Differences in regional cerebral blood flow response to a 5HT3 antagonist in early- and late-onset cocaine-dependent subjects

Sex Differences in Substance Use Disorders: A Neurobiological Perspective

Clinical studies provide fundamental knowledge of substance use behaviors (substance of abuse, patterns of use, relapse rates). The combination of neuroimaging approaches reveal correlation between substance use disorder (SUD) and changes in neural structure, function, and neurotransmission. Here, we review these advances, placing special emphasis on sex specific findings from structural neuroimaging studies of those dependent on alcohol, nicotine, cannabis, psychostimulants, or opioids. Recent clinical studies in SUD analyzing sex differences reveal neurobiological changes that are differentially impacted in common reward processing regions such as the striatum, hippocampus, amygdala, insula, and corpus collosum. We reflect on the contribution of sex hormones, period of drug use and abstinence, and the potential impact of these factors on the interpretation of the reported findings. With the overall recognition that SUD impacts the brains of females and males differentially, it is of fundamental importance that future research is designed with sex as a variable of study in this field. Improved understanding of neurobiological changes in males and females in SUD will advance knowledge underlying sex-specific susceptibility and the neurobiological impact in these disorders. Together these findings will inform future treatments that are tailor designed for improved efficacy in females and males with SUD.

The role of neurocognitive functioning, substance use variables and the DSM-5 severity scale in cocaine relapse: A prospective study

BACKGROUND

The severity of substance use disorder (SUD) is currently defined by the sum of DSM-5 criteria. However, little is known about the validity of this framework or the role of additional severity indicators in relapse prediction. This study aimed to investigate the relationship between DSM-5 criteria, neurocognitive functioning, substance use variables and cocaine relapse among inpatients with cocaine use disorder (CUD).

METHODS

128 adults aged between 18 and 45 years were evaluated; 68 (59 males, 9 females) had CUD and 60 (52 males, 8 females) were healthy controls. For the group with CUD, the use of other substances was not an exclusion criterion. Participants were tested using a battery of neurocognitive tests. Cocaine relapse was evaluated 3 months after discharge.

RESULTS

Scores for attention span and working memory were worse in patients compared to controls. Earlier onset and duration of cocaine use were related to poorer inhibitory control and global executive functioning, respectively; recent use was related to worse performance in inhibitory control, attention span and working memory. More DSM-5 criteria at baseline were significantly associated with relapse.

CONCLUSIONS

Recent cocaine use was the most predictive variable for neurocognitive impairments, while DSM-5 criteria predicted cocaine relapse at three months post treatment. The integration of neurocognitive measures, DSM-5 criteria and cocaine use variables in CUD diagnosis could improve severity differentiation. Longitudinal studies using additional biomarkers are needed to disentangle the different roles of severity indicators in relapse prediction and to achieve more individualized and effective treatment strategies for these patients.

High-dose ondansetron reduces activation of interoceptive and sensorimotor brain regions

Several psychiatric disorders involve abnormalities of interoception and associated neural circuitry centered on the insula. The development of interventions modulating interoceptive circuits could lead to novel treatment approaches for these disorders. The 5-HT3 receptor antagonist ondansetron is a good candidate for the modulation of interoceptive circuits, as 5-HT3 receptors are located abundantly on sensory pathways and ondansetron has shown some clinical utility in disorders characterized by sensory and interoceptive abnormalities. The present study tested the ability of three different doses of ondansetron to engage neural regions involved in interoception to determine the drug's utility as a therapeutic agent to target circuit abnormalities in patients. Fifty-three healthy subjects were randomized to receive a single 8-mg (n = 18), 16-mg (n = 17), or 24-mg (n = 18) dose of ondansetron and placebo before MRI scanning on separate days. Subjects performed an fMRI task previously shown to engage interoceptive circuitry in which they viewed videos depicting body movements/sensation and control videos. The results revealed a highly significant relationship between dosage and activation in bilateral insula, somatosensory and premotor regions, cingulate cortex, and temporal cortex for control but not body-focused videos. These effects were driven by a robust reduction in activation for ondansetron compared to placebo for the 24-mg group, with weaker effects for the 16-mg and 8-mg groups. In conclusion, high-dose ondansetron reduces activation of several areas important for interoception, including insula and sensorimotor cortical regions. This study reveals the potential utility of this drug in modulating hyperactivity in these regions in patients.

Posterior hippocampal regional cerebral blood flow predicts abstinence: a replication study

The posterior hippocampus (pHp) plays a major role in the processing and storage of drug-related cues and is linked to striatal-limbic brain circuits involved with craving and drug salience. We have recently reported that increased basal regional cerebral blood flow (rCBF) in a pHp loci, as measured by pseudo-continuous arterial spin labeling magnetic resonance imaging, predicted days to cocaine relapse following residential treatment. In this secondary analysis, we explored whether rCBF in this same pHp region would successfully predict 30-day point prevalence abstinence 60 days following residential treatment in an independent group of previously studied participants with cocaine dependence. rCBF was assessed with single photon emission computerized tomography during a saline infusion in 21 cocaine dependence and 22 healthy control participants. pHp rCBF was significantly higher in those endorsing substance use (n = 10) relative to both abstinent (n = 11) (p < 0.001) and control (p < 0.05) participants. There were no significant differences in measured demographic or clinical variables between the actively using and non-using participants. This replicative finding suggests that heightened pHp activation is a significant predictor of substance use in cocaine-dependent individuals, possibly reflecting a neural susceptibility to continued drug cues.

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach

Background

Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2–4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations.

Results

The voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of regional cerebral blood flow in brain regions in cocaine-dependent participants are presented with corresponding level of significance.

Conclusions

The SVM-based approach successfully classified cocaine-dependent and healthy control participants using voxels selected with information theoretic-based and statistical methods from participants’ SPECT data. The regions found in this study align with brain regions reported in the literature. These findings support the future use of brain imaging and SVM-based classifier in the diagnosis of substance use disorders and furthering an understanding of their underlying pathology.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1218-z) contains supplementary material, which is available to authorized users.