childhood exposure to tobacco and mercury in children's gut microbiota.

Sonia Pérez-Castro, Giuseppe D'Auria, Maria Llambrich, Sílvia Fernández-Barrés, Maria-Jose Lopez-Espinosa, Sabrina Llop, Benito Regueiro, Mariona Bustamante, M Pilar Francino, Martine Vrijheid and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  4. 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

11 authors at 5 institutions in 1 country.

Sonia Pérez-CastroMicrobiology Department, Complexo Hospitalario Universitario de Vigo (CHUVI), Vigo, Spain.
Giuseppe D'AuriaSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Maria LlambrichISGlobal, Barcelona, Spain.
Sílvia Fernández-BarrésSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Maria-Jose Lopez-EspinosaSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Sabrina LlopSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Benito RegueiroMicrobiology and Infectology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Vigo, Spain.
Mariona BustamanteSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
M Pilar FrancinoSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Martine VrijheidSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Léa MaitreSpanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública · ESBarcelona Institute for Global Health · ESGalicia Sur Biomedical Foundation · ESFundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana · ESPompeu Fabra University · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Early life determinants of the development of gut microbiome composition in infants have been widely investigated; however, if early life pollutant exposures, such as tobacco or mercury, have a persistent influence on the gut microbial community, its stabilization at later childhood remains largely unknown. Objective: In this exposome-wide study, we aimed at identifying the contribution of exposure to tobacco and mercury from the prenatal period to childhood, to individual differences in the fecal microbiome composition of 7-year-old children, considering co-exposure to a width of established lifestyle and clinical determinants. Methods: Gut microbiome was studied by 16S rRNA amplicon sequencing in 151 children at the genus level. Exposure to tobacco was quantified during pregnancy through questionnaire (active tobacco consumption, second-hand smoking -SHS) and biomonitoring (urinary cotinine) at 4 years (urinary cotinine, SHS) and 7 years (SHS). Exposure to mercury was quantified during pregnancy (cord blood) and at 4 years (hair). Forty nine other potential environmental determinants (12 at pregnancy/birth/infancy, 15 at 4 years and 22 at 7 years, such as diet, demographics, quality of living/social environment, and clinical records) were registered. We used multiple models to determine microbiome associations with pollutants including multi-determinant multivariate analysis of variance and linear correlations (wUnifrac, Bray-Curtis and Aitchison ß-diversity distances), single-pollutant permutational multivariate analysis of variance adjusting for co-variates (Aitchison), and multivariable association model with single taxa (MaAsLin2; genus). Sensitivity analysis was performed including genetic data in a subset of 107 children. Results: Active smoking in pregnancy was systematically associated with microbiome composition and ß-diversity ( Discussion: Our findings suggest a long-term sustainable effect of prenatal tobacco exposure on the children's gut microbiota. This effect was not found for mercury exposure or tobacco exposure during childhood. Assessing the role of these exposures on the children's microbiota, considering multiple environmental factors, should be further investigated.

Indexed as

16S rRNAbirth cohortchildrendietgut microbiotamercurysecond-hand smokesmoking during pregnancy

Identifiers

PMID38249448
PMCPMC10799562
OpenAlexW4390611540

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.