Ketamine has transformed depression treatment by providing therapeutic relief within a single day, unlike monoaminergic antidepressants that require weeks to take effect. Here, we conducted whole-brain screening in mice to compare drug-evoked c-fos expression—acting as a marker of brain activity leading to protein synthesis-dependent forms of plasticity—following treatment with monoaminergic antidepressants, ketamine and psilocybin. Our findings reveal a shared limbic brain circuit comprising subcortical and frontal cortical regions, with a key distinction: c-fos-based activity in the prelimbic and infralimbic frontal cortex—areas strongly implicated in depression—was acutely induced by ketamine and high-dose psilocybin, but emerged only after chronic dosing with the selective serotonin reuptake inhibitor fluoxetine or psilocybin microdosing. These results suggest the existence of a core limbic subcortico-cortical circuit underlying antidepressant efficacy, provide mechanistic insight into the delayed therapeutic effects of monoaminergic antidepressants, and reveal a close similarity in brain activity evoked by monoaminergic antidepressants and psilocybin microdosing. ### Competing Interest Statement P.O. and J.A.L. are founders and shareholders or Theracast. P.O., K.J., J.C., T.G. and M.M are employees of Theracast. Theracast

In a recent SXSW presentation, Jeffrey A. Lieberman, MD, explored the potential of psychedelics and cannabis within the realm of physician leadership. Highlighting the high interest in the medicinal use of these substances, Lieberman underscored the necessity of responsible use and rigorous scientific research. In this podcast interview with Mike Sacopulos, he delved into the potential benefits and risks of using mindbending drugs in clinical settings. Lieberman stressed that while these substances may offer therapeutic potential, they must be administered with caution and under the supervision of trained medical professionals. As psychiatry advances, it is crucial for physicians to adopt a balanced, informed perspective and thoroughly comprehend the effects of these substances on the human brain and behavior.

Schizophrenia is among the most devastating and costly human diseases. The public face of the failure to appropriately treat schizophrenia includes approximately 100,000 homeless individuals with schizophrenia and related psychoses and 200,000 incarcerated individuals with similar diagnoses. Clozapine and long-acting injectable antipsychotics are among the most effective treatments, but both are markedly underused. The following organizations should take responsibility for fixing this problem: National Institute of Mental Health, Patient-Centered Outcomes Research Institute, Substance Abuse and Mental Health Services Administration, Centers for Medicare and Medicaid Services, U.S. Food and Drug Administration, American Psychiatric Association, and patient and family advocacy groups.

AIM:Artificial Intelligence (AI)-based prediction models of treatment response promise to revolutionize psychiatric care by enabling personalized treatment, but very few have been thoroughly tested in different samples or compared to current clinical standards. Here we present models predicting antipsychotic response and assess their clinical utility in a robust methodological framework. METHODS:Machine learning models were trained and cross-validated on clinical and sociodemographic data from 594 individuals with established schizophrenia (NCT00014001) and 323 individuals with first episode psychosis (NCT03510325). Models predicted four measures of antipsychotic response at 3 months after baseline. Clinical utility was assessed using decision curve and calibration curve analyses. Model performance was tested in a reduced feature space and across sex, ethnicity, antipsychotic, and symptom change subgroups to investigate model fairness. RESULTS:Models predicting total symptom severity (r = 0.4-0.68) and symptomatic remission (BAC = 62.4%-69%) performed well in both samples and externally validated successfully in the opposing cohort (r = 0.4-0.5, BAC = 63.5%-65.7%). Performance remained significant when the models were reduced to 8-9 key variables (r = 0.53 for total symptom severity, BAC = 65.3% for symptomatic remission). Models predicting symptomatic remission had a net benefit across risk thresholds of 0.5-0.9 and were moderately well-calibrated (ECE = 0.16-0.18). Model performance different across sex, ethnicity and medication subgroups. CONCLUSIONS:We present a robust framework for training and assessing the clinical utility of prediction models in psychiatry. Our models generalize across different psychosis populations and show promising calibration and net benefit. However, performance disparities across demographic and treatment subgroups highlight the need for more diverse clinical samples to ensure equitable prediction.

