Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium.

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

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.

Denoising scanner effects from multimodal MRI data using linked independent component analysis.

Pooling magnetic resonance imaging (MRI) data across research studies, or utilizing shared data from imaging repositories, presents exceptional opportunities to advance and enhance reproducibility of neuroscience research. However, scanner confounds hinder pooling data collected on different scanners or across software and hardware upgrades on the same scanner, even when all acquisition protocols are harmonized. These confounds reduce power and can lead to spurious findings. Unfortunately, methods to address this problem are scant. In this study, we propose a novel denoising approach that implements a data-driven linked independent component analysis (LICA) to identify scanner-related effects for removal from multimodal MRI to denoise scanner effects. We utilized multi-study data to test our proposed method that were collected on a single 3T scanner, pre- and post-software and major hardware upgrades and using different acquisition parameters. Our proposed denoising method shows a greater reduction of scanner-related variance compared with standard GLM confound regression or ICA-based single-modality denoising. Although we did not test it here, for combining data across different scanners, LICA should prove even better at identifying scanner effects as between-scanner variability is generally much larger than within-scanner variability. Our method has great promise for denoising scanner effects in multi-study and in large-scale multi-site studies that may be confounded by scanner differences.

Amygdala Resting State Connectivity Differences between Bipolar II and Borderline Personality Disorders.

BACKGROUND: Borderline personality disorder (BPD) and bipolar II disorder (BD II) have significant clinical overlap, leaving the potential for diagnostic inaccuracies and inadequate treatment recommendations. However, few studies have probed for clinical and neurobiological differences between the two disorders. Clinically, some prior studies have linked BPD with greater impulsivity and more frequent negative affective shifts than BD II, whereas previous neuroimaging studies have highlighted both similar and distinct neural abnormalities in BPD and BD II. Notably, no prior study has specifically targeted cortico-limbic neural differences, which have been hypothesized to underlie these core clinical differences. METHODS: Individuals with BPD (n = 14) and BD II (n = 15) completed various clinical measures and a resting state functional imaging scan at 3T. Whole-brain amygdala resting state functional connectivity (RSFC) was compared between the two groups. RESULTS: Relative to the BD II group, BPD participants reported significantly higher levels of impulsivity, trait anxiety, more frequent negative affective shifts, greater interpersonally reactive affective instability, lower overall functioning, and were characterized by lower amygdala-middle frontal gyrus RSFC. Lower amygdala-middle frontal gyrus RSFC was associated with greater impulsivity, trait anxiety, affective shifts, interpersonal affective reactivity, and functional impairment. LIMITATIONS: The current study consisted of small sample sizes and lacked a control group. CONCLUSIONS: This preliminary study suggests that amygdala-frontal RSFC may distinguish BPD from BD II. These results may guide future work aimed at identifying neural markers that can help disentangle these two disorders, leading to greater diagnostic accuracy and appropriate treatment implementation.

A cross-sectional examination of choice and behavior of veterans with access to free medicinal cannabis.

Background: With a rise in public pressure to increase veteran access to medicinal cannabis, free cannabis collectives for military veterans are proliferating across the US. Objectives: The aim of the current study was to document which cannabis formulations and routes of administration are chosen by veterans with increased access to cannabis, and to determine whether cannabis is being used as a substitute for other licit and illicit drugs. Method: The current study collected cross-sectional self-report data on cannabis use, cannabinoid constituent composition, primary indication of use, and substitution practices among a sample of 93 US military veterans (84.9% male) with access to free cannabis. Result: Most of the sample reported using cannabinoids as a substitute for either alcohol, tobacco, prescription medications, or illicit substances, reported that they use cannabis frequently (Modal frequency >4x/day, Modal quantity = 5 to 8 grams/week), and primarily select higher-risk cannabis formulations (i.e., high THC/low CBD, smoked). The majority of the sample reported that they use cannabis to self-treat multiple physical and mental health conditions/symptoms. Conclusions: Results of the current study suggest that military Veterans with reduced barriers to access cannabis could be making both helpful and harmful choices regarding their cannabis use. These findings suggest that more guidance on the selection of cannabis-based products in this population is warranted, particularly as barriers to medicinal cannabis access are reduced.

