| 1 | Schizophr Bull 2009 Jan 35: 96-108 |
|---|---|
| PMID | 19023125 |
| Title | A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype. |
| Abstract | 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. 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. 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. 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. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 2 | Schizophr Bull 2009 Jan 35: 96-108 |
| PMID | 19023125 |
| Title | A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype. |
| Abstract | 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. 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. 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. 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. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 3 | Neuroimage 2010 Nov 53: 839-47 |
| PMID | 20600988 |
| Title | Identifying gene regulatory networks in schizophrenia. |
| Abstract | The imaging genetics approach to studying the genetic basis of disease leverages the individual strengths of both neuroimaging and genetic studies by visualizing and quantifying the brain activation patterns in the context of genetic background. Brain imaging as an intermediate phenotype can help clarify the functional link among genes, the molecular networks in which they participate, and brain circuitry and function. Integrating genetic data from a genome-wide association study (GWAS) with brain imaging as a quantitative trait (QT) phenotype can increase the statistical power to identify risk genes. A QT analysis using brain imaging (DLPFC activation during a working memory task) as a quantitative trait has identified unanticipated risk genes for schizophrenia. Several of these genes (RSRC1, ARHGAP18, ROBO1-ROBO2, GPC1, TNIK, and CTXN3-SLC12A2) have functions related to progenitor cell proliferation, migration, and differentiation, cytoskeleton reorganization, axonal connectivity, and development of forebrain structures. These genes, however, do not function in isolation but rather through gene regulatory networks. To obtain a deeper understanding how the GWAS-identified genes participate in larger gene regulatory networks, we measured correlations among transcript levels in the mouse and human postmortem tissue and performed a gene set enrichment analysis (GSEA) that identified several microRNA associated with schizophrenia (448, 218, 137). The results of such computational approaches can be further validated in animal experiments in which the networks are experimentally studied and perturbed with specific compounds. Glypican 1 and FGF17 mouse models for example, can be used to study such gene regulatory networks. The model demonstrates epistatic interactions between FGF and glypican on brain development and may be a useful model of negative symptom schizophrenia. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 4 | Behav Brain Funct 2012 -1 8: 27 |
| PMID | 22643131 |
| Title | Association of CTXN3-SLC12A2 polymorphisms and schizophrenia in a Thai population. |
| Abstract | A genome-wide association study (GWAS) combined with brain imaging as a quantitative trait analysis revealed that the SNPs near CTXN3-SLC12A2 region were related to forebrain development and stress response which involved in schizophrenia. In the present study, the SNPs in this region were analyzed for association with schizophrenia in a Thai population. A total of 115 schizophrenia and 173 unrelated normal controls with mean age of 37.87?±?11.8 and 42.81?±?6.0 years, respectively, were included in this study. Genotyping was performed using polymerase chain reaction and high-resolution melting (HRM) analysis. The difference in genotype distribution between patient and control was assessed by Chi-square test of the SPSS software. We found a significant association between the GWAS-discovered SNP, rs245178, with the risk of schizophrenia in the Thai population [P?=?0.006, odds ratio for the minor G allele: 0.62(0.46-0.83)]. Additionally, another potential SNP, rs698172, which was in moderate linkage disequilibrium with rs245178, also showed strong association with schizophrenia [P?=?0.003, odds ratio for minor T allele: 0.61(0.46-0.82)]. This association remained significant at 5% level after the Bonferroni correction for multiple testing. This study shows that two SNPs in intergenic of the CTXN3 and SLC12A2 genes, rs245178 and rs698172, are associated with risk of schizophrenia in Thai population. Further study is required for clarification the role of genetic variation around these SNPs in expression pattern of the CTXN3 and SLC12A2 genes, which may be involved in schizophrenia pathogenesis. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 5 | Behav Brain Funct 2015 -1 11: 10 |
| PMID | 25889058 |
| Title | Association between 5q23.2-located polymorphism of CTXN3 gene (Cortexin 3) and schizophrenia in European-Caucasian males; implications for the aetiology of schizophrenia. |
| Abstract | The objective of the study was to examine several polymorphisms in DISC1 and CTNX3 genes as possible risk factors in schizophrenia. DISC1 (disrupted-in-schizophrenia 1) has been studied extensively in relation to mental disease while CTXN3, has only recently emerged as a potential "candidate" gene in schizophrenia. CTXN3 resides in a genomic region (5q21-34) known to be associated with schizophrenia and encodes a protein cortexin 3 which is highly enriched in brain. We used ethnically homogeneous samples of 175 male patients and 184 male control subjects. All patients were interviewed by two similarly qualified psychiatrists. Controls were interviewed by one of the authors (O.S.). Genotyping was performed, following amplification by polymerase chain reaction (PCR), using fragment analysis in a standard commercial setting (Applied Biosystems, USA). We have found a statistically significant association between rs6595788 polymorphism of CTXN3 gene and the risk of schizophrenia; the presence of AG genotype increased the risk 1.5-fold. Polymorphisms in DISC1 gene showed only marginally statistically significant association with schizophrenia (rs17817356) or no association whatsoever (rs821597 and rs980989) while two polymorphisms (rs9661837 and rs3737597) were found to be only slightly polymorphic in the samples. Evidence available in the literature suggests that altered expression of cortexin 3, either alone, or in parallel with changes in DISC1, could subtly perturb GABAergic neurotransmission and/or metabolism of amyloid precursor protein (APP) in developing brain, thus potentially exposing the affected individual to an increased risk of schizophrenia later in life. |
| SCZ Keywords | schizophrenia, schizophrenic |