Despite the prevalence of schizophrenia and its considerable impact, knowledge about its pathophysiology is rudimentary. Given its profound impact on the wellbeing of our Veterans, there is an urgent need to discover novel molecular targets, so that better diagnostic tests, treatments, and preventive measures can be attained. Although the risk of schizophrenia is known to be increased by certain genetic factors, studies that have examined its genetic basis have up-to-now provided only limited insight. Our proposal aims to better understand the genetic factors that carry risk for schizophrenia and the mechanisms through which they act. Recent large-scale genome-wide association studies in schizophrenia -- i.e., studies that screen the whole genome in patients vs. controls -- have identified hundreds of susceptibility loci. However, because the majority of these loci are located within non-coding regions -- i.e., regions that do not express any gene products (i.e., mRNA transcripts) -- the causal variants and the mechanism through which they increase the risk for the disease remains unclear. While in the past these genomic regions were characterized as """"""""junk DNA,"""""""" recent findings provide strong evidence that they play an important role in regulating transcription -- the process in which mRNA transcripts are synthesized using genes as templates. More precisely, specific proteins, named transcription factors, bind to these """"""""junk DNA"""""""" regions and facilitate or inhibit transcription. The accessibility of the regulatory regions is controlled by multiple biological modifications of histones -- the proteins that wrap genomic DNA and keep it in a compacted state within each cell. The biochemical modifications of histones provide the mechanism that acts as a switch which """"""""opens"""""""" or """"""""closes"""""""" the binding of transcription factors to the regulatory elements, and subsequently controls the rate and quantity of transcription. Because the majority of genetic risk variants for schizophrenia are located in the """"""""junk DNA,"""""""" and because the abnormalities in transcription are described by numerous human postmortem studies in schizophrenia, in this proposal we aim to precisely map the regulatory regions, to identify the schizophrenia risk genetic variants that are localized within these regions, and to define the affected transcripts. We are interested in studying schizophrenia;therefore, the analysis needs to be performed in tissues that present abnormalities in this condition. For this reason, we will use postmortem human brain specimens and will focus on two brain regions that have consistently showed abnormalities in schizophrenia (superior temporal gyrus and dorsolateral prefrontal cortex). Because the brain tissue contains different cell types, and because the histone modifications that affect regulatory regions are specific for each cell type, we will use an advanced molecular technique that will allow us to separate neurons from other cells in the brain. Next, we will perform genome scans in neuronal cells and identify the genomic regions that have a significant role in regulating transcription, as well as will determine if these regulatory regions are present in """"""""open"""""""" or """"""""closed"""""""" states. This approach will generate an annotation map that can be used to identify the schizophrenia risk genetic variants that are located within the regulatory regions, thus affecting binding of transcription factors and subsequently transcription. Specific transcripts that will be detected by this approach will be further validated in in vitro cell culture models and gene expression human postmortem studies in schizophrenia. Finally, by using advanced biomathematical models, we will examine whether or not these genes cluster together in """"""""gene networks"""""""", which are significantly affected in schizophrenia. If they do, we will have gained important knowledge of targeting a specific group of genes and specific molecular pathways. This would be very promising for the development of drug treatments which are more efficacious than those currently in use today.

Public Health Relevance

The VHA Independent Budget Report for FY2003 listed 104,593 Veterans being treated for schizophrenia (source -, accounting for nearly 12% of the VA's total healthcare costs. This Merit proposal seeks to elucidate some of the neurobiological mechanisms through which genetic risk factors for schizophrenia increase the risk for the disease. We propose to integrate multiple high-dimensional data (genomics, transcriptomics and epigenomics) using advanced bio statistical models and gene network approaches, followed by validation of significant findings in in vitro and human postmortem gene expression studies. The proposed studies will identify genes that carry a high probability for causality in schizophrenia and identiy some of the mechanisms through which they act. This holds the potential for direct translational and clinical applications of which may reinvigorate stalled drug development that can improve the mental health of our Veterans.

National Institute of Health (NIH)
Veterans Affairs (VA)
Non-HHS Research Projects (I01)
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Special Emphasis - Research on Clinical Application of Genetics (SPLC)
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James J Peters VA Medical Center
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Egervari, Gabor; Landry, Joseph; Callens, James et al. (2017) Striatal H3K27 Acetylation Linked to Glutamatergic Gene Dysregulation in Human Heroin Abusers Holds Promise as Therapeutic Target. Biol Psychiatry 81:585-594
Jiang, Yan; Loh, Yong-Hwee Eddie; Rajarajan, Prashanth et al. (2017) The methyltransferase SETDB1 regulates a large neuron-specific topological chromatin domain. Nat Genet 49:1239-1250
Halene, Tobias B; Kozlenkov, Alexey; Jiang, Yan et al. (2016) NeuN+ neuronal nuclei in non-human primate prefrontal cortex and subcortical white matter after clozapine exposure. Schizophr Res 170:235-44
Kozlenkov, Alexey; Wang, Minghui; Roussos, Panos et al. (2016) Substantial DNA methylation differences between two major neuronal subtypes in human brain. Nucleic Acids Res 44:2593-612
Wang, Minghui; Roussos, Panos; McKenzie, Andrew et al. (2016) Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer's disease. Genome Med 8:104
Roussos, Panos; Guennewig, Boris; Kaczorowski, Dominik C et al. (2016) Activity-Dependent Changes in Gene Expression in Schizophrenia Human-Induced Pluripotent Stem Cell Neurons. JAMA Psychiatry 73:1180-1188
Franzén, Oscar; Ermel, Raili; Cohain, Ariella et al. (2016) Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases. Science 353:827-30
Watson, Corey T; Roussos, Panos; Garg, Paras et al. (2016) Genome-wide DNA methylation profiling in the superior temporal gyrus reveals epigenetic signatures associated with Alzheimer's disease. Genome Med 8:5
Fullard, John F; Halene, Tobias B; Giambartolomei, Claudia et al. (2016) Understanding the genetic liability to schizophrenia through the neuroepigenome. Schizophr Res 177:115-124
Fromer, Menachem; Roussos, Panos; Sieberts, Solveig K et al. (2016) Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci 19:1442-1453

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