Marijuana matters: reviewing the impact of marijuana on cognition, brain structure and function, & exploring policy implications and barriers to research.

The neurobiologic effects of cannabis, commonly referred to as 'marijuana' (MJ), have been studied for decades. The impact of recreational MJ use on cognition and measures of brain function and structure is outlined, and variables influencing study results are discussed, including age of the consumer, patterns of MJ use, variations in MJ potency, and the presence of additional cannabinoids. Although evidence suggests that chronic, heavy recreational MJ use is related to cognitive decrements and neural changes, particularly when use begins in adolescence, findings from studies of recreational MJ users may not be applicable to medical marijuana (MMJ) patients given differences in demographic variables, product selection, and reasons for use. Although additional research is needed to fully understand the impact of MJ and individual cannabinoids on the brain, current findings are beginning to inform public policy, including considerations for age limits, potential limits for some cannabinoids, and guidelines for use. However, barriers continue to impede researchers' ability to conduct studies that will guide policy change and provide vital information to consumers and patients regarding best practices and safest methods for use. The need for information is critical, as legalization of MJ for medical and recreational use is increasingly widespread.

Nabilone pharmacotherapy for cannabis dependence: A randomized, controlled pilot study.

BACKGROUND AND OBJECTIVES: We assessed the safety, tolerability, and preliminary efficacy of nabilone, a cannabinoid agonist, to treat cannabis dependence. METHODS: Eighteen adults with DSM-IV cannabis dependence were randomized to receive either 2 mg/day of nabilone (n = 10) or placebo (n = 8) for 10 weeks in addition to medication management. Twelve participants, six in each group, completed treatment. The safety and tolerability of nabilone was assessed at each visit. Any side effects from nabilone or the placebo were documented. Cannabis use outcomes were assessed via self-report of days of use and twice-weekly urine cannabinoid tests; secondary outcomes included cannabis craving and anxiety. RESULTS: We assessed safety and tolerability at each study visit. A total of eight adverse events, all mild or moderate, were reported in two participants in the nabilone group, and six events were reported in four participants in the placebo group during study treatment. A total of eight adverse events were reported in two participants in the nabilone group and six events were reported in four participants in the placebo group during study treatment. All reported adverse events were rated mild-to-moderate. There were no side effects deemed serious enough to be classified as an FDA-defined serious adverse event. In general, participants in both groups reported reduced cannabis use according to self-report over the course of the study, although these reductions were not statistically discernible. Moreover, there was no difference in cannabis use between the nabilone group and the placebo group as measured by self-report. DISCUSSION AND CONCLUSIONS: Nabilone pharmacotherapy was safe and well-tolerated in participants with cannabis dependence. Future studies might evaluate a higher dose of nabilone to determine its effects on cannabis use outcomes in participants with cannabis dependence. SCIENTIFIC SIGNIFICANCE: There remains a clear need for additional pharmacotherapy trials for cannabis dependence, and nabilone remains a candidate for such trials. (Am J Addict 2017;26:795-801).

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.

Identifying Variables Associated with Menopause-Related Shame and Stigma: Results from a National Survey Study.

