CannaCount: an improved metric for quantifying estimates of maximum possible cannabinoid exposure.

Increasing numbers of individuals have access to cannabinoid-based products containing various amounts of delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD), and other cannabinoids. Exposure to specific cannabinoids likely influences outcomes; however, current methods for quantifying cannabis exposure do not account for the cannabinoid concentrations of the products used. We developed CannaCount, an examiner-driven metric that quantifies estimated maximum possible cannabinoid exposure by accounting for variables related to cannabinoid concentration, duration, frequency, and quantity of use. To demonstrate feasibility and applicability, CannaCount was used to quantify estimated maximum THC and CBD exposure in 60 medical cannabis patients enrolled in a two-year, longitudinal, observational study. Medical cannabis patients reported using a variety of product types and routes of administration. Calculating estimated exposure to THC and CBD was possible for the majority of study visits, and the ability to generate estimated cannabinoid exposure improved over time, likely a function of improved product labeling, laboratory testing, and more informed consumers. CannaCount is the first metric to provide estimated maximum possible exposure to individual cannabinoids based on actual cannabinoid concentrations. This metric will ultimately facilitate cross-study comparisons and can provide researchers and clinicians with detailed information regarding exposure to specific cannabinoids, which will likely have significant clinical impact.

A survey of medical cannabis use during perimenopause and postmenopause.

OBJECTIVE: Expanding access to legal cannabis has dovetailed with increased interest in medical cannabis (MC) use; however, there is a paucity of research examining MC use to alleviate menopause-related symptoms. This survey study assessed patterns of MC use in perimenopausal and postmenopausal individuals. METHODS: Participants (perimenopausal, n = 131; postmenopausal, n = 127) completed assessments of menopause-related symptomatology and cannabis use, including modes of use, type of use, and menopause-related symptoms addressed by MC use. RESULTS: Most participants reported current cannabis use (86.1%) and endorsed using MC for menopause-related symptoms (78.7%). The most common modes of use were smoking (84.3%) and edibles (78.3%), and the top menopause-related symptoms for MC use were sleep disturbance (67.4%) and mood/anxiety (46.1%). Relative to postmenopausal participants, perimenopausal participants reported significantly worse menopause-related symptomatology on the vasomotor and psychosocial subscales of the Menopause-Specific Quality of Life Questionnaire ( P s ≤ 0.04), including greater burden of anxiety ( P = 0.01) and hot flash ( P = 0.04) symptoms. In addition, perimenopausal participants reported higher incidence of depression ( P = 0.03) and anxiety diagnoses ( P < 0.01), as well as increased use of MC to treat menopause-related mood/anxiety symptoms relative to postmenopausal participants ( P = 0.01). CONCLUSIONS: Results suggest that many individuals are currently using MC as an adjunctive treatment for menopause-related symptoms, particularly sleep disturbance and mood/anxiety. Future research should examine the impact of different MC use characteristics (e.g., cannabinoid profiles) on the efficacy of MC use for menopause-related symptoms. Increased severity and prevalence of mood and anxiety symptoms in perimenopausal participants suggest promising targets for clinical trials of cannabinoid-based therapies.

Elevated striatal glutamate + glutamine in recreational cannabis users during abstinence.

Cannabis withdrawal symptoms contribute to relapse, but the underlying mechanism remains unclear. We hypothesize that cannabis withdrawal may be associated with a reset of regional γ-amino butyric acid (GABA) and glutamate concentrations secondary to changes in the endocannabinoid system during abstinence and conducted a study on this issue. We used magnetic resonance spectroscopy (MRS) to detect the associated changes of these neurochemicals in twenty-six frequent, recreational cannabis users and eleven age-matched non-using controls. Twenty users (8F/12M) and ten control (5F/5M) participants completed a verified 21-day abstinence period. Striatal GABA and glutamine concentrations were measured at baseline and on abstinence days 7 and 21 in conjunction with measures of cannabis withdrawal symptoms and mood state. Cannabis users reported increased self-reported ratings of cannabis-withdrawal-symptoms on abstinence day 7 relative to controls. Striatal glutamate + glutamine (Glx) group concentrations were elevated in cannabis users at baseline and abstinence days 7 and 21 (F = 7.16, p = 0.012), and changes in GABA concentration and withdrawal symptoms between baseline and abstinence day 7 were positively correlated (r = 0.550, p = 0.010). In addition, baseline striatal GABA concentrations were negatively correlated with withdrawal symptoms on abstinence day 7 (r = -0.680, p = 0.003). Our data demonstrate that striatal Glx was elevated in cannabis users and baseline striatal GABA correlated with withdrawal during the abstinence. In addition, striatal GABA may temporally correlate with self-reported withdrawal symptoms during the initial days of abrupt cannabis abstinence. These findings provide preliminary evidence that striatal GABA and Glx are associated with the severity of cannabis withdrawal.

