Chapter Eight - Opportunities for Bioinformatics in the Classification of Behavior and Psychiatric Disorders

https://doi.org/10.1016/B978-0-12-398323-7.00008-2Get rights and content

Abstract

A bioinformatics approach to behavioral neuroscience provides both unique opportunities and challenges for research on behavior. A major challenge has been to describe, define, and discriminate among abstract behavioral processes, in large part by distinguishing among the biological mechanisms of unique but not entirely discrete, entities of behavior. Understanding the complexity of neurobiology and behavior requires integration of data across diverse biological systems, types of data, and levels of scale. With the perspective and application of bioinformatics, we can uncover the relationships among these systems and take steps forward in realizing the common and distinct bases of psychiatric disease.

Introduction

As the final chapter in this volume on the informatics of behavior, we here, expand on the historical challenges of behavioral neuroscience to define, characterize, and classify psychiatric disorders, and elaborate on ways in which the tools and analyses of bioinformatics are able to advance behavioral investigation (Fig. 8.1). In psychiatry, classification schemes have been largely based on clusters of symptoms of seemingly related overt phenotypes. Unfortunately, for many disorders, the resulting diagnostic criteria provide poor classification with limited implications for research and therapeutics. An alarming reduction in investments in behavioral science by industry is a telling indicator of the challenges that have been faced in psychopharmacology (Brunner, Balci, & Ludvig, 2012) and calls for a pharmacologically relevant nosology have been made (Ban, 2006). Each of the preceding chapters highlights the diverse technologies and methods for multilevel data integration and large-scale data analysis that can be brought to bear in the application of bioinformatics to the intersection of behavioral neuroscience and psychiatry.

Section snippets

Brief historical overview of psychiatric classification systems

Early psychiatric classifications, similar to other “medicalized” disorders, were based on broad aggregates of undesirable and maladaptive characteristics, or “habits.” These systems essentially attributed abnormal behavior to individual responsibility. Classifications and diagnosis of psychiatric and behavioral disorders originally stem from qualitative interpretation of the maladies of individuals, tanamount to “folk psychology” (Slavney, 1992) reliant on the psychiatrists own “theory of

Challenges of understanding psychiatric disorders

Classification of psychiatric and behavioral disorders has been challenging because of the complexity and heterogeneity of the disorders. Ultimately, this results in difficulty naming and identifying discrete entities of behavioral function and presents challenges for research, diagnostics, and therapeutics. These challenges are eloquently described in a recent review of translational studies of alcohol use disorders (Crabbe, 2012).

Transforming the approach to psychiatric classification from

Finding the biological correlates of behavior

The fundamental objective and challenge of biological psychology has been to reliably map behavioral states and traits onto biological mechanisms and processes. Early philosophers could merely ponder the connections between biology, cognition, and behavior from the scant evidence presumably provided by gross injury. These unfortunate explorations eventually led to the recognition that the seat of thought and emotion belonged in the brain, not the heart. Human consciousness was considered far

Data Intensive Methods for Mapping Biological Substrate to Behavioral Function

Genomics and bioinformatics present new technologies and experimental methods for the global mapping of biological substrates onto psychological functions and characteristics. Experimental technologies have rendered it feasible to measure the abundance of tens of thousands of biological molecules, image in situ the expression of transcripts in three-dimensional space, map large numbers of human functional images onto common coordinates, and enable integration of diverse experimental data types

Conclusion: The Promise of Reconstructing Behavior Through Biology

Bioinformatics and complementary advances in high-throughput assessment of brain and behavior have delivered technologies for rapidly identifying and characterizing the role of biological systems in behavioral processes. This has enabled the discovery of new molecular targets for investigation, diagnostics, and therapeutics. While much of this work is in early stages, compelling advances are being made and translation to practice is already occurring. A major opportunity enabled by the

Acknowledgments

The authors gratefully acknowledge helpful suggestions by M. H. Haendel and funding from NIH RO1 AA18776 and The Jackson Laboratory.

References (144)

  • H. Akil et al.

    Challenges and opportunities in mining neuroscience data

    Science

    (2011)
  • J. Amberger et al.