Background: Despite the significance of menopause as a natural biological milestone experienced by approximately half the population, few studies have evaluated factors associated with menopause-related shame and stigma. Given previous research indicating increased shame and stigma are associated with negative outcomes that directly impact health (e.g., reduced access to health care), it is critical to identify variables associated with menopause-related shame and stigma. Materials and Methods: As part of a larger, national survey, 214 perimenopausal (n = 111) and postmenopausal (n = 103) individuals completed self-report questionnaires assessing demographics and menopause-related symptoms, shame, and stigma. Regression analyses examined variables associated with shame and stigma. Results: Over a third of respondents reported feeling shame related to their menopause-related symptoms (37.4%), while the majority of respondents reported feeling stigma associated with symptoms (82.7%). In addition, most respondents endorsed talking about their symptoms with friends, family, partners, or doctors (80.8%), and felt that their peers might experience the same symptoms (93.9%). Regression analyses identified several significant predictor variables; in particular, more severe psychosocial and urogenital symptoms, higher education level, and younger age were significantly associated with greater odds of reporting shame and stigma. Conclusions: Overall, findings suggest that even though menopausal individuals report feeling their symptoms are similar to their peers, shame and stigma are significantly associated with these symptoms, which may be impacted by symptom severity and socioeconomic factors. Results suggest that younger individuals (i.e., those just entering perimenopause) with more education may be more likely to feel shame and stigma, which could inform interventional strategies and improve clinical outcomes.

Contemplating cannabis? The complex relationship between cannabinoids and hepatic metabolism resulting in the potential for drug-drug interactions.

The majority of states have fully legalized the use of medical cannabis (MC), and nearly all other states allow limited access to cannabidiol (CBD), a non-intoxicating constituent of cannabis often touted for a range of therapeutic indications. Further, the Agricultural Improvement Act of 2018 legalized hemp-derived products in all 50 states; typically high in CBD, these products are derived from cannabis varieties containing ≤0.3% delta-9-tetrahydrocannabinol (THC) by weight. The recent "green rush" has resulted in a striking increase in cannabis use among patients and consumers who often use a wide variety of novel product types, each with a unique blend of cannabinoid constituents. Importantly, however, several cannabinoids have the potential to cause drug-drug interactions (DDI) with other medications, primarily due to their involvement with the hepatic cytochrome P450 (CYP450) system. This article examines the potential for individual cannabinoids, particularly CBD, to interact with the hepatic metabolic system, which is concerning given its involvement in the metabolism of commonly-prescribed medications. CBD and other cannabinoids are metabolized extensively by the CYP450 system, and also inhibit many of these enzymes, potentially leading to variable serum levels of other medications, as well as variable levels of cannabinoids when other medications modify the system. As access and interest in cannabinoid-based products continues to increase, critical questions remain unanswered regarding their safety. The complex relationship between cannabinoids and the hepatic metabolic system, including common potential DDI resulting from cannabinoid exposure, are explored along with the clinical significance of these potential interactions and monitoring or mitigation strategies.

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.

Clinical and cognitive improvement following full-spectrum, high-cannabidiol treatment for anxiety: open-label data from a two-stage, phase 2 clinical trial.

BACKGROUND: Evidence suggests cannabidiol (CBD) has anxiolytic properties, indicating potential for novel treatment strategies. However, few clinical trials of CBD-based products have been conducted, and none thus far have examined the impact of these products on cognition. METHODS: For the open-label stage of clinical trial NCT02548559, autoregressive linear modeling assessed efficacy and tolerability of four-weeks of 1 mL t.i.d. treatment with a full-spectrum, high-CBD sublingual solution (9.97 mg/mL CBD, 0.23 mg/mL Δ-9-tetrahydrocannabinol) in 14 outpatients with moderate-to-severe anxiety, defined as ≥16 on the Beck Anxiety Inventory (BAI) or ≥11 on the Overall Anxiety Severity and Impairment Scale (OASIS). RESULTS: Findings suggest significant improvement on primary outcomes measuring anxiety and secondary outcomes assessing mood, sleep, quality of life, and cognition (specifically executive function) following treatment. Anxiety is significantly reduced at week 4 relative to baseline (BAI: 95% CI = [-21.03, -11.40], p < 0.001, OASIS: 95% CI = [-9.79, -6.07], p < 0.001). Clinically significant treatment response (≥15% symptom reduction) is achieved and maintained as early as week 1 in most patients (BAI = 78.6%, OASIS = 92.7%); cumulative frequency of treatment responders reached 100% by week 3. The study drug is well-tolerated, with high adherence/patient retention and no reported intoxication or serious adverse events. Minor side effects, including sleepiness/fatigue, increased energy, and dry mouth are infrequently endorsed. CONCLUSIONS: Results provide preliminary evidence supporting efficacy and tolerability of a full-spectrum, high-CBD product for anxiety. Patients quickly achieve and maintain symptom reduction with few side effects. A definitive assessment of the impact of this novel treatment on clinical symptoms and cognition will be ascertained in the ongoing double-blind, placebo-controlled stage.