Unravelling psychiatric heterogeneity and predicting suicide attempts in women with trauma-related dissociation using artificial intelligence.

Background: Suicide is a leading cause of death, and rates of attempted suicide have increased during the COVID-19 pandemic. The under-diagnosed psychiatric phenotype of dissociation is associated with elevated suicidal self-injury; however, it has largely been left out of attempts to predict and prevent suicide.Objective: We designed an artificial intelligence approach to identify dissociative patients and predict prior suicide attempts in an unbiased, data-driven manner.Method: Participants were 30 controls and 93 treatment-seeking female patients with posttraumatic stress disorder (PTSD) and various levels of dissociation, including some with the PTSD dissociative subtype and some with dissociative identity disorder (DID).Results: Unsupervised learning models identified patients along a spectrum of dissociation. Moreover, supervised learning models accurately predicted prior suicide attempts with an F1 score up to 0.83. DID had the highest risk of prior suicide attempts, and distinct subtypes of dissociation predicted suicide attempts in PTSD and DID.Conclusions: These findings expand our understanding of the dissociative phenotype and underscore the urgent need to assess for dissociation to identify individuals at high-risk of suicidal self-injury.

Dissociation, feelings of detachment and disruption in one's sense of self and surroundings, is associated with an elevated risk of suicidal self-injury; however, it has largely been left out of attempts to predict and prevent suicide.Using machine learning techniques, we found dissociative identity disorder had the highest risk of prior suicide attempts, and distinct subtypes of dissociation predicted suicide attempts in posttraumatic stress disorder and dissociative identity disorder.These findings underscore the urgent need to assess for dissociation to identify individuals at high-risk of suicidal self-injury.

An Observational, Longitudinal Study of Cognition in Medical Cannabis Patients over the Course of 12 Months of Treatment: Preliminary Results.

OBJECTIVE: Cannabis use has increased dramatically across the country; however, few studies have assessed the long-term impact of medical cannabis (MC) use on cognition. Studies examining recreational cannabis users generally report cognitive decrements, particularly in those with adolescent onset. As MC patients differ from recreational consumers in motives for use, product selection, and age of onset, we assessed cognitive and clinical measures in well-characterized MC patients over 1 year. Based on previous findings, we hypothesized MC patients would not show decrements and might instead demonstrate improvements in executive function over time. METHOD: As part of an ongoing study, MC patients completed a baseline visit prior to initiating MC and evaluations following 3, 6, and 12 months of treatment. At each visit, patients completed a neurocognitive battery assessing executive function, verbal learning/memory, and clinical scales assessing mood, anxiety, and sleep. Exposure to delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) was also quantified. RESULTS: Relative to baseline, MC patients demonstrated significant improvements on measures of executive function and clinical state over the course of 12 months; verbal learning/memory performance generally remained stable. Improved cognitive performance was not correlated with MC use; however, clinical improvement was associated with higher CBD use. Analyses suggest cognitive improvements were associated with clinical improvement. CONCLUSIONS: Study results extend previous pilot findings, indicating that MC patients may exhibit enhanced rather than impaired executive function over time. Future studies should examine distinctions between recreational and MC use to identify potential mechanisms related to cognitive changes and the role of clinical improvement.

No pain, all gain? Interim analyses from a longitudinal, observational study examining the impact of medical cannabis treatment on chronic pain and related symptoms.

Previous studies have demonstrated improvements in pain following short-term medical cannabis (MC) use, suggesting long-term MC treatment may alleviate symptoms associated with chronic pain. The goal of this observational and longitudinal study was to examine patients using MC to treat chronic pain pre versus post MC treatment. These interim analyses included 37 patients with chronic pain evaluated prior to initiation of MC treatment and following 3 and 6 months of MC use; pain, clinical state, sleep, quality of life, and conventional medication use were assessed. Correlation analyses examined the relationship between changes in pain and other clinical measures, assessed the impact of cannabinoid exposure on pain and clinical ratings, and assessed whether baseline cannabis expectancies influenced outcome variables. Additionally, a pilot group of treatment-as-usual patients (n = 9) who did not use MC were examined at baseline and 3 months later. Relative to baseline, following 3 and 6 months of treatment, MC patients exhibited improvements in pain which were accompanied by improved sleep, mood, anxiety, and quality of life, and stable conventional medication use. Reduced pain was associated with improvements in aspects of mood and anxiety. The results generally suggest increased THC exposure was related to pain-related improvement, while increased CBD exposure was related to improved mood. Cannabis expectancies were not related to observed improvements. Pilot analyses revealed that treatment-as-usual patients do not demonstrate the same pattern of improvement. Findings highlight the potential efficacy of MC treatment for pain and underscore the unique impact of individual cannabinoids on specific aspects of pain and comorbid symptoms. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Assessing Cannabis Use Disorder in Medical Cannabis Patients: Interim Analyses from an Observational, Longitudinal Study.

