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

doi:10.1016/j.neuroimage.2012.03.022

Back

Multifaceted genomic risk for brain function in schizophrenia

Journal article

Peer reviewed

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 and Jingyu Liu

NeuroImage (Orlando, Fla.), Vol.61(4), pp.866-875

07/16/2012

DOI: 10.1016/j.neuroimage.2012.03.022

PMCID: PMC3376184

PMID: 22440650

Files and links (1)

url

https://www.ncbi.nlm.nih.gov/pmc/articles/3376184View

Open Access

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. ► We analyze SNP data in conjunction with fMRI data using a multivariate approach. ► We identify a SNP component related to brain function disruptions in schizophrenia. ► Schizophrenia patients show disrupted functions in precentral and postcentral gyri. ► The related SNP component presents a combined effect from multiple SNPs and genes. ► The related SNP component involves four neurotransmitter signaling pathways.

Schizophrenia

fMRI

SNP

Multivariate

Parallel-ICA

Details

Title: Subtitle: Multifaceted genomic risk for brain function in schizophrenia
Creators: Jiayu Chen - Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA
Vince D Calhoun - Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA
Godfrey D Pearlson - Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT 06106-3310, USA
Stefan Ehrlich - Massachusetts General Hospital/Massachusetts Institute of Technology/Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129-2000, USA
Jessica A Turner - The Mind Research Network, Albuquerque, NM 87106-3834, USA
Beng-Choon Ho - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA 52242-100, USA
Thomas H Wassink - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA 52242-100, USA
Andrew M Michael - The Mind Research Network, Albuquerque, NM 87106-3834, USA
Jingyu Liu - Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA
Resource Type: Journal article
Publication Details: NeuroImage (Orlando, Fla.), Vol.61(4), pp.866-875
DOI: 10.1016/j.neuroimage.2012.03.022
PMID: 22440650
PMCID: PMC3376184
NLM abbreviation: Neuroimage
ISSN: 1053-8119
eISSN: 1095-9572
Publisher: Elsevier Inc
Grant note: DOI: 10.13039/100000002, name: National Institutes of Health, award: 5 P20 RR 021938–03
Language: English
Date published: 07/16/2012
Academic Unit: Psychiatry; Stead Family Department of Pediatrics
Record Identifier: 9984003468302771

Metrics

27 Record Views

38 Times Cited - Web of Science