Evidence map›Paper›PMID 22440650›Full record

ArticleNeuroImage2012

Multifaceted genomic risk for brain function in schizophrenia.

Jiayu Chen, Vince D Calhoun, Godfrey D Pearlson, Stefan Ehrlich, Jessica A Turner, Beng-Choon Ho, Thomas H Wassink, Andrew M Michael, Jingyu Liu

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
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  18. Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2014
    Article
  19. Review
  20. A review of multivariate analyses in imaging genetics.Frontiers in neuroinformatics · 2014
    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

9 authors at 6 institutions in 2 countries.

Jiayu ChenDepartment of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA. jchen@mrn.org
Vince D Calhoun
Godfrey D Pearlson
Stefan Ehrlich
Jessica A Turner
Beng-Choon Ho
Thomas H Wassink
Andrew M Michael
Jingyu Liu
Mind Research Network · USUniversity of Iowa · USUniversity of New Mexico · USInstitute for Community Living · USRochester Institute of Technology · USUniversity Hospital Carl Gustav Carus · DE

Funding

Multivariate methods for identifying multitask/multimodal brain imaging biomarkersR01EB006841 · NIBIB · THE MIND RESEARCH NETWORK · PI VINCE D CALHOUN, Sergey Plis · 2007 to 2026
$9.8M
NEURAL MECHANISMS OF SCHIZOPHRENIAP20RR021938 · NCRR · THE MIND RESEARCH NETWORK · PI JUNG, REX · 2008 to 2011
$9.4M
Unified multivariate data-driven solutions for static and dynamic brain connectivityR01EB020407 · NIBIB · THE MIND RESEARCH NETWORK · PI ADALI, TULAY, CALHOUN, VINCE D · 2015 to 2018
$2.7M
NCRR NIH HHS 5 P20-RR 021938-03NCRR NIH HHS P20 RR021938NIBIB NIH HHS R01 EB006841NIBIB NIH HHS R01 EB020407
6 · The paper itself

Abstract

Recently, deriving candidate endophenotypes from brain imaging data has become a valuable approach to study genetic influences on schizophrenia (SZ), whose pathophysiology remains unclear. In this work we utilized a multivariate approach, parallel independent component analysis, to identify genomic risk components associated with brain function abnormalities in SZ. 5157 candidate single nucleotide polymorphisms (SNPs) were derived from genome-wide array based on their possible connections with SZ and further investigated for their associations with brain activations captured with functional magnetic resonance imaging (fMRI) during a sensorimotor task. Using data from 92 SZ patients and 116 healthy controls, we detected a significant correlation (r=0.29; p=2.41 × 10(-5)) between one fMRI component and one SNP component, both of which significantly differentiated patients from controls. The fMRI component mainly consisted of precentral and postcentral gyri, the major activated regions in the motor task. On average, higher activation in these regions was observed in participants with higher loadings of the linked SNP component, predominantly contributed to by 253 SNPs. 138 identified SNPs were from known coding regions of 100 unique genes. 31 identified SNPs did not differ between groups, but moderately correlated with some other group-discriminating SNPs, indicating interactions among alleles contributing toward elevated SZ susceptibility. The genes associated with the identified SNPs participated in four neurotransmitter pathways: GABA receptor signaling, dopamine receptor signaling, neuregulin signaling and glutamate receptor signaling. In summary, our work provides further evidence for the complexity of genomic risk to the functional brain abnormality in SZ and suggests a pathological role of interactions between SNPs, genes and multiple neurotransmitter pathways.

Indexed as

Brain MappingGenetic Predisposition to DiseaseAdolescentAdultBrainFemaleGenome-Wide Association StudyHumansMagnetic Resonance ImagingMaleMiddle AgedPolymorphism, Single NucleotideSchizophreniaSynaptic TransmissionYoung Adult

Identifiers

PMID22440650
PMCPMC3376184
OpenAlexW2079770462

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.