| 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 | PLoS ONE 2011 -1 6: e23356 |
| PMID | 21915259 |
| Title | RNA-Seq of human neurons derived from iPS cells reveals candidate long non-coding RNAs involved in neurogenesis and neuropsychiatric disorders. |
| Abstract | Genome-wide expression analysis using next generation sequencing (RNA-Seq) provides an opportunity for in-depth molecular profiling of fundamental biological processes, such as cellular differentiation and malignant transformation. Differentiating human neurons derived from induced pluripotent stem cells (iPSCs) provide an ideal system for RNA-Seq since defective neurogenesis caused by abnormalities in transcription factors, DNA methylation, and chromatin modifiers lie at the heart of some neuropsychiatric disorders. As a preliminary step towards applying next generation sequencing using neurons derived from patient-specific iPSCs, we have carried out an RNA-Seq analysis on control human neurons. Dramatic changes in the expression of coding genes, long non-coding RNAs (lncRNAs), pseudogenes, and splice isoforms were seen during the transition from pluripotent stem cells to early differentiating neurons. A number of genes that undergo radical changes in expression during this transition include candidates for schizophrenia (SZ), bipolar disorder (BD) and autism spectrum disorders (ASD) that function as transcription factors and chromatin modifiers, such as POU3F2 and ZNF804A, and genes coding for cell adhesion proteins implicated in these conditions including NRXN1 and NLGN1. In addition, a number of novel lncRNAs were found to undergo dramatic changes in expression, one of which is HOTAIRM1, a regulator of several HOXA genes during myelopoiesis. The increase we observed in differentiating neurons suggests a role in neurogenesis as well. Finally, several lncRNAs that map near SNPs associated with SZ in genome wide association studies also increase during neuronal differentiation, suggesting that these novel transcripts may be abnormally regulated in a subgroup of patients. |
| SCZ Keywords | schizophrenia, schizophrenic |