Questioning the predictive validity of the amphetamine-induced hyperactivity model for screening mood stabilizing drugs

Anat Lan, Haim Einat

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Animal models are critical for the study of disease mechanisms and the screening of potential novel treatments. In the context of bipolar disorder, amphetamine-induced hyperactivity (AIH) is a frequently used screening model for antimanic effects. Yet, the utility of screening models depends on their predictive (or pharmacological) validity and it is expected that such models will respond to effective treatments. Lithium is the prototypic mood stabilizer but previous data regarding the effects of lithium in the AIH model are not clear and most data comes from studies using acute lithium administration that is not relevant to the therapeutic regimen in patients. To evaluate the pharmacological validity of AIH as a model for mania-like behavior we tested the interaction between chronic oral administration of lithium and amphetamine in ICR (CD-1®) mice and in black Swiss mice. We conducted 4 different experiments where chronic lithium was followed by an acute injection of amphetamine and one experiment where chronic amphetamine was combined with chronic lithium. The results show that amphetamine result in hyperactivity (experiments 1–4) and that lithium has no effects. Moreover, chronic amphetamine (experiment 5) result in sensitization that is not attenuated by lithium. The results clearly show that the predictive validity of the AIH model in ICR or black Swiss mice is problematic and possibly cast doubt on the utilization of the AIH as a screening model for novel mood stabilizers in other strains of mice.

Original languageEnglish
Pages (from-to)109-113
Number of pages5
JournalBehavioural Brain Research
Volume362
DOIs
StatePublished - 19 Apr 2019

Keywords

  • Affective disorders
  • Animal models
  • Bipolar disorder
  • Psychostimulants
  • Screening model
  • Validity

ASJC Scopus subject areas

  • Behavioral Neuroscience

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