Cannabidiol (CBD) is a compound found within the Cannabis sativa plant. Previous studies suggest CBD may reduce anxiety. In this clinical trial, 14 patients with anxiety were treated for four-weeks with a cannabis-derived study product with high levels of CBD, administered under their tongue 3 times each day. All patients knew that they were being given CBD. Following four weeks of treatment, patients reported reduced anxiety as well as improvements in mood, sleep, quality of life, and measures reflecting their self-control and ability to think flexibly. Patients did not experience any serious negative effects during the trial. The impact of this product is now being evaluated in more patients with anxiety.

Increased White Matter Coherence Following Three and Six Months of Medical Cannabis Treatment.

Background: Previous studies have demonstrated abnormal white matter (WM) microstructure in recreational cannabis consumers; however, the long-term impact of medical cannabis (MC) use on WM coherence is unknown. Accordingly, this study assessed the longitudinal impact of MC treatment on WM coherence. Given results from preclinical studies, we hypothesized that MC treatment would be associated with increased fractional anisotropy (FA) and reduced mean diffusivity (MD). Methods: As part of a larger, longitudinal investigation, patients interested in treating at least one medical condition with commercially available MC products of their choosing were assessed before initiating MC use (baseline n=37; female=25, male=12) and following three (n=31) and six (n=22) months of treatment. WM coherence was assessed via diffusion tensor imaging for bilateral regions of interest including the genu of the corpus callosum, anterior limb of the internal capsule, external capsule, and anterior corona radiata, as well as an occipital control region not expected to change over time. Results: In MC patients, FA values significantly increased bilaterally in several callosal regions relative to baseline following both 3 and 6 months of treatment; MD values significantly decreased in all callosal regions but only following 6 months of treatment. No significant changes in WM coherence were observed in the control region or in a pilot sample of treatment-as-usual patients (baseline n=14), suggesting that increased WM coherence observed in MC patients may be attributed to MC treatment as opposed to confounding factors. Interestingly, significant reductions in MD values correlated with higher cannabidiol (CBD) exposure but not Δ-9-tetrahydrocannabinol exposure. Conclusions: Overall, MC treatment was associated with increased WM coherence, which contrasts with prior research examining recreational cannabis consumers, likely related to inherent differences between recreational consumers and MC patients (e.g., product choice, age of onset). In addition, increased CBD exposure was associated with reduced MD following 6 months of treatment, extending evidence from preclinical research indicating that CBD may be neuroprotective against demyelination. However, additional research is needed to elucidate the clinical efficacy of MC treatment and the risks and benefits of long-term MC use.

A scoping review of the use of cannabidiol in psychiatric disorders.

Cannabidiol (CBD) has become a fast-growing avenue for research in psychiatry, and clinicians are challenged with understanding the implications of CBD for treating mental health disorders. The goal of this review is to serve as a guide for mental health professionals by providing an overview of CBD and a synthesis the current evidence within major psychiatric disorders. PubMed and PsycINFO were searched for articles containing the terms "cannabidiol" in addition to major psychiatric disorders and symptoms, yielding 2952 articles. Only randomized controlled trials or within-subject studies investigating CBD as a treatment option for psychiatric disorders (N = 16) were included in the review. Studies were reviewed for psychotic disorders (n = 6), anxiety disorders (n = 3), substance use disorders (tobacco n = 3, cannabis n = 2, opioid n = 1), and insomnia (n = 1). There were no published studies that met inclusion criteria for alcohol or stimulant use disorder, PTSD, ADHD, autism spectrum disorder, or mood disorders. Synthesis of the CBD literature indicates it is generally safe and well tolerated. The most promising preliminary findings are related to the use of CBD in psychotic symptoms and anxiety. There is currently not enough high-quality evidence to suggest the clinical use of CBD for any psychiatric disorder.

