Evidence map›Paper›PMID 28823710›Full record

ArticleBiological psychiatry2017

No Evidence That Schizophrenia Candidate Genes Are More Associated With Schizophrenia Than Noncandidate Genes.

Emma C Johnson, Richard Border, Whitney E Melroy-Greif, Christiaan A de Leeuw, Marissa A Ehringer, Matthew C Keller

Abstract read
In one paragraph

Article in Biological psychiatry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 9 pooled it
–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

74 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  17. A Comprehensive 4-layeredCurrent pharmaceutical biotechnology · 2025
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14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Emma C JohnsonDepartment of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado. Electronic address: emma.c.johnson@colorado.edu.
Richard BorderDepartment of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado.
Whitney E Melroy-GreifDepartment of Neuroscience, The Scripps Research Institute, La Jolla, California.
Christiaan A de LeeuwDepartment of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research/VU University Amsterdam, Amsterdam; Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, the Netherlands.
Marissa A EhringerInstitute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado.
Matthew C KellerDepartment of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado.

Funding

Alcohol Research in the Science/Practitioner ModelT32AA013525 · NIAAA · SAN DIEGO STATE UNIVERSITY · PI EDWARD P RILEY, ANDREA SPADONI TOWNSEND · 2002 to 2026
$8.4M
Estimating the genetic and environmental architecture of psychiatric disordersR01MH100141 · NIMH · UNIVERSITY OF COLORADO · PI KELLER, MATTHEW CHARLES · 2013 to 2022
$5.3M
RESEARCH TRAINING: DEVELOPMENTAL BEHAVIORAL GENETICST32HD007289 · NICHD · UNIVERSITY OF COLORADO AT BOULDER · PI STALLINGS, MICHAEL CRAIG · 1985 to 2014
$3.1M
Translational studies of nicotinic receptor genes: alcohol and nicotine behaviorsR01AA017889 · NIAAA · UNIVERSITY OF COLORADO · PI EHRINGER, MARISSA A · 2009 to 2013
$2.6M
NIAAA NIH HHS R01 AA017889NIAAA NIH HHS T32 AA013525NICHD NIH HHS T32 HD007289NIMH NIH HHS R01 MH100141
6 · The paper itself

Abstract

backgroundA recent analysis of 25 historical candidate gene polymorphisms for schizophrenia in the largest genome-wide association study conducted to date suggested that these commonly studied variants were no more associated with the disorder than would be expected by chance. However, the same study identified other variants within those candidate genes that demonstrated genome-wide significant associations with schizophrenia. As such, it is possible that variants within historic schizophrenia candidate genes are associated with schizophrenia at levels above those expected by chance, even if the most-studied specific polymorphisms are not.

methodsThe present study used association statistics from the largest schizophrenia genome-wide association study conducted to date as input to a gene set analysis to investigate whether variants within schizophrenia candidate genes are enriched for association with schizophrenia.

resultsAs a group, variants in the most-studied candidate genes were no more associated with schizophrenia than were variants in control sets of noncandidate genes. While a small subset of candidate genes did appear to be significantly associated with schizophrenia, these genes were not particularly noteworthy given the large number of more strongly associated noncandidate genes.

conclusionsThe history of schizophrenia research should serve as a cautionary tale to candidate gene investigators examining other phenotypes: our findings indicate that the most investigated candidate gene hypotheses of schizophrenia are not well supported by genome-wide association studies, and it is likely that this will be the case for other complex traits as well.

Indexed as

Genome-Wide Association StudyCase-Control StudiesGenetic Predisposition to DiseaseHumansPolymorphism, Single NucleotideReproducibility of ResultsSchizophreniaCandidate genesComplex traitsGene set analysisGenome-wide association studyGWASSchizophreniaSingle nucleotide polymorphismSNP

Identifiers

PMID28823710
PMCPMC5643230

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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.