ObjectivesThe pathology of Tardive Dyskinesia (TD) has yet to be fully understood, but there have been proposed hypotheses for the cause of this condition. Our team previously reported a possible association of TD with the Complement Component C4 gene in the HLA region. In this study, we explored the HLA region further by examining two previously identified schizophrenia-associated HLA-region single-nucleotide polymorphisms (SNPs), namely rs13194504 and rs210133.MethodsThe SNPs rs13194504 and rs210133 were tested for association with the occurrence and severity of TD in a sample of 172 schizophrenia patients who were recruited for four studies from three different clinical sites in Canada and USA.ResultsThe rs13194504 AA genotype was associated with decreased severity for TD as measured by Abnormal Involuntary Movement Scale (AIMS) scores (p = 0.047) but not for TD occurrence. SNP rs210133 was not significantly associated with either TD occurrence or AIMS scores.ConclusionOur findings suggest that the rs13194504 AA genotype may play a role in TD severity, while SNP rs210133 may not have a major role in the risk or severity of TD.

Objective: The rate of worldwide mass shootings increased almost 400% over the last 40 years. About 30% are followed by the perpetrator's fatal or nonfatal suicide attempt. Method: We examined the rate of fatal and nonfatal attempts among 528 mass shooters over the last 40 years and their relationship to detected mental illness to better understand this specific context of suicide. We collected information on U.S.-based, personal-cause mass murders that involved one or more firearms, from online sources. Results: A greater proportion of mass shooters from 2000 to 2019 took or attempted to take their own lives (40.5%) compared with those from 1980 to 1999 (23.2%, p < 0.001). More than double the proportion of perpetrators who made a fatal or nonfatal suicide attempt had a history of non-psychotic psychiatric/neurologic symptoms (38.9%), compared with perpetrators who did not make a fatal or nonfatal suicide attempt (18.1%; p < 0.001). Among mass shooters who made fatal or nonfatal suicide attempts, 77 of 175 (44%) did not have any recorded psychiatric, neurologic, or substance use condition. Of the 98 mass shooters who made fatal or non-fatal suicide attempts and had a psychiatric, substance use, or neurologic condition, 41 had depressive disorders. Conclusion: It is possible that a lack of information about the perpetrators' mental health or suicidal ideation led to an underestimation of their prevalence. These data suggest that suicide associated with mass shootings may represent a specific context for suicide, and approaches such as psychological autopsy can help to ascertain when psychiatric illness mediates the relationship between mass shootings and suicide.

Despite research advances and progress in health care, schizophrenia remains a debilitating and costly disease. Onset occurs typically during youth and can lead to a relapsing and ultimately chronic course with persistent symptoms and functional impairment if not promptly and properly treated. Consequently, over time, schizophrenia causes substantial distress and disability for patients, their families and accrues to a collective burden to society. Recent research has revealed much about the pathophysiology that underlies the progressive nature of schizophrenia. Additionally, treatment strategies for disease management have been developed that have the potential to not just control psychotic symptoms but limit the cumulative morbidity of the illness. Given the evidence for their effectiveness and feasibility for their application, it is perplexing that this model of care has not yet become the standard of care and widely implemented to reduce the burden of illness on patients and society. This begs the question of whether the failure of implementation of a potentially disease-modifying strategy is due to the lack of evidence of efficacy (or belief in it) and readiness for implementation, or whether it's the lack of motivation and political will to support their utilization. To address this question, we reviewed and summarized the literature describing the natural history, pathophysiology and therapeutic strategies that can alleviate symptoms, prevent relapse, and potentially modify the course of schizophrenia. We conclude that, while we await further advances in mental health care from research, we must fully appreciate and take advantage of the effectiveness of existing treatments and overcome the attitudinal, policy, and infrastructural barriers to providing optimal mental health care capable of providing a disease- modifying treatment to patients with schizophrenia.

While mass murders involving academic settings, especially using firearms, are of grave, growing public concern, identifying consistent patterns to aid prevention has proved challenging. Although some characteristics, such as