Background: To date, no studies have directly assessed potential cannabis use disorder (CUD) in medical cannabis (MC) patients pre- vs post-MC treatment. Given that MC patients use cannabis for symptom alleviation rather than intoxication, we hypothesized that MC patients would exhibit few symptoms of CUD after initiating MC treatment. Methods: As part of an ongoing observational, longitudinal study, 54 MC patients completed baseline assessments prior to initiating MC use and returned for at least one follow-up assessment after three, six, and/or twelve months of a self-selected MC treatment regimen; detailed MC treatment information was collected and quantified. All patients completed the Cannabis Use Disorder Identification Test - Revised (CUDIT-R) at each visit. Changes in individual items scores and total scores were assessed over time, and we examined whether total CUDIT-R scores correlated with frequency of MC use, delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) exposure. Further, Cronbach's alpha analyses were conducted to provide preliminary data regarding the psychometric properties of the CUDIT-R when used among MC patients. Results: Although total CUDIT-R scores increased relative to baseline, on average, ratings fell below the 'hazardous use' threshold at each visit. Analyses of individual items revealed that increases in total scores were primarily attributable to increases in frequency of use and not necessarily other aspects of problematic use. Total CUDIT-R scores were not associated with number of MC uses or CBD exposure, but a significant relationship was detected between increased THC exposure and higher CUDIT-R scores. Importantly however, analyses revealed that the CUDIT-R does not appear to be an appropriate tool for identifying CUD in MC patients. Conclusions: Screening tools specifically designed to assess CUD in MC patients are needed and should distinguish between frequent use and problematic use; exposure to individual cannabinoids must also be considered.

Recreational cannabis use impairs driving performance in the absence of acute intoxication.

BACKGROUND: Across the nation, growing numbers of individuals are exploring the use of cannabis for medical or recreational purposes, and the proportion of cannabis-positive drivers involved in fatal crashes increased from 8 percent in 2013 to 17 percent in 2014, raising concerns about the impact of cannabis use on driving. Previous studies have demonstrated that cannabis use is associated with impaired driving performance, but thus far, research has primarily focused on the effects of acute intoxication. METHODS: The current study assessed the potential impact of cannabis use on driving performance using a customized driving simulator in non-intoxicated, heavy, recreational cannabis users and healthy controls (HCs) without a history of cannabis use. RESULTS: Overall, cannabis users demonstrated impaired driving relative to HC participants with increased accidents, speed, and lateral movement, and reduced rule-following. Interestingly, however, when cannabis users were divided into groups based on age of onset of regular cannabis use, significant driving impairment was detected and completely localized to those with early onset (onset before age 16) relative to the late onset group (onset ≥16 years old). Further, covariate analyses suggest that impulsivity had a significant impact on performance differences. CONCLUSIONS: Chronic, heavy, recreational cannabis use was associated with worse driving performance in non-intoxicated drivers, and earlier onset of use was associated with greater impairment. These results may be related to other factors associated with early exposure such as increased impulsivity.

Prefrontal cortex activation during cognitive interference in nonsuicidal self-injury.

Nonsuicidal self-injury (NSSI), deliberate behavior resulting in self-inflicted damage to oneself, is common, particularly among female adolescents, and may be a form of maladaptive emotion regulation. Cognitive interference, a specific type of processing associated with inhibiting prepotent responses in favor of less automatic ones, is utilized in treatment strategies to shift patients' thoughts and behaviors away from maladaptive responses and replace them with more adaptive ones. We examined cognitive interference processing using the Multi-Source Interference Task (MSIT) in females with NSSI behavior (n=15) and healthy control females (n=15). Functional magnetic resonance imaging (fMRI) data were collected concurrently. Results revealed similar between-group performance on the MSIT; however, women with NSSI behavior exhibited altered patterns of neural activation during the MSIT. Specifically, the NSSI group demonstrated increased cingulate cortex (CC) and decreased dorsolateral prefrontal cortex (DLPFC) activation compared to the control group. Further, within the NSSI group, DLPFC activation inversely correlated with emotional reactivity and self-reported impulsivity, suggesting that decreased DLPFC activation is associated with poorer emotional control and increased impulsivity. Taken together, these results indicate that women with NSSI behavior utilize different cortical areas during cognitive interference processing, which may have broader implications regarding the treatment efficacy of cognitive-based therapies.