    A new face and new challenges for Online Mendelian Inheritance in Man (OMIM(R))

    Human Mutation

    (2011)
  • American Medico-Psychological Association. (1918). Statistical manual for the use of institutions for the insane. From...
  • American Psychiatric Association

    Diagnostic and statistical manual of mental disorders

    (1952)
  • American Psychiatric Association

    Diagnostic and statistical manual of mental disorders—Revised

    (1987)
  • American Psychiatric Association

    Diagnostic and statistical manual of mental disorders—Text revision

    (2000)
  • R. Arey et al.

    An inhibitor of casein kinase 1 epsilon/delta partially normalizes the manic-like behaviors of the ClockDelta19 mouse

    Behavioural Pharmacology

    (2012)
  • C.P. Austin et al.

    The knockout mouse project

    Nature Genetics

    (2004)
  • E.J. Baker et al.

    GeneWeaver: A web-based system for integrative functional genomics

    Nucleic Acids Research

    (2012)
  • E.J. Baker et al.

    Ontological Discovery Environment: A system for integrating gene-phenotype associations

    Genomics

    (2009)
  • T.A. Ban

    Academic psychiatry and the pharmaceutical industry

    Progress in Neuro-Psychopharmacology & Biological Psychiatry

    (2006)
  • T. Barrett et al.

    Gene expression omnibus: Microarray data storage, submission, retrieval, and analysis

    Methods in Enzymology

    (2006)
  • S. Bauer et al.

    Bayesian ontology querying for accurate and noise-tolerant semantic searches

    Bioinformatics

    (2012)
  • V.M. Bedell et al.

    Lessons from morpholino-based screening in zebrafish

    Briefings in Functional Genomics

    (2011)
  • E.B. Binder et al.

    Emerging methods in the molecular biology of neuropsychiatric disorders

    Handbook of Clinical Neurology

    (2012)
  • Y.A. Blednov et al.

    Behavioral actions of alcohol: Phenotypic relations from multivariate analysis of mutant mouse data

    Genes, Brain, and Behavior

    (2012)
  • D. Boutte et al.

    Association of genetic copy number variations at 11 q14.2 with brain regional volume differences in an alcohol use disorder population

    Alcohol

    (2012)
  • D. Brunner et al.

    Comparative psychology and the grand challenge of drug discovery in psychiatry and neurodegeneration

    Behavioural Processes

    (2012)
  • R.A. Bryant et al.

    Amygdala and ventral anterior cingulate activation predicts treatment response to cognitive behaviour therapy for post-traumatic stress disorder

    Psychological Medicine

    (2008)
  • C. Bult et al.

    A genome end-game: Understanding gene function in the nervous system

    Nature Neuroscience

    (2004)
  • T.A. Carter et al.

    Chipping away at complex behavior: transcriptome/phenotype correlations in the mouse brain

    Physiology & Behavior

    (2001)
  • M. Cerda et al.

    Genetic and environmental influences on psychiatric comorbidity: A systematic review

    Journal of Affective Disorders

    (2010)
  • C.K. Chen et al.

    MouseFinder: Candidate disease genes from mouse phenotype data

    Human Mutation

    (2012)
  • E.J. Chesler et al.

    Genetic correlates of gene expression in recombinant inbred strains: a relational model system to explore neurobehavioral phenotypes

    Neuroinformatics

    (2003)
  • K.J. Clark et al.

    Transgenic zebrafish using transposable elements

    Methods in Cell Biology

    (2011)
  • J.D. Coley

    Emerging differentiation of folkbiology and folkpsychology: Attributions of biological and psychological properties to living things

    Child Development

    (1995)
  • A.N. Coogan et al.

    Chronotherapeutics and psychiatry: Setting the clock to relieve the symptoms

    The World Journal of Biological Psychiatry

    (2011)
  • E.H. Cook

    Autism spectrum disorder: Unbroken mirror neurons; rare copy number variants

    Autism Research

    (2010)
  • L. Cosmides et al.

    Beyond intuition and instinct blindness: Toward an evolutionarily rigorous cognitive science

    Cognition

    (1994)
  • J.C. Crabbe

    Translational behaviour-genetic studies of alcohol: Are we there yet?

    Genes, Brain, and Behavior

    (2012)
  • N. Craddock et al.

    Rethinking psychosis: The disadvantages of a dichotomous classification now outweigh the advantages

    World Psychiatry

    (2007)
  • N. Craddock et al.

    The Kraepelinian dichotomy—Going, going … but still not gone

    The British Journal of Psychiatry

    (2010)
  • P. Danecek et al.

    High levels of RNA-editing site conservation amongst 15 laboratory mouse strains

    Genome Biology

    (2012)
  • R.J. Davidson et al.

    Social influences on neuroplasticity: Stress and interventions to promote well-being

    Nature Neuroscience

    (2012)
  • H.S. Decker

    How Kraepelinian was Kraepelin? How Kraepelinian are the neo-Kraepelinians?–from Emil Kraepelin to DSM-III

    History of Psychiatry

    (2007)
  • S. Edwards et al.

    Experimental psychiatric illness and drug abuse models: From human to animal, an overview

    Methods in Molecular Biology

    (2012)
  • S.C. Ekker et al.

    Zebrafish genome project: Bringing new biology to the vertebrate genome field

    Zebrafish

    (2007)
  • M.A. Enoch et al.

    Neurophysiological and genetic distinctions between pure and comorbid anxiety disorders

    Depression and Anxiety

    (2008)
  • J.P. Feighner et al.

    Diagnostic criteria for use in psychiatric research

    Archives of General Psychiatry

    (1972)
  • X.M. Fernandez-Suarez et al.

    Using the ensembl genome server to browse genomic sequence data

    Current Protocols in Bioinformatics

    (2010)
  • G.S. Fisch

    Animal models and human neuropsychiatric disorders

    Behavior Genetics

    (2007)
  • J. Flint

    Analysis of quantitative trait loci that influence animal behavior

    Journal of Neurobiology

    (2003)
  • A.G. Fraser et al.

    On the impossibility of being expert

    British Medical Journal

    (2010)
  • R. Gerlai

    Zebra fish: An uncharted behavior genetic model

    Behavior Genetics

    (2003)
  • M.A. Geyer et al.

    From antipsychotic to anti-schizophrenia drugs: role of animal models

    Trends in Pharmacological Sciences

    (2012)
  • G.V. Gkoutos et al.

    Ontologies for the description of mouse phenotypes

    Comparative and Functional Genomics

    (2004)
  • D. Goldman et al.

    The genetics of addictions: Uncovering the genes

    Nature Reviews. Genetics

    (2005)
  • D. Goldowitz et al.

    Large-scale mutagenesis of the mouse to understand the genetic bases of nervous system structure and function

    Brain Research. Molecular Brain Research

    (2004)
  • I.H. Gotlib et al.

    Bringing genetics back to psychiatric endophenotypes

    Biological Psychiatry

    (2012)
  • I.I. Gottesman et al.

    Genetic theorizing and schizophrenia

    The British Journal of Psychiatry

    (1973)

    • Cited by (3)

    • Tools for exploring mouse models of human disease

      2016, Drug Discovery Today: Disease Models
      Citation Excerpt :

      Challenges still exist to exploit the full potential of mouse for disease models, particularly in certain disease areas [35]. A recent review highlighted the challenges in the field of neuropsychiatric diseases [36] e.g. it is easy to define metabolic phenotypes such as hypoglycaemia in human and mouse by reference to the blood concentration of the same biochemical entity (glucose), but defining similar mouse phenotypes to psychiatric abnormalities such as psychosis involves considerable effort [37]. In addition to the informatics challenges, a culture shift is still needed in both the research and clinical communities to encourage collection of higher quality phenotype data.

    • Animal models of bipolar mania: The past, present and future

      2016, Neuroscience
      Citation Excerpt :

      Face validity is typically considered to be the requirement for reasonable ‘symptomatic’ homology or overlap with diagnostic criteria. This could pose a problem when diagnostic criteria are poorly defined or based solely on phenomenology (Chesler and Logan, 2012). Another issue arises when adhering to strict definitions of face validity—excessive anthropomorphization of rodent behavior.

    • GeneWeaver: finding consilience in heterogeneous cross-species functional genomics data

      2015, Mammalian Genome
    View full text
    Copyright © 2012 Elsevier Inc. All rights reserved.