Evidence map›Paper›PMID 23922213›Full record

ArticleStatistics in medicine2014

Testing gene-environment interactions in family-based association studies using trait-based ascertained samples.

Weiming Zhang, Carl D Langefeld, Gary K Grunwald, Tasha E Fingerlin

Open access · greenAbstract read
In one paragraph

Article in Statistics in medicine, 2014. 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
0.2field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  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

4 authors at 2 institutions in 1 country.

Weiming ZhangDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, U.S.A.
Carl D Langefeld
Gary K Grunwald
Tasha E Fingerlin
Colorado School of Public Health · USWake Forest University · US

Funding

Genetic & Epidemiologic Predictors of Glucose Homeostasis Measures in HispanicsR01DK085175 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WAGENKNECHT, LYNNE E, WATANABE, RICHARD M · 2010 to 2013
$6.9M
Molecular genetics of glucose homeostasis and fatR01HL060894 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BOWDEN, DONALD W · 1999 to 2009
$6.0M
IRAS FAMILY STUDY--GENETICS OF INSULIN RESISTANCER01HL060944 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WAGENKNECHT, LYNNE E · 1999 to 2009
$5.5M
IRAS FAMILY STUDY--GENETICS OF INSULIN RESISTANCER01HL061019 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI NORRIS, JILL M · 1999 to 2009
$2.6M
IRAS FAMILY STUDY: GENETICS OF INSULIN RESISTANCER01HL061210 · NHLBI · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI BRYER-ASH, MICHAEL · 1999 to 2008
$2.3M
IRAS FAMILY STUDY--GENETICS OF INSULIN RESISTANCER01HL060931 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BERGMAN, RICHARD NATHAN · 1999 to 2003
$852k
NHLBI NIH HHS HL-60894NHLBI NIH HHS HL-60931-02NHLBI NIH HHS HL-60944-02NHLBI NIH HHS HL-61019-02NHLBI NIH HHS HL-61210-02NHLBI NIH HHS R01 HL060894NHLBI NIH HHS R01 HL060931NHLBI NIH HHS R01 HL060944NHLBI NIH HHS R01 HL061019NHLBI NIH HHS R01 HL061210NIDDK NIH HHS DK-085175-11A1NIDDK NIH HHS R01 DK085175
6 · The paper itself

Abstract

The study of gene-environment interactions is an increasingly important aspect of genetic epidemiological investigation. Historically, it has been difficult to study gene-environment interactions using a family-based design for quantitative traits or when parent-offspring trios were incomplete. The QBAT-I provides researchers a tool to estimate and test for a gene-environment interaction in families of arbitrary structure that are sampled without regard to the phenotype of interest, but is vulnerable to inflated type I error if families are ascertained on the basis of the phenotype. In this study, we verified the potential for type I error of the QBAT-I when applied to samples ascertained on a trait of interest. The magnitude of the inflation increases as the main genetic effect increases and as the ascertainment becomes more extreme. We propose an ascertainment-corrected score test that allows the use of the QBAT-I to test for gene-environment interactions in ascertained samples. Our results indicate that the score test and an ad hoc method we propose can often restore the nominal type I error rate, and in cases where complete restoration is not possible, dramatically reduce the inflation of the type I error rate in ascertained samples.

Indexed as

Data Interpretation, StatisticalGene-Environment InteractionModels, GeneticQuantitative Trait, HeritableFamilyGenotypeHumansPhenotypeascertainmentfamily-based association studygene-environment interactionQBAT-Iquantitative trait

Identifiers

PMID23922213
PMCPMC4041108
OpenAlexW1994873658

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.