Evidence map›Paper›PMID 26010994›Full record

ArticleBirth defects research. Part A, Clinical and molecular teratology2015

Detecting gene-environment interactions in human birth defects: Study designs and statistical methods.

Caroline G Tai, Rebecca E Graff, Jinghua Liu, Michael N Passarelli, Joel A Mefford, Gary M Shaw, Thomas J Hoffmann, John S Witte

Abstract read
In one paragraph

Article in Birth defects research. Part A, Clinical and molecular teratology, 2015. 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
0.6field-weighted citation impact, top 20% 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, 9 citations in OpenAlex.

  1. Article
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  3. Review
  4. 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

8 authors at 4 institutions in 2 countries.

Caroline G TaiDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California.
Rebecca E GraffDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California.
Jinghua LiuInstitute for Human Genetics, University of California San Francisco, San Francisco, California.
Michael N PassarelliDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California.
Joel A MeffordDepartment of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California.
Gary M ShawDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California.
Thomas J HoffmannDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California.
John S WitteDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California.
University of California, San Francisco · USInstitute of Human Genetics · PLStanford University · USUCSF Helen Diller Family Comprehensive Cancer Center · US

Funding

Genomic/Epigenomic Factors and Non-Syndromic Congenital Heart Defect Risk R01HD039054 · NICHD · ARKANSAS CHILDREN'S HOSPITAL RES INST · PI HOBBS, CHARLOTTE A · 2000 to 2016
$13.6M
Training in Molecular& Genetic Epidemiology of CancerR25CA112355 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WITTE, JOHN S. · 2005 to 2018
$6.5M
Genetic Epidemiology of Prostate Cancer Risk and ProgressionR01CA088164 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VAN DEN EEDEN, STEPHEN K., WITTE, JOHN S. · 2000 to 2015
$6.1M
NCI NIH HHS R01 CA088164NCI NIH HHS R01CA088164NCI NIH HHS R25 CA112355NCI NIH HHS R25CA112355NICHD NIH HHS R01 HD039054NICHD NIH HHS R01HD039054
6 · The paper itself

Abstract

backgroundThe National Birth Defects Prevention Study (NBDPS) contains a wealth of information on affected and unaffected family triads, and thus provides numerous opportunities to study gene-environment interactions (G×E) in the etiology of birth defect outcomes. Depending on the research objective, several analytic options exist to estimate G×E effects that use varying combinations of individuals drawn from available triads.

methodsIn this study, we discuss important considerations in the collection of genetic data and environmental exposures.

resultsWe will also present several population- and family-based approaches that can be applied to data from the NBDPS including case-control, case-only, family-based trio, and maternal versus fetal effects. For each, we describe the data requirements, applicable statistical methods, advantages, and disadvantages.

conclusionA range of approaches can be used to evaluate potentially important G×E effects in the NBDPS. Investigators should be aware of the limitations inherent to each approach when choosing a study design and interpreting results.

Indexed as

Gene-Environment InteractionGenetic Predisposition to DiseaseModels, StatisticalResearch DesignCase-Control StudiesCongenital AbnormalitiesFemaleHumansMalePedigreePolymorphism, Single NucleotideRisk Factorsbirth defectscase-onlycongenital heart defectsfamily-based studygene-environment interactiongenetic epidemiologyNational Birth Defects Prevention Studyneural tube defectstransmission disequilibrium test

Identifiers

PMID26010994
PMCPMC4537677
OpenAlexW1943703850

What OpenQuestion holds

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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.