In search of a depressed mouse: utility of models for studying depression-related behavior in genetically modified mice

Mol Psychiatry. 2004 Apr;9(4):326-57. doi: 10.1038/


The ability to modify mice genetically has been one of the major breakthroughs in modern medical science affecting every discipline including psychiatry. It is hoped that the application of such technologies will result in the identification of novel targets for the treatment of diseases such as depression and to gain a better understanding of the molecular pathophysiological mechanisms that are regulated by current clinically effective antidepressant medications. The advent of these tools has resulted in the need to adopt, refine and develop mouse-specific models for analyses of depression-like behavior or behavioral patterns modulated by antidepressants. In this review, we will focus on the utility of current models (eg forced swim test, tail suspension test, olfactory bulbectomy, learned helplessness, chronic mild stress, drug-withdrawal-induced anhedonia) and research strategies aimed at investigating novel targets relevant to depression in the mouse. We will focus on key questions that are considered relevant for examining the utility of such models. Further, we describe other avenues of research that may give clues as to whether indeed a genetically modified animal has alterations relevant to clinical depression. We suggest that it is prudent and most appropriate to use convergent tests that draw on different antidepressant-related endophenotypes, and complimentary physiological analyses in order to provide a program of information concerning whether a given phenotype is functionally relevant to depression-related pathology.

Publication types

  • Research Support, U.S. Gov't, P.H.S.
  • Review

MeSH terms

  • Animals
  • Animals, Genetically Modified / genetics*
  • Behavior, Animal*
  • Depressive Disorder / genetics
  • Depressive Disorder / physiopathology*
  • Disease Models, Animal*
  • Mice
  • Mice, Mutant Strains / genetics*
  • Reproducibility of Results
  • Sensitivity and Specificity