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Towards understanding the schizophrenia code: An expanded convergent functional genomics approach

Authors

  • H. Le-Niculescu,

    1. Laboratory of Neurophenomics, Indiana University School of Medicine, Indianapolis, Indiana
    2. INBRAIN, Indiana University School of Medicine, Indianapolis, Indiana
    3. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, Indiana
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  • Y. Balaraman,

    1. Laboratory of Neurophenomics, Indiana University School of Medicine, Indianapolis, Indiana
    2. INBRAIN, Indiana University School of Medicine, Indianapolis, Indiana
    3. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, Indiana
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  • S. Patel,

    1. Laboratory of Neurophenomics, Indiana University School of Medicine, Indianapolis, Indiana
    2. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, Indiana
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  • J. Tan,

    1. Laboratory of Neurophenomics, Indiana University School of Medicine, Indianapolis, Indiana
    2. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, Indiana
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  • K. Sidhu,

    1. Laboratory of Neurophenomics, Indiana University School of Medicine, Indianapolis, Indiana
    2. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, Indiana
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  • R.E. Jerome,

    1. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
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  • H.J. Edenberg,

    1. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
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  • R. Kuczenski,

    1. Department of Psychiatry, UC San Diego, La Jolla, California
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  • M.A. Geyer,

    1. Department of Psychiatry, UC San Diego, La Jolla, California
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  • J.I. Nurnberger Jr,

    1. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, Indiana
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  • S.V. Faraone,

    1. Department of Psychiatry, SUNY Upstate Medical University, Syracuse, New York
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  • M.T. Tsuang,

    1. Department of Psychiatry, UC San Diego, La Jolla, California
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  • A.B. Niculescu

    Corresponding author
    1. Laboratory of Neurophenomics, Indiana University School of Medicine, Indianapolis, Indiana
    2. INBRAIN, Indiana University School of Medicine, Indianapolis, Indiana
    3. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, Indiana
    • Institute of Psychiatric Research, 791 Union Drive, Indianapolis, IN 46202.
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  • Please cite this article as follows: Le-Niculescu H, Balaraman Y, Patel S, Tan J, Sidhu K, Jerome RE, Edenberg HJ, Kuczenski R, Geyer MA, Nurnberger JI Jr, Faraone SV, Tsuang MT, Niculescu AB. 2006. Towards Understanding The Schizophrenia Code: An Expanded Convergent Functional Genomics Approach. Am J Med Genet Part B 144B:129–158.

Abstract

Identifying genes for schizophrenia through classical genetic approaches has proven arduous. Here, we present a comprehensive convergent analysis that translationally integrates brain gene expression data from a relevant pharmacogenomic mouse model (involving treatments with a psychomimetic agent—phencyclidine (PCP), and an anti-psychotic—clozapine), with human genetic linkage data and human postmortem brain data, as a Bayesian strategy of cross validating findings. Topping the list of candidate genes, we have three genes involved in GABA neurotransmission (GABRA1, GABBR1, and GAD2), one gene involved in glutamate neurotransmission (GRIA2), one gene involved in neuropeptide signaling (TAC1), two genes involved in synaptic function (SYN2 and KCNJ4), six genes involved in myelin/glial function (CNP, MAL, MBP, PLP1, MOBP and GFAP), and one gene involved in lipid metabolism (LPL). These data suggest that schizophrenia is primarily a disorder of brain functional and structural connectivity, with GABA neurotransmission playing a prominent role. These findings may explain the EEG gamma band abnormalities detected in schizophrenia. The analysis also revealed other high probability candidates genes (neurotransmitter signaling, other structural proteins, ion channels, signal transduction, regulatory enzymes, neuronal migration/neurite outgrowth, clock genes, transcription factors, RNA regulatory genes), pathways and mechanisms of likely importance in pathophysiology. Some of the pathways identified suggest possible avenues for augmentation pharmacotherapy of schizophrenia with other existing agents, such as benzodiazepines, anticonvulsants and lipid modulating agents. Other pathways are new potential targets for drug development. Lastly, a comparison with our earlier work on bipolar disorder illuminates the significant molecular overlap between schizophrenia and bipolar disorder. © 2007 Wiley-Liss, Inc.

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