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Genome-Wide Associations of Schizophrenia Studied with Computer Simulation

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Hippocampal Microcircuits

Part of the book series: Springer Series in Computational Neuroscience ((NEUROSCI))

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Abstract

A recent genome-wide association study (GWAS) demonstrated 108 association loci that are associated with development of schizophrenia (Schizophrenia Working Group, 2014). These are just the sites that can be implicated using the statistical power conferred by current data. It is expected that many more sites will be uncovered as new studies use larger numbers of cases and controls. The number of likely associated loci is uncertain, but one estimate suggests it may be in the thousands (International Schizophrenia Consortium). For any given patient, only a small subset of these locations will show mutations. The clinical pathway hypothesis for polygenic diseases predicts that the various sites of damage associated with a given disease reflect sets of mutationally damaged genes that together produce the disease (we will use the term clinical pathway so as to distinguish it from the traditional definition of a pathway as a biochemical sequence) (Sullivan, 2012). What is a clinical pathway? This term remains weakly defined and will differ between diseases and even within a single disease. For example, multiple clinical pathways in schizophrenia may well involve (1) developmental sequences, (2) intracellular cascade sequences such as second-messenger cascades in neurons, (3) genetic activation sequences or RNA transcriptional control sequences, (4) immunological and scavenging pathways (e.g., synapse and cell elimination in schizophrenia Sullivan 2012), and (5) pathways of dynamical physiological interactions that together provide physiological activity.

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Author information

Authors and Affiliations

  1. Department of Neuroscience, Brown University, Providence, RI, USA

    Samuel A. Neymotin

  2. Institute for Psychiatric Research, Orangeburg, NY, USA

    Nathan S. Kline

  3. Yale University, New Haven, CT, USA

    Mohamed A. Sherif

  4. VA Connecticut Healthcare System, West Haven, CT, USA

    Mohamed A. Sherif

  5. Department Physiology and Pharmacology, SUNY Downstate, Brooklyn, NY, USA

    Mohamed A. Sherif, Jeeyune Q. Jung, Joseph J. Kabariti & William W. Lytton

  6. Department Neurology, Kings County Hospital Center, Brooklyn, NY, USA

    William W. Lytton

Authors
  1. Samuel A. Neymotin
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  2. Nathan S. Kline
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  3. Mohamed A. Sherif
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  4. Jeeyune Q. Jung
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  5. Joseph J. Kabariti
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  6. William W. Lytton
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Corresponding author

Correspondence to Samuel A. Neymotin .

Editor information

Editors and Affiliations

  1. School of Computer Science, University of Lincoln, Lincoln, UK

    Vassilis Cutsuridis

  2. School of Natural Sciences, Department of Computing Science and Mathematics, University of Stirling, Stirling, UK

    Bruce P. Graham

  3. Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK

    Stuart Cobb

  4. Institute for Integrative Neuroanatomy, Charité – Universitätsmedizin Berlin, Berlin, Germany

    Imre Vida

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Neymotin, S.A., Kline, N.S., Sherif, M.A., Jung, J.Q., Kabariti, J.J., Lytton, W.W. (2018). Genome-Wide Associations of Schizophrenia Studied with Computer Simulation. In: Cutsuridis, V., Graham, B., Cobb, S., Vida, I. (eds) Hippocampal Microcircuits. Springer Series in Computational Neuroscience. Springer, Cham. https://doi.org/10.1007/978-3-319-99103-0_21

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