Abstract
Individual differences in vulnerability to addiction have been widely studied through factor analysis (FA) in humans, a statistical method that identifies “latent” variables (variables that are not measured directly) that reflect the common variance among a larger number of observed measures. Despite its widespread application in behavioral genetics, FA has not been used in preclinical opioid addiction research. The current study used FA to examine the latent factor structure of four measures of i.v. morphine self-administration (MSA) in rats (i.e., acquisition, demand elasticity, morphine/cue- and stress/cue-induced reinstatement). All four MSA measures are generally assumed in the preclinical literature to reflect “addiction vulnerability,” and individual differences in multiple measures of abuse liability are best accounted for by a single latent factor in some human studies. A one-factor model was therefore fitted to the data. Two different regularized FAs indicated that a one-factor model fit our data well. Acquisition, elasticity of demand and morphine/cue-induced reinstatement loaded significantly onto a single latent factor while stress/cue-induced reinstatement did not. Consistent with findings from some human studies, our results indicated a common drug “addiction” factor underlying several measures of opioid SA. However, stress/cue-induced reinstatement loaded poorly onto this factor, suggesting that unique mechanisms mediate individual differences in this vs. other MSA measures. Further establishing FA approaches in drug SA and in preclinical neuropsychopathology more broadly will provide more reliable, clinically relevant core factors underlying disease vulnerability in animal models for further genetic analyses.
Highlights
Individual differences in susceptibility to addiction in humans have been studied widely through factor analysis (FA), a statistical method that identifies “latent” variables that reflect the common variance among a larger number of observed measures
Increases in fixed ratio (FR) requirement resulted in a progressive reduction in morphine consumption that was welldescribed by an exponential demand function (R2 = 0.84) (Figure 2B)
Our data demonstrated that a single latent addiction factor fits four distinct morphine self-administration (MSA) measures
Summary
Individual differences in susceptibility to addiction in humans have been studied widely through factor analysis (FA), a statistical method that identifies “latent” variables (variables that are not measured directly) that reflect the common variance among a larger number of observed measures. [1], FA is Individual Differences in Opioid Self-Administration a theory-driven statistical method that uses well-defined indicators from a common behavioral domain [2]. Factor analytic approaches have been widely used in the clinical literature to explore the factor structure underlying various addiction measures Such structures may have both vertical and horizontal dimensions. The horizontal dimension represents the degree of similarity between factors within a single level of the hierarchy [8] Elaboration of such two-dimensional factor structure may yield one or more robust endophenotypes that can be used to identify genomic loci associated with core features of substance use disorders [9, 10]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
