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. 2009 Jan;35(1):96-108.
doi: 10.1093/schbul/sbn155. Epub 2008 Nov 20.

A Genome-Wide Association Study of Schizophrenia Using Brain Activation as a Quantitative Phenotype

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Free PMC article

A Genome-Wide Association Study of Schizophrenia Using Brain Activation as a Quantitative Phenotype

Steven G Potkin et al. Schizophr Bull. .
Free PMC article

Abstract

Background: Genome-wide association studies (GWASs) are increasingly used to identify risk genes for complex illnesses including schizophrenia. These studies may require thousands of subjects to obtain sufficient power. We present an alternative strategy with increased statistical power over a case-control study that uses brain imaging as a quantitative trait (QT) in the context of a GWAS in schizophrenia.

Methods: Sixty-four subjects with chronic schizophrenia and 74 matched controls were recruited from the Functional Biomedical Informatics Research Network (FBIRN) consortium. Subjects were genotyped using the Illumina HumanHap300 BeadArray and were scanned while performing a Sternberg Item Recognition Paradigm in which they learned and then recognized target sets of digits in an functional magnetic resonance imaging protocol. The QT was the mean blood oxygen level-dependent signal in the dorsolateral prefrontal cortex during the probe condition for a memory load of 3 items.

Results: Three genes or chromosomal regions were identified by having 2 single-nucleotide polymorphisms (SNPs) each significant at P < 10(-6) for the interaction between the imaging QT and the diagnosis (ROBO1-ROBO2, TNIK, and CTXN3-SLC12A2). Three other genes had a significant SNP at <10(-6) (POU3F2, TRAF, and GPC1). Together, these 6 genes/regions identified pathways involved in neurodevelopment and response to stress.

Conclusion: Combining imaging and genetic data from a GWAS identified genes related to forebrain development and stress response, already implicated in schizophrenic dysfunction, as affecting prefrontal efficiency. Although the identified genes require confirmation in an independent sample, our approach is a screening method over the whole genome to identify novel SNPs related to risk for schizophrenia.

Figures

Fig. 1.
Fig. 1.
Regions of the Genome Showing Evidence of Association in the Quantitative Trait (QT) analysis. Physical map of the single-nucleotide polymorphisms (SNPs) associated with (a) ROBO2-ROBO1 region, (b) TNIK gene, and (c) CTXN3-SLC12A2 region produced by WGAViewer. The topmost sector is the ideogram of chromosomes 3 or 5; the vertical red line shows the relative of location of gene region. Below this is the graph showing the –log P significance values of the individual SNPs on the imaging phenotype (dorsolateral prefrontal cortex) for the right hemisphere. The small blue lines below this indicate the location of the exons in the transcripts annotated (translated region of the DNA). The vertical lines above the accompanying triangular matrix indicate the SNP locations and demonstrate the LD pattern between SNPs (D') calculated using Haploview 4·1. The warmer colors on the flame scale indicate greater LD, while the blue indicates absence of LD.
Fig. 1.
Fig. 1.
Regions of the Genome Showing Evidence of Association in the Quantitative Trait (QT) analysis. Physical map of the single-nucleotide polymorphisms (SNPs) associated with (a) ROBO2-ROBO1 region, (b) TNIK gene, and (c) CTXN3-SLC12A2 region produced by WGAViewer. The topmost sector is the ideogram of chromosomes 3 or 5; the vertical red line shows the relative of location of gene region. Below this is the graph showing the –log P significance values of the individual SNPs on the imaging phenotype (dorsolateral prefrontal cortex) for the right hemisphere. The small blue lines below this indicate the location of the exons in the transcripts annotated (translated region of the DNA). The vertical lines above the accompanying triangular matrix indicate the SNP locations and demonstrate the LD pattern between SNPs (D') calculated using Haploview 4·1. The warmer colors on the flame scale indicate greater LD, while the blue indicates absence of LD.
Fig. 1.
Fig. 1.
Regions of the Genome Showing Evidence of Association in the Quantitative Trait (QT) analysis. Physical map of the single-nucleotide polymorphisms (SNPs) associated with (a) ROBO2-ROBO1 region, (b) TNIK gene, and (c) CTXN3-SLC12A2 region produced by WGAViewer. The topmost sector is the ideogram of chromosomes 3 or 5; the vertical red line shows the relative of location of gene region. Below this is the graph showing the –log P significance values of the individual SNPs on the imaging phenotype (dorsolateral prefrontal cortex) for the right hemisphere. The small blue lines below this indicate the location of the exons in the transcripts annotated (translated region of the DNA). The vertical lines above the accompanying triangular matrix indicate the SNP locations and demonstrate the LD pattern between SNPs (D') calculated using Haploview 4·1. The warmer colors on the flame scale indicate greater LD, while the blue indicates absence of LD.

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