| 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 | Mol. Cell. Neurosci. 2011 Jun 47: 93-9 |
| PMID | 21440632 |
| Title | Knockdown of mental disorder susceptibility genes disrupts neuronal network physiology in vitro. |
| Abstract | schizophrenia and bipolar disorder are common diseases caused by multiple genes that disrupt brain circuits. While great progress has been made in identifying schizophrenia susceptibility genes, these studies have left two major unanswered mechanistic questions: is there a core biochemical mechanism that these genes regulate, and what are the electrophysiological consequences of the altered gene expression? Because clinical studies implicate abnormalities in neuronal networks, we developed a system for studying the neurophysiology of neuronal networks in vitro where the role of candidate disease genes can be rapidly assayed. Using this system we focused on three postsynaptic proteins DISC1, TNIK and PSD-93/DLG2 each of which is encoded by a schizophrenia susceptibility gene. We also examined the utility of this assay system in bipolar disorder (BD), which has a strong genetic overlap with schizophrenia, by examining the bipolar disorder susceptibility gene Dctn5. The global neuronal network firing behavior of primary cultures of mouse hippocampus neurons was examined on multi-electrode arrays (MEAs) and genes of interest were knocked down using RNAi interference. Measurement of multiple neural network parameters demonstrated phenotypes for these genes compared with controls. Moreover, the different genes disrupted network properties and showed distinct and overlapping effects. These data show multiple susceptibility genes for complex psychiatric disorders, regulate neural network physiology and demonstrate a new assay system with wide application. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 5 | Mol. Psychiatry 2011 Oct 16: 1006-23 |
| PMID | 20838393 |
| Title | The psychiatric disease risk factors DISC1 and TNIK interact to regulate synapse composition and function. |
| Abstract | Disrupted in schizophrenia 1 (DISC1), a genetic risk factor for multiple serious psychiatric diseases including schizophrenia, bipolar disorder and autism, is a key regulator of multiple neuronal functions linked to both normal development and disease processes. As these diseases are thought to share a common deficit in synaptic function and architecture, we have analyzed the role of DISC1 using an approach that focuses on understanding the protein-protein interactions of DISC1 specifically at synapses. We identify the Traf2 and Nck-interacting kinase (TNIK), an emerging risk factor itself for disease, as a key synaptic partner for DISC1, and provide evidence that the DISC1-TNIK interaction regulates synaptic composition and activity by stabilizing the levels of key postsynaptic density proteins. Understanding the novel DISC1-TNIK interaction is likely to provide insights into the etiology and underlying synaptic deficits found in major psychiatric diseases. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 6 | Mol. Psychiatry 2012 Sep 17: 887-905 |
| PMID | 22584867 |
| Title | Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction. |
| Abstract | We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 7 | Neuropharmacology 2012 Mar 62: 1230-41 |
| PMID | 21195721 |
| Title | DISC1-binding proteins in neural development, signalling and schizophrenia. |
| Abstract | In the decade since Disrupted in schizophrenia 1 (DISC1) was first identified it has become one of the most convincing risk genes for major mental illness. As a multi-functional scaffold protein, DISC1 has multiple identified protein interaction partners that highlight pathologically relevant molecular pathways with potential for pharmaceutical intervention. Amongst these are proteins involved in neuronal migration (e.g. APP, Dixdc1, LIS1, NDE1, NDEL1), neural progenitor proliferation (GSK3?), neurosignalling (Girdin, GSK3?, PDE4) and synaptic function (Kal7, TNIK). Furthermore, emerging evidence of genetic association (NDEL1, PCM1, PDE4B) and copy number variation (NDE1) implicate several DISC1-binding partners as risk factors for schizophrenia in their own right. Thus, a picture begins to emerge of DISC1 as a key hub for multiple critical developmental pathways within the brain, disruption of which can lead to a variety of psychiatric illness phenotypes. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 8 | Pharmacogenomics J. 2015 Aug -1: -1 |
| PMID | 26282453 |
| Title | Association studies of genomic variants with treatment response to risperidone, clozapine, quetiapine and chlorpromazine in the Chinese Han population. |
| Abstract | schizophrenia is a widespread mental disease with a prevalence of about 1% in the world population. Continuous long-term treatment is required to maintain social functioning and prevent symptom relapse of schizophrenia patients. However, there are considerable individual differences in response to the antipsychotic drugs. There is a pressing need to identify more drug-response-related markers. But most pharmacogenomics of schizophrenia have typically focused on a few candidate genes in small sample size. In this study, 995 subjects were selected for discovering the drug-response-related markers. A total of 77 single-nucleotide polymorphisms of 25 genes have been investigated for four commonly used antipsychotic drugs in China: risperidone, clozapine, quetiapine, and chlorpromazine. Significant associations with treatment response for several genes, such as CYP2D6, CYP2C19, COMT, ABCB1, DRD3 and HTR2C have been verified in our study. Also, we found several new candidate genes (TNIK, RELN, NOTCH4 and SLC6A2) and combinations (haplotype rs1544325-rs5993883-rs6269-rs4818 in COMT) that are associated with treatment response to the four drugs. Also, multivariate interactions analysis demonstrated the combination of rs6269 in COMT and rs3813929 in HTR2C may work as a predictor to improve the clinical antipsychotic response. So our study is of great significance to improve current knowledge on the pharmacogenomics of schizophrenia, thus promoting the implementation of personalized medicine in schizophrenia.The Pharmacogenomics Journal advance online publication, 18 August 2015; doi:10.1038/tpj.2015.61. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 9 | J. Comp. Neurol. 2015 Sep 523: 1913-24 |
| PMID | 25753355 |
| Title | Organization of TNIK in dendritic spines. |
| Abstract | Tumor necrosis factor receptor-associated factor 2 (TRAF2)- and noncatalytic region of tyrosine kinase (NCK)-interacting kinase (TNIK) has been identified as an interactor in the psychiatric risk factor, Disrupted in schizophrenia 1 (DISC1). As a step toward deciphering its function in the brain, we performed high-resolution light and electron microscopic immunocytochemistry. We demonstrate here that TNIK is expressed in neurons throughout the adult mouse brain. In striatum and cerebral cortex, TNIK concentrates in dendritic spines, especially in the vicinity of the lateral edge of the synapse. Thus, TNIK is highly enriched at a microdomain critical for glutamatergic signaling. |
| SCZ Keywords | schizophrenia, schizophrenic |