Distinct Behavioral Profiles and Neuronal Correlates of Heroin Vulnerability Versus Resiliency in a Multi-Symptomatic Model of Heroin Use Disorder in Rats.

Abstract

Objective: The behavioral and diagnostic heterogeneity within the opioid use disorder (OUD) diagnosis is not readily captured in current animal models, limiting the translational relevance of the mechanistic research that is conducted in experimental animals. The authors hypothesized that a nonlinear clustering of OUD-like behavioral traits would capture population heterogeneity and yield subpopulations of OUD vulnerable rats with distinct behavioral and neurocircuit profiles.

Methods: Over 900 male and female heterogeneous stock rats, a line capturing genetic and behavioral heterogeneity present in humans, were assessed for several measures of heroin use and rewarded and non-rewarded seeking behaviors. A nonlinear stochastic block model clustering analysis was used to assign rats to OUD vulnerable, intermediate, and resilient clusters. Additional behavioral tests and circuit analyses using c-fos protein activation were conducted on the vulnerable and resilient subpopulations.

Results: OUD vulnerable rats exhibited greater heroin taking and seeking behaviors relative to those in the intermediate and resilient clusters. Akin to human OUD diagnosis, further vulnerable rat subclustering revealed subpopulations with different combinations of behavioral traits, including sex differences. Lastly, heroin cue-induced neuronal patterns of circuit activation differed between resilient and vulnerable phenotypes. Behavioral sex differences were recapitulated in patterns of circuitry activation, including preferential engagement of extended amygdala stress circuitry in males and cortico-striatal drug cue-seeking circuitry in females.

Conclusion: Using a nonlinear clustering approach in rats, the analysis captured behavioral diagnostic heterogeneity reflective of human OUD diagnosis. OUD vulnerability and resiliency were associated with distinct neuronal activation patterns, posing this approach as a translational tool in assessing neurobiological mechanisms underpinning OUD.