Evidence map›Paper›PMID 39473136›Full record

ArticleBiometrical journal. Biometrische Zeitschrift2024

Cross-Cohort Mixture Analysis: A Data Integration Approach With Applications on Gestational Age and DNA-Methylation-Derived Gestational Age Acceleration Metrics.

Elena Colicino, Roberto Ascari, Hachem Saddiki, Francheska Merced-Nieves, Nicolò Foppa Pedretti, Kathi Huddleston, Robert O Wright, Rosalind J Wright, Program Collaborators for Environmental Influences on Child Health Outcomes

Abstract read
In one paragraph

Article in Biometrical journal. Biometrische Zeitschrift, 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. Article
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

9 authors.

Elena ColicinoDepartment of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID https://orcid.org/0000-0002-1875-8448
Roberto AscariDepartment of Economics, Management and Statistics, University of Milano-Bicocca, Milan, Italy.ORCID https://orcid.org/0000-0003-0146-976X
Hachem SaddikiDepartment of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Francheska Merced-NievesDepartment of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Nicolò Foppa PedrettiDepartment of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID https://orcid.org/0000-0003-1306-8170
Kathi HuddlestonDepartment of Nursing, George Mason University, Fairfax, Virginia, USA.
Robert O WrightDepartment of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Rosalind J WrightDepartment of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Program Collaborators for Environmental Influences on Child Health Outcomes

Funding

Project-005U2COD023375 · OD · DUKE UNIVERSITY · PI Linda S Adair, Phillip Brian Smith · 2016 to 2026
$215.9M
ECHODAC (Environmental Influences on Child Health Outcomes Data Analysis Center)U24OD023382 · OD · JOHNS HOPKINS UNIVERSITY · PI Diane J Catellier, LISA P JACOBSON · 2016 to 2026
$148.4M
Mount Sinai ECHO site for Perinatal Environment and Development StudiesUH3OD023337 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KECIA Nicole CARROLL, Robert O Wright · 2018 to 2026
$54.1M
Conduits: Mount Sinai Health System Translational Science HubUL1TR004419 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$46.4M
The ECHO Measurement Core: A Framework and Resource for Assessing Environmental Exposure and Child HealthU24OD023319 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Courtney K Blackwell, RICHARD GERSHON · 2016 to 2026
$43.7M
NCATS NIH HHS UL1 TR004419NIH HHS U24 OD023319NIH HHS U24OD023319NIH HHS U24 OD023382NIH HHS U24OD023382NIH HHS U2C OD023375NIH HHS U2COD023375NIH HHS UH3 OD023337NIH HHS UH3OD023337
6 · The paper itself

Abstract

Data integration of multiple studies can provide enhanced exposure contrast and statistical power to examine associations between environmental exposure mixtures and health outcomes. Extant research has combined populations and identified an overall mixture-outcome association, without accounting for differences across studies. We extended the Bayesian Weighted Quantile Sum (BWQS) regression to a hierarchical framework to analyze mixtures across cohorts. The hierarchical BWQS (HBWQS) approach aggregates sample size of multiple cohorts to calculate an overall mixture index, thereby identifying the most harmful exposure(s) across cohorts; and provides cohort-specific associations between the overall mixture index and the outcome. We showed results from 10 simulated scenarios including four mixture components in three, eight, and ten populations, and two real-case examples on the association between prenatal metal mixture exposure-comprising arsenic, cadmium, and lead-and both gestational age and epigenetic-derived gestational age acceleration metrics. Simulated scenarios showed good empirical coverage and little bias for all HBWQS-estimated parameters. The Watanabe-Akaike information criterion showed a better average performance for the HBWQS regression than the BWQS across scenarios. HBWQS results incorporating cohorts within the national Environmental influences on Child Health Outcomes (ECHO) program from three different sites showed that the environmental mixture was negatively associated with gestational age in a single site. The HBWQS approach facilitates the combination of multiple cohorts and accounts for individual cohort differences in mixture analyses. HBWQS findings can be used to develop regulations, policies, and interventions regarding multiple co-occurring environmental exposures and it will maximize the use of extant publicly available data.

Indexed as

BiometryDNA MethylationGestational AgeBayes TheoremCohort StudiesEnvironmental ExposureFemaleHumansPregnancyBayesianCross‐studyHBWQSHierarchical modelsMixtureWeighted Quantile Sum (WQS) regression

Identifiers

PMID39473136
PMCPMC12852946

What OpenQuestion holds

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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.