Elucidation of the mechanism of dopamine signaling to ERK that underlies plasticity in dopamine D1 receptor-expressing neurons leading to acquired cocaine preference is incomplete. NCS-Rapgef2 is a novel cAMP effector, expressed in neuronal and endocrine cells in adult mammals, that is required for D1 dopamine receptor-dependent ERK phosphorylation in mouse brain. In this report, we studied the effects of abrogating NCS-Rapgef2 expression on cAMP-dependent ERKfiEgr-1/Zif268 signaling in cultured neuroendocrine cells; in D1 medium spiny neurons of NAc slices; and in either male or female mouse brain in a region-specific manner. NCS-Rapgef2 gene deletion in the NAc in adult mice, using adeno-associated virus-mediated expression of cre recombinase, eliminated cocaine-induced ERK phosphorylation and Egr-1/Zif268 upregulation in D1-medium spiny neurons and cocaine-induced behaviors, including locomotor sensitization and conditioned place preference. Abrogation of NCS-Rapgef2 gene expression in mPFC and BLA, by crossing mice bearing a floxed Rapgef2 allele with a cre mouse line driven by calcium/calmodulin-dependent kinase IIa promoter also eliminated cocaine-induced phospho-ERK activation and Egr-1/Zif268 induction, but without effect on the cocaine-induced behaviors. Our results indicate that NCS-Rapgef2 signaling to ERK in dopamine D1 receptor-expressing neurons in the NAc, but not in corticolimbic areas, contributes to cocaine-induced locomotor sensitization and conditioned place preference. Ablation of cocaine-dependent ERK activation by elimination of NCS-Rapgef2 occurred with no effect on phosphorylation of CREB in D1 dopaminoceptive neurons of NAc. This study reveals a new cAMP-dependent signaling pathway for cocaine-induced behavioral adaptations, mediated through NCS-Rapgef2/phospho-ERK activation, independently of PKA/CREB signaling.
Cannabis Use Disorder (CUD) has been linked to a complex set of neuro-behavioral risk factors. While many studies have revealed sex and gender differences, the relative importance of these risk factors by sex and gender has not been described. We used an “explainable” machine learning approach that combined decision trees [gradient tree boosting, XGBoost] with factor ranking tools [SHapley’s Additive exPlanations (SHAP)] to investigate sex and gender differences in CUD. We confirmed that previously identified environmental, personality, mental health, neurocognitive, and brain factors highly contributed to the classification of cannabis use levels and diagnostic status. Risk factors with larger effect sizes in men included personality (high openness), mental health (high externalizing, high childhood conduct disorder, high fear somaticism), neurocognitive (impulsive delay discounting, slow working memory performance) and brain (low hippocampal volume) factors. Conversely, risk factors with larger effect sizes in women included environmental (low education level, low instrumental support) factors. In summary, environmental factors contributed more strongly to CUD in women, whereas individual factors had a larger importance in men.
Rates of return to use in addiction treatment remain high. We argue that the development of improved treatment options will require advanced understanding of individual heterogeneity in Substance Use Disorders (SUDs). We hypothesized that considerable individual differences exist in the three functional domains underlying addiction—approach-related behavior, executive function, and negative emotionality. We included N = 593 participants from the enhanced Nathan Kline Institute-Rockland Sample community sample (ages 18–59, 67% female) that included N = 420 Controls and N = 173 with past SUDs [54% female; N = 75 Alcohol Use Disorder (AUD) only, N = 30 Cannabis Use Disorder (CUD) only, and N = 68 Multiple SUDs]. To test our a priori hypothesis that distinct neuro-behavioral subtypes exist within individuals with past SUDs, we conducted a latent profile analysis with all available phenotypic data as input (74 subscales from 18 measures), and then characterized resting-state brain function for each discovered subtype. Three subtypes with distinct neurobehavioral profiles were recovered (p < 0.05, Cohen’s D: 0.4–2.8): a “Reward type” with higher approach-related behavior (N = 69); a “Cognitive type” with lower executive function (N = 70); and a “Relief type” with high negative emotionality (N = 34). For those in the Reward type, substance use mapped onto resting-state connectivity in the Value/Reward, Ventral-Frontoparietal and Salience networks; for the Cognitive type in the Auditory, Parietal Association, Frontoparietal and Salience networks; and for the Relief type in the Parietal Association, Higher Visual and Salience networks (pFDR < 0.05). Subtypes were equally distributed amongst individuals with different primary SUDs (χ2 = 4.71, p = 0.32) and gender (χ2 = 3.44, p = 0.18). Results support functionally derived subtypes, demonstrating considerable individual heterogeneity in the multi-dimensional impairments in addiction. This confirms the need for mechanism-based subtyping to inform the development of personalized addiction medicine approaches.
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