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.

Measuring Ostracism-Induced Changes in Consumption of Palatable Food: Feasibility of a Novel Behavioral Task.

Purpose: Ostracism is a highly aversive interpersonal experience. Previous research suggests that it can increase consumption of highly palatable food in some individuals, but decrease it in others. Thus, we developed the Cyberball-Milkshake Task (CMT), to facilitate research investigating individual differences in ostracism's effects on consumption of highly palatable food. We present data on feasibility for the CMT in a sample of young adult women. Materials and Methods: Participants were 22 women, 18-30 years old, reporting very low or very high levels of emotional eating at screening. Participants performed the CMT, which consisted of 12 trials. Each trial included: playing a round of Cyberball (a computerized game of catch with fictitious "other participants" programmed to either include or exclude the participant); viewing a chocolate image; and then consuming a participant-determined amount of milkshake. Participants subsequently played an additional inclusion and exclusion round of Cyberball, each immediately followed by questionnaires assessing current mood and recent Cyberball experience. Results: Cyberball exclusion (vs. inclusion) was associated with large, significant increases in reported ostracism and threats to self-esteem; exclusion's effects on affect were in the expected direction (e.g., increased negative affect), but generally small and non-significant. Milkshake intake was measurable for 95% of participants, on 96% of trials. Intake decreased quadratically across trials, with a steep negative slope for low trial numbers that decreased to the point of being flat for the highest trial numbers. Discussion: The CMT is a generally feasible approach to investigating ostracism's effects on consumption of highly palatable food. The feasibility (and validity) of the CMT may benefit from modification (e.g., fewer trials and longer rounds of Cyberball). Future research should examine whether performance on a modified version of the CMT predicts real-world behavior in a larger sample.

Deconstructing dissociation: a triple network model of trauma-related dissociation and its subtypes.

Trauma-related pathological dissociation is characterized by disruptions in one's sense of self, perceptual, and affective experience. Dissociation and its trauma-related antecedents disproportionately impact women. However, despite the gender-related prevalence and high individual and societal costs, dissociation remains widely underappreciated in clinical practice. Moreover, dissociation lacks a synthesized neurobiological model across its subtypes. Leveraging the Triple Network Model of psychopathology, we sought to parse heterogeneity in dissociative experience by examining functional connectivity of three core neurocognitive networks as related to: (1) the dimensional dissociation subtypes of depersonalization/derealization and partially-dissociated intrusions; and, (2) the diagnostic category of dissociative identity disorder (DID). Participants were 91 women with and without: a history of childhood trauma, current posttraumatic stress disorder (PTSD), and varied levels of dissociation. Participants provided clinical data about dissociation, PTSD symptoms, childhood maltreatment history, and completed a resting-state functional magnetic resonance imaging scan. We used a novel statistical approach to assess both overlapping and unique contributions of dissociation subtypes. Covarying for age, childhood maltreatment and PTSD severity, we found dissociation was linked to hyperconnectivity within central executive (CEN), default (DN), and salience networks (SN), and decreased connectivity of CEN and SN with other areas. Moreover, we isolated unique connectivity markers associated with depersonalization/derealization in CEN and DN, to partially-dissociated intrusions in CEN, and to DID in CEN. This suggests dissociation subtypes have robust functional connectivity signatures that may serve as targets for PTSD/DID treatment engagement. Our findings underscore dissociation assessment as crucial in clinical care, in particular, to reduce gender-related health disparities.

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.