| 1 | PLoS Comput. Biol. 2012 -1 8: e1002587 |
|---|---|
| PMID | 22792057 |
| Title | Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia. |
| Abstract | With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P(meta)<1 × 10??, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. |
| SCZ Keywords | schizophrenia |
| 2 | Psychiatry Res 2013 Jun 208: 97-8 |
| PMID | 23036492 |
| Title | Lack of genetic association of the HLA-DQA1(?)0501 variant with schizophrenia in a Chinese population. |
| Abstract | -1 |
| SCZ Keywords | schizophrenia |
| 3 | Biol. Psychiatry 2013 Nov 74: 696-705 |
| PMID | 23664640 |
| Title | Prefrontal cortical dysfunction after overexpression of histone deacetylase 1. |
| Abstract | Postmortem brain studies have shown that HDAC1-a lysine deacetylase with broad activity against histones and nonhistone proteins-is frequently expressed at increased levels in prefrontal cortex (PFC) of subjects diagnosed with schizophrenia and related disease. However, it remains unclear whether upregulated expression of Hdac1 in the PFC could affect cognition and behavior. Using adeno-associated virus, an Hdac1 transgene was expressed in young adult mouse PFC, followed by behavioral assays for working and long-term memory, repetitive activity, and response to novelty. Prefrontal cortex transcriptomes were profiled by microarray. Antipsychotic drug effects were explored in mice treated for 21 days with haloperidol or clozapine. Hdac1 overexpression in PFC neurons and astrocytes resulted in robust impairments in working memory, increased repetitive behaviors, and abnormal locomotor response profiles in novel environments. Long-term memory remained intact. Over 300 transcripts showed subtle but significant changes in Hdac1-overexpressing PFC. Major histocompatibility complex class II (MHC II)-related transcripts, including HLA-DQA1/H2-Aa, HLA-DQB1/H2-Ab1, and HLA-DRB1/H2-Eb1, located in the chromosome 6p21.3-22.1 schizophrenia and bipolar disorder risk locus, were among the subset of genes with a more robust (>1.5-fold) downregulation in expression. Hdac1 levels declined during the course of normal PFC development. Antipsychotic drug treatment, including the atypical clozapine, did not affect Hdac1 levels in PFC but induced expression of multiple MHC II transcripts. Excessive HDAC1 activity, due to developmental defects or other factors, is associated with behavioral alterations and dysregulated expression of MHC II and other gene transcripts in the PFC. |
| SCZ Keywords | schizophrenia |
| 4 | Psychol Med 2014 Jul 44: 2177-87 |
| PMID | 24284030 |
| Title | The one and the many: effects of the cell adhesion molecule pathway on neuropsychological function in psychosis. |
| Abstract | Genetic studies of single gene variants have been criticized as providing a simplistic characterization of the genetic basis of illness risk that ignores the effects of other variants within the same biological pathways. Of candidate biological pathways for schizophrenia (SZ), the cell adhesion molecule (CAM) pathway has repeatedly been linked to both psychosis and neurocognitive dysfunction. Here we tested, using risk allele scores derived from the schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ), whether alleles within the CAM pathway were correlated with poorer neuropsychological function in patients. In total, 424 patients with psychosis were assessed in areas of cognitive ability typically found to be impaired in SZ: intelligence quotient, memory, working memory and attentional control. CAM pathway genes were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Alleles within these genes identified as significantly associated with SZ risk in the PGC-SCZ were then used to calculate a CAM pathway-based polygenic risk allele score for each patient and these scores were tested for association with cognitive ability. Increased CAM pathway polygenic risk scores were significantly associated with poorer performance on measures of memory and attention, explaining 1-3% of variation on these measures. Notably, the most strongly associated single nucleotide polymorphism (SNP) in the CAM pathway (rs9272105 within HLA-DQA1) explained a similar amount of variance in attentional control, but not memory, as the polygenic risk analysis. These data support a role for the CAM pathway in cognitive function, both at the level of individual SNPs and the wider pathway. In so doing these data highlight the value of pathway-based polygenic risk score studies as well as single gene studies for understanding SZ-associated deficits in cognition. |
| SCZ Keywords | schizophrenia |
| 5 | Am. J. Med. Genet. B Neuropsychiatr. Genet. 2016 Mar 171: 181-202 |
| PMID | 26462458 |
| Title | Currently recognized genes for schizophrenia: High-resolution chromosome ideogram representation. |
| Abstract | A large body of genetic data from schizophrenia-related research has identified an assortment of genes and disturbed pathways supporting involvement of complex genetic components for schizophrenia spectrum and other psychotic disorders. Advances in genetic technology and expanding studies with searchable genomic databases have led to multiple published reports, allowing us to compile a master list of known, clinically relevant, or susceptibility genes contributing to schizophrenia. We searched key words related to schizophrenia and genetics from peer-reviewed medical literature sources, authoritative public access psychiatric websites and genomic databases dedicated to gene discovery and characterization of schizophrenia. Our list of 560 genes were arranged in alphabetical order in tabular form with gene symbols placed on high-resolution human chromosome ideograms. Genome wide pathway analysis using GeneAnalytics was carried out on the resulting list of genes to assess the underlying genetic architecture for schizophrenia. Recognized genes of clinical relevance, susceptibility or causation impact a broad range of biological pathways and mechanisms including ion channels (e.g., CACNA1B, CACNA1C, CACNA1H), metabolism (e.g., CYP1A2, CYP2C19, CYP2D6), multiple targets of neurotransmitter pathways impacting dopamine, GABA, glutamate, and serotonin function, brain development (e.g., NRG1, RELN), signaling peptides (e.g., PIK3CA, PIK4CA) and immune function (e.g., HLA-DRB1, HLA-DQA1) and interleukins (e.g., IL1A, IL10, IL6). This summary will enable clinical and laboratory geneticists, genetic counselors, and other clinicians to access convenient pictorial images of the distribution and location of contributing genes to inform diagnosis and gene-based treatment as well as provide risk estimates for genetic counseling of families with affected relatives. © 2015 Wiley Periodicals, Inc. |
| SCZ Keywords | schizophrenia |