Evidence map›Paper›PMID 22311237›Full record

ArticleGenetic epidemiology2012

Gene-environment interactions on growth trajectories.

Shuang Wang, Wei Xiong, Weiping Ma, Stephen Chanock, Wieslaw Jedrychowski, Rongling Wu, Frederica P Perera

Open access · greenAbstract read
In one paragraph

Article in Genetic epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 5 institutions in 3 countries.

Shuang WangDepartment of Biostatistics, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA. sw2206@columbia.edu
Wei Xiong
Weiping Ma
Stephen Chanock
Wieslaw Jedrychowski
Rongling Wu
Frederica P Perera
Columbia University · USFudan University · CNJagiellonian University · PLNational Cancer Institute · USPenn State Milton S. Hershey Medical Center · US

Funding

Laboratory of Translational GenomicsZIACP010201 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI PROKUNINA-OLSSON, LIUDMILA · 2010 to 2025
$91.2M
HEALTH EFFECTS OF PAH &ETS IN MINORITY WOMEN &NEWBORNSR01ES008977 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PERERA, FREDERICA P · 1997 to 2011
$12.9M
The Columbia Center for Children's Environmental HealthP01ES009600 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PERERA, FREDERICA P · 1999 to 2014
$11.2M
Windows of Susceptibility to PAH/DEP Exposure and AsthmaP50ES015905 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PERERA, FREDERICA P · 2007 to 2011
$10.3M
Developmental effects of early-life exposure to airborne PAHs.R01ES015282 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PERERA, FREDERICA P · 2009 to 2012
$1.7M
NIEHS NIH HHS P01 ES009600NIEHS NIH HHS P01 ES09600NIEHS NIH HHS P50 ES015905NIEHS NIH HHS P50ES015905NIEHS NIH HHS R01 ES008977NIEHS NIH HHS R01 ES015282NIEHS NIH HHS R01 ES08977
6 · The paper itself

Abstract

It has been suggested that children with larger brains tend to perform better on IQ tests or cognitive function tests. Prenatal head growth and head growth in infancy are two crucial periods for subsequent intelligence. Studies have shown that environmental exposure to air pollutants during pregnancy is associated with fetal growth reduction, developmental delay, and reduced IQ. Meanwhile, genetic polymorphisms may modify the effect of environment on head growth. However, studies on gene-environment or gene-gene interactions on growth trajectories have been quite limited partly due to the difficulty to quantitatively measure interactions on growth trajectories. Moreover, it is known that assessing the significance of gene-environment or gene-gene interactions on cross-sectional outcomes empirically using the permutation procedures may bring substantial errors in the tests. We proposed a score that quantitatively measures interactions on growth trajectories and developed an algorithm with a parametric bootstrap procedure to empirically assess the significance of the interactions on growth trajectories under the likelihood framework. We also derived a Wald statistic to test for interactions on growth trajectories and compared it to the proposed parametric bootstrap procedure. Through extensive simulation studies, we demonstrated the feasibility and power of the proposed testing procedures. We applied our method to a real dataset with head circumference measures from birth to age 7 on a cohort currently being conducted by the Columbia Center for Children's Environmental Health (CCCEH) in Krakow, Poland, and identified several significant gene-environment interactions on head circumference growth trajectories.

Indexed as

Gene-Environment InteractionModels, GeneticModels, StatisticalAir PollutantsAlgorithmsAryl Hydrocarbon HydroxylasesChildChild, PreschoolComputer SimulationCytochrome P-450 CYP1A1Cytochrome P-450 CYP1B1Environmental ExposureEpistasis, GeneticFemaleGlutathione TransferaseHeadAir PollutantsAryl Hydrocarbon HydroxylasesCYP1A1 protein, humanCYP1B1 protein, humanCytochrome P-450 CYP1A1Cytochrome P-450 CYP1B1glutathione S-transferase T1Glutathione TransferaseGSTT2 protein, human

Identifiers

PMID22311237
PMCPMC3380164
OpenAlexW1960287548

What OpenQuestion holds

Textmetadata
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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.