Title

Heritable variation in locomotion, reward sensitivity and impulsive behaviors in a genetically diverse inbred mouse panel.

Document Type

Article

Publication Date

11-2021

Publication Title

Genes, brain, and behavior

Keywords

JMG

JAX Source

Genes Brain Behav 2021 Nov; 20(8):e12773

Volume

20

Issue

8

First Page

12773

Last Page

12773

ISSN

1601-183X

PMID

34672075

DOI

https://doi.org/10.1111/gbb.12773

Grant

DA039841

Abstract

Drugs of abuse, including alcohol and stimulants like cocaine, produce effects that are subject to individual variability, and genetic variation accounts for at least a portion of those differences. Notably, research in both animal models and human subjects point toward reward sensitivity and impulsivity as being trait characteristics that predict relatively greater positive subjective responses to stimulant drugs. Here we describe use of the eight collaborative cross (CC) founder strains and 38 (reversal learning) or 10 (all other tests) CC strains to examine the heritability of reward sensitivity and impulsivity traits, as well as genetic correlations between these measures and existing addiction-related phenotypes. Strains were all tested for activity in an open field and reward sensitivity (intake of chocolate BOOST®). Mice were then divided into two counterbalanced groups and underwent reversal learning (impulsive action and waiting impulsivity) or delay discounting (impulsive choice). CC and founder mice show significant heritability for impulsive action, impulsive choice, waiting impulsivity, locomotor activity, and reward sensitivity, with each impulsive phenotype determined to be non-correlating, independent traits. This research was conducted within the broader, inter-laboratory effort of the Center for Systems Neurogenetics of Addiction (CSNA) to characterize CC and DO mice for multiple, cocaine abuse related traits. These data will facilitate the discovery of genetic correlations between predictive traits, which will then guide discovery of genes and genetic variants that contribute to addictive behaviors.

Comments

We gratefully acknowledge the technical assistance of Ms. Barbara Force and the contribution of the Computational Sciences Service at The Jackson Laboratory for expert assistance with the work described in this publication.

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