Decreased Cingulate Cortex activation during cognitive control processing in bipolar disorder.

BACKGROUND: Cognitive deficits are well-documented in patients with bipolar disorder (BPD) and may impact the efficacy of psychotherapy. Cognitive control, a form of executive functioning, is often used therapeutically to shift patients' thoughts and behaviors from automatic, maladaptive responses to adaptive coping strategies. This study examined cognitive control processing in patients with BPD using the Multi-Source Interference Task (MSIT). METHOD: Twenty-nine patients diagnosed with BPD and 21 healthy control (HC) subjects completed the MSIT with concurrent functional magnetic resonance imaging (fMRI). RESULTS: Patients with BPD generally performed worse on the MSIT relative to HC participants; the BPD group had significantly lower performance accuracy and made more omission errors. Further, fMRI analyses revealed differential patterns of activation between the groups during the MSIT. Region of interest (ROI) analyses revealed that relative to HC participants, patients with BPD activated significantly fewer voxels within the cingulate cortex (CC) and more voxels within prefrontal cortex (PFC), although the PFC findings did not survive more stringent significance thresholds. LIMITATIONS: Patients and HCs were not matched for age, sex, and premorbid verbal IQ, however, these variables were controlled for statistically. Medication usage in the BPD group may have possibly impacted the results. Given a priori hypotheses, ROI analyses were utilized. CONCLUSIONS: Decreased CC activation and increased PFC activation may be associated with impaired cognitive control, demonstrated by BPD patients when completing the MSIT. Identifying the neural mechanisms which underlie key cognitive abnormalities in BPD may aid in clarifying the pathophysiology of this disorder and inform selection of potential targets for cognition remediation in BPD.

Joint Effects: A Pilot Investigation of the Impact of Bipolar Disorder and Marijuana Use on Cognitive Function and Mood.

Marijuana is the most widely used illicit substance in those diagnosed with bipolar I disorder. However, there is conflicting evidence as to whether marijuana may alleviate or exacerbate mood symptomatology. As bipolar disorder and marijuana use are individually associated with cognitive impairment, it also remains unclear whether there is an additive effect on cognition when bipolar patients use marijuana. The current study aimed to determine the impact of marijuana on mood in bipolar patients and to examine whether marijuana confers an additional negative impact on cognitive function. Twelve patients with bipolar disorder who smoke marijuana (MJBP), 18 bipolar patients who do not smoke (BP), 23 marijuana smokers without other Axis 1 pathology (MJ), and 21 healthy controls (HC) completed a neuropsychological battery. Further, using ecological momentary assessment, participants rated their mood three times daily as well as after each instance of marijuana use over a four-week period. Results revealed that although the MJ, BP, and MJBP groups each exhibited some degree of cognitive impairment relative to HCs, no significant differences between the BP and MJBP groups were apparent, providing no evidence of an additive negative impact of BPD and MJ use on cognition. Additionally, ecological momentary assessment analyses indicated alleviation of mood symptoms in the MJBP group after marijuana use; MJBP participants experienced a substantial decrease in a composite measure of mood symptoms. Findings suggest that for some bipolar patients, marijuana may result in partial alleviation of clinical symptoms. Moreover, this improvement is not at the expense of additional cognitive impairment.

From Pavlov to PTSD: the extinction of conditioned fear in rodents, humans, and anxiety disorders.

Nearly 100 years ago, Ivan Pavlov demonstrated that dogs could learn to use a neutral cue to predict a biologically relevant event: after repeated predictive pairings, Pavlov's dogs were conditioned to anticipate food at the sound of a bell, which caused them to salivate. Like sustenance, danger is biologically relevant, and neutral cues can take on great salience when they predict a threat to survival. In anxiety disorders such as posttraumatic stress disorder (PTSD), this type of conditioned fear fails to extinguish, and reminders of traumatic events can cause pathological conditioned fear responses for decades after danger has passed. In this review, we use fear conditioning and extinction studies to draw a direct line from Pavlov to PTSD and other anxiety disorders. We explain how rodent studies have informed neuroimaging studies of healthy humans and humans with PTSD. We describe several genes that have been linked to both PTSD and fear conditioning and extinction and explain how abnormalities in fear conditioning or extinction may reflect a general biomarker of anxiety disorders. Finally, we explore drug and neuromodulation treatments that may enhance therapeutic extinction in anxiety disorders.