Integrating objective gene-brain-behavior markers of psychiatric disorders

J Integr Neurosci. 2007 Mar;6(1):1-34. doi: 10.1142/s0219635207001465.

Abstract

There is little consensus about which objective markers should be used to assess major psychiatric disorders, and predict/evaluate treatment response for these disorders. Clinical practice relies instead on subjective signs and symptoms, such that there is a "translational gap" between research findings and clinical practice. This gap arises from: a) a lack of integrative theoretical models which provide a basis for understanding links between gene-brain-behavior mechanisms and clinical entities; b) the reliance on studying one measure at a time so that linkages between markers are their specificity are not established; and c) the lack of a definitive understanding of what constitutes normative function. Here, we draw on a standardized methodology for acquiring multiple sources of genomic, brain and behavioral data in the same subjects, to propose candidate markers of selected psychiatric disorders: depression, post-traumatic stress disorder, schizophrenia, attention-deficit/hyperactivity disorder and dementia disorders. This methodology has been used to establish a standardized international database which provides a comprehensive framework and the basis for testing hypotheses derived from an integrative theoretical model of the brain. Using this normative base, we present preliminary findings for a number of disorders in relation to the proposed markers. Establishing these objective markers will be the first step towards determining their sensitivity, specificity and treatment prediction in individual patients.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Behavior / physiology*
  • Biomarkers
  • Brain / pathology*
  • Databases, Factual / statistics & numerical data
  • Humans
  • Mental Disorders* / genetics
  • Mental Disorders* / pathology
  • Mental Disorders* / physiopathology
  • Models, Biological*

Substances

  • Biomarkers