- 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 i 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 th 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 wll 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 bio mathematical 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 - www.nami.org), 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)
Project #
Application #
Study Section
Special Panel for Genomics (SPLC)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
James J Peters VA Medical Center
United States
Zip Code
McKenzie, Andrew T; Wang, Minghui; Hauberg, Mads E et al. (2018) Brain Cell Type Specific Gene Expression and Co-expression Network Architectures. Sci Rep 8:8868
Bryois, Julien; Garrett, Melanie E; Song, Lingyun et al. (2018) Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun 9:3121
Girdhar, Kiran; Hoffman, Gabriel E; Jiang, Yan et al. (2018) Cell-specific histone modification maps in the human frontal lobe link schizophrenia risk to the neuronal epigenome. Nat Neurosci 21:1126-1136
Hauberg, Mads E; Fullard, John F; Zhu, Lingxue et al. (2018) Differential activity of transcribed enhancers in the prefrontal cortex of 537 cases with schizophrenia and controls. Mol Psychiatry :
Dobbyn, Amanda; Huckins, Laura M; Boocock, James et al. (2018) Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS. Am J Hum Genet 102:1169-1184
Vora, Anvi K; Fisher, Amanda M; New, Antonia S et al. (2018) Dimensional Traits of Schizotypy Associated With Glycine Receptor GLRA1 Polymorphism: An Exploratory Candidate-Gene Association Study. J Pers Disord 32:421-432
Giambartolomei, Claudia; Zhenli Liu, Jimmy; Zhang, Wen et al. (2018) A Bayesian framework for multiple trait colocalization from summary association statistics. Bioinformatics 34:2538-2545
Fullard, John F; Hauberg, Mads E; Bendl, Jaroslav et al. (2018) An atlas of chromatin accessibility in the adult human brain. Genome Res 28:1243-1252
Koumakis, Lefteris; Roussos, Panos; Potamias, George (2017) minepath.org: a free interactive pathway analysis web server. Nucleic Acids Res 45:W116-W121
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

Showing the most recent 10 out of 39 publications