Evidence map›Paper›PMID 31299210›Full record

ArticleReproductive toxicology (Elmsford, N.Y.)2020

Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's.

Shuzhao Li, Piera Cirillo, Xin Hu, ViLinh Tran, Nickilou Krigbaum, Shaojun Yu, Dean P Jones, Barbara Cohn

Abstract read
In one paragraph

Article in Reproductive toxicology (Elmsford, N.Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Review
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  12. Endocrine-disrupting compounds and metabolomic reprogramming in breast cancer.Journal of biochemical and molecular toxicology · 2023
    Review
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  17. What is next for occupational cancer epidemiology?Scandinavian journal of work, environment & health · 2022
    Article
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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

8 authors.

Shuzhao LiDepartment of Medicine, School of Medicine, Emory University, Atlanta, GA, 30303, USA. Electronic address: sli49@emory.edu.
Piera CirilloThe Center for Research on Women and Children's Health, Child Health and Development Studies, Public Health Institute, 1683 Shattuck Avenue, Suite B, Berkeley, CA, 94709, USA.
Xin HuDepartment of Medicine, School of Medicine, Emory University, Atlanta, GA, 30303, USA.
ViLinh TranDepartment of Medicine, School of Medicine, Emory University, Atlanta, GA, 30303, USA.
Nickilou KrigbaumThe Center for Research on Women and Children's Health, Child Health and Development Studies, Public Health Institute, 1683 Shattuck Avenue, Suite B, Berkeley, CA, 94709, USA.
Shaojun YuDepartment of Medicine, School of Medicine, Emory University, Atlanta, GA, 30303, USA.
Dean P JonesDepartment of Medicine, School of Medicine, Emory University, Atlanta, GA, 30303, USA.
Barbara CohnThe Center for Research on Women and Children's Health, Child Health and Development Studies, Public Health Institute, 1683 Shattuck Avenue, Suite B, Berkeley, CA, 94709, USA. Electronic address: bcohn@chdstudies.org.

Funding

Pilot Project ProgramP30ES019776 · NIEHS · EMORY UNIVERSITY · PI William Michael Caudle · 2013 to 2026
$22.6M
U2C Experimental CoreU2CES030163 · NIEHS · EMORY UNIVERSITY · PI MORGAN, EDWARD THOMAS · 2018 to 2021
$3.6M
Mummichog 3, aligning mass spectrometry data to biological networks - Neutral LossU01CA235493 · NCI · JACKSON LABORATORY · PI LI, SHUZHAO, SIUZDAK, GARY E · 2018 to 2021
$2.0M
Orbitrap Elite/H-ESI BundleS10OD018006 · OD · EMORY UNIVERSITY · PI JONES, DEAN PAUL · 2014 to 2014
$600k
Multiscale, multifactorial immune networks as a web serviceUH2AI132345 · NIAID · EMORY UNIVERSITY · PI LI, SHUZHAO · 2017 to 2018
$423k
NCI NIH HHS U01 CA235493NIAID NIH HHS UH2 AI132345NIEHS NIH HHS P30 ES019776NIEHS NIH HHS U2C ES030163NIH HHS S10 OD018006
6 · The paper itself

Abstract

Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many exposures in humans, and the emerging metabolomics technology offers a means to read out both the biological activity and environmental impact in the same dataset. How to integrate exposome and metabolome in data analysis is still challenging. Here, we employ a hierarchical community network to investigate the global associations between the metabolome and mixed exposures including DDTs, PFASs and PCBs, in a women cohort with sera collected in California in the 1960s. Strikingly, this analysis revealed that the metabolite communities associated with the exposures were non-specific and shared among exposures. This suggests that a small number of metabolic phenotypes may account for the response to a large class of environmental chemicals.

Indexed as

ExposomeMetabolomeNeural Networks, ComputerCaliforniaCohort StudiesFemaleHumansMetabolomicsBreast cancerDDTExposomeGene environment interactionHierarchical community networkMetabolic phenotypeMetabolomicsMixed exposuresMulti-omics integrationMWASPCBPFASVariance analysis

Identifiers

PMID31299210
PMCPMC6949431

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.