Evidence map›Paper›PMID 21468025›Full record

ArticleThe pharmacogenomics journal2012

Pathway based analysis of genotypes in relation to alcohol dependence.

M A Reimers, B P Riley, G Kalsi, D A Kertes, K S Kendler

Open access · greenAbstract read
In one paragraph

Article in The pharmacogenomics journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

8 citing papers in PubMed, 19 citations in OpenAlex.

  1. Flying Together:International journal of molecular sciences · 2020
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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

5 authors at 2 institutions in 1 country.

M A ReimersDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298-0032, USA. mreimers@vcu.edu
B P Riley
G Kalsi
D A Kertes
K S Kendler
Virginia Commonwealth University · USUniversity of Florida · US

Funding

An Alcohol Affected Sib Pair Study of Alcohol DependenceR37AA011408 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI KENDLER, KENNETH SEEDMAN · 2007 to 2016
$6.5M
IRISH AFFECTED SIB PAIR STUDY OF ALCOHOL DEPENDENCER01AA011408 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI KENDLER, KENNETH SEEDMAN · 1997 to 2005
$3.4M
Project 3: Cross Species Characterization of Gene Networks in Acute ResponsesP20AA017828 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI KENDLER, KENNETH SEEDMAN, MILES, MICHAEL F · 2009 to 2012
$2.2M
NIAAA NIH HHS P20 AA017828NIAAA NIH HHS R01 AA011408NIAAA NIH HHS R01-AA-11408NIAAA NIH HHS R37 AA011408
6 · The paper itself

Abstract

We introduce a method for detecting variants in several genes of related function with small effect on a phenotype of interest. Our method uses logistic regression to test whether multiple alleles within a functional set have significantly higher than expected predictive value, even though none individually may have strong individual effects. We illustrate this method by testing seven gene sets (including 48 genes), from a study with 1350 single nucleotide polymorphisms in 130 addiction candidate genes studied in a sample of 575 alcohol dependence (AD) cases and 530 controls. We conclude that AD is related to variation in genes participating in Glutamate and γ-amino butyric acid signaling, as has been reported elsewhere, and in stress response pathways, but not with genes in several other systems implicated in other drugs of abuse.

Indexed as

GenotypeAlcoholismgamma-Aminobutyric AcidGene Regulatory NetworksGlutamic AcidHumansLinkage DisequilibriumPolymorphism, Single NucleotideSignal TransductionTranscriptomegamma-Aminobutyric AcidGlutamic Acid

Identifiers

PMID21468025
PMCPMC3134610
OpenAlexW2080705319

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.