Large-scale characterization of cocaine addiction-like behaviors reveals that escalation of intake, aversion-resistant responding, and breaking-points are highly correlated measures of the same construct

Abstract

Twin studies suggest that approximately 50% of the vulnerability to cocaine use disorder is determined by genetic factors, but genome-wide association studies (GWAS) in humans have only begun to identify specific genes that confer this risk. The identification of a set of single nucleotide polymorphisms (SNPs) associated with increased vulnerability to develop compulsive cocaine use represents a major goal for understanding of the genetic risk factors to cocaine use disorder and facilitating the identification of novel druggable targets. Here we characterized addiction-like behaviors in heterogeneous stock (HS) rats, a unique outbred strain of rats characterized by high genetic variability that has been developed to mimic genetic variability in humans. HS rats were allowed to self-administer cocaine 6h/daily for 14 days. Animals were also screened for compulsive cocaine use, using progressive-ratio (PR) and responding despite adverse consequences (contingent foot shocks). To minimize cohort-specific effects, we used large cohorts (n = 46-60) and normalized the level of responding within cohorts using a Z-score. To take advantage of the three behaviors related to compulsive intake and further identify subjects that are consistently vulnerable vs. resilient to compulsive cocaine use we computed an Addiction index by averaging normalized responding (Z-scores) for the three behavioral tests. Results showed high individual variability between vulnerable and resilient rats that is likely to facilitate detection of gene variants associated with vulnerable vs. resilient individuals. Such data will have considerable translational value for designing pharmacogenetic studies in humans.

Dopamine Circuit Mechanisms of Addiction-Like Behaviors

“…This represents a challenge for animal models, where the comparatively limited genetic diversity of research subjects may elide some variability factors. Recent work has made use of “heterogeneous stock” rodents – the product of multiple strain crossings - to increase genetic diversity and investigate individual differences in addiction-like behavior and reward learning in the context of drug use ( Hughson et al, 2019 ; de Guglielmo et al, 2021 ; King et al, 2021 ; Sedighim et al, 2021 ). One such study identified a relationship between gut bacterial content and behavioral features of impulsivity and attention ( Peterson et al, 2020 ).…”

Cocaine addiction-like behaviors are associated with long-term changes in gene regulation, energy metabolism, and GABAergic inhibition within the amygdala

“…Rats were classified as having a low or high AI by a median split. AI was computed by averaging normalized measurements (z-scores) for the three behavioral tests (escalation, motivation, resistance to punishment) 126 . The z-scores are calculated as follows 𝑧 = 𝑥−𝜇 𝜎 , where 𝑥 is the raw value, 𝜇 is the mean of the cohort, and 𝜎 is the standard deviation of the cohort.…”

High quality, high throughput, and low-cost simultaneous video recording of 60 animals in operant chambers using PiRATeMC

“…The use of animal models in operant self-administration paradigms is critical to the advancements in the characterization of addiction behaviors, the mapping of neurobiological mechanisms, and their translation into human treatments and interventions (Spanagel, 2017). Animal models of drug self-administration typically use variables such as the number of infusions, active lever press, resistance to punishment, or breaking point to measure psychological construct such as “craving”, “motivation”, “escalation”, and “vulnerability” (Belin et al 2009; Guglielmo et al 2023, preprint, doi:10.1101/2021.07.22.453410; Kallupi et al 2022, preprint, doi:10.1101/2022.07.26.501618). However, these simple behavioral measures are limited in their capability to provide in-depth information about the organization and the complexity of behavior during an operant session.…”