4.7 Article

Multifaceted genomic risk for brain function in schizophrenia

Journal

NEUROIMAGE
Volume 61, Issue 4, Pages 866-875

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2012.03.022

Keywords

Schizophrenia; fMRI; SNP; Parallel-ICA; Multivariate

Funding

  1. National Institutes of Health [5 P20 RR 021938-03]

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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 x 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. (C) 2012 Elsevier Inc. All rights reserved.

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