Evidence map›Paper›PMID 28343281›Full record

ArticleBehavior genetics2017

Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders.

Seung Bin Cho, Fazil Aliev, Shaunna L Clark, Amy E Adkins, Howard J Edenberg, Kathleen K Bucholz, Bernice Porjesz, Danielle M Dick

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Behavior genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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.

Seung Bin ChoDepartment of Psychology, Virginia Commonwealth University, PO Box 842018, 817W. Franklin Street, Richmond, VA, 23284-2018, USA. sbcho@vcu.edu.ORCID 0000-0003-0336-6625
Fazil AlievDepartment of Psychology, Virginia Commonwealth University, PO Box 842018, 817W. Franklin Street, Richmond, VA, 23284-2018, USA.
Shaunna L ClarkCenter for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA.
Amy E AdkinsDepartment of Psychology, Virginia Commonwealth University, PO Box 842018, 817W. Franklin Street, Richmond, VA, 23284-2018, USA.
Howard J EdenbergDepartment of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA.
Kathleen K BucholzDepartment of Psychiatry, Washington University, Saint Louis, MO, USA.
Bernice PorjeszDepartment of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA.
Danielle M DickDepartment of Psychology, Virginia Commonwealth University, PO Box 842018, 817W. Franklin Street, Richmond, VA, 23284-2018, USA.

Funding

Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI TIMOTHY J. EBERLEIN · 2001 to 2026
$128.0M
Washington University Institute of Clinical and Translational Sciences (UL1)UL1RR024992 · NCRR · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2007 to 2011
$45.4M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
JH/CIDR Genotyping for Genome-Wide Association StudiesU01HG004438 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI VALLE, DAVID · 2007 to 2011
$24.2M
Investigating Methylation Patterns Associated with Alcohol Use and AddictionK01AA021266 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI CLARK, SHAUNNA L · 2012 to 2016
$580k
NCATS NIH HHS UL1 TR000448NCRR NIH HHS UL1 RR024992NHGRI NIH HHS U01 HG004438NHLBI NIH HHS HHSN268200782096CNIAAA NIH HHS K01 AA021266
6 · The paper itself

Abstract

Twin studies indicate that latent genetic factors overlap across comorbid psychiatric disorders. In this study, we used a novel approach to elucidate shared genetic factors across psychiatric outcomes by clustering single nucleotide polymorphisms based on their genome-wide association patterns. We applied latent profile analysis (LPA) to p-values resulting from genome-wide association studies across three phenotypes: symptom counts of alcohol dependence (AD), antisocial personality disorder (ASP), and major depression (MD), using the European-American case-control genome-wide association study subsample of the collaborative study on the genetics of alcoholism (N = 1399). In the 3-class model, classes were characterized by overall low associations (85.6% of SNPs), relatively stronger association only with MD (6.8%), and stronger associations with AD and ASP but not with MD (7.6%), respectively. These results parallel the genetic factor structure identified in twin studies. The findings suggest that applying LPA to association results across multiple disorders may be a promising approach to identify the specific genetic etiologies underlying shared genetic variance.

Indexed as

AlcoholismAntisocial Personality DisorderCase-Control StudiesCluster AnalysisComorbidityFemaleGenetic Association StudiesGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyGenotypeHumansMajor Depressive DisorderMaleMental DisordersMental HealthComorbidityGenetic etiologyGWASLatent profile analysisPsychiatric disorder

Identifiers

PMID28343281
PMCPMC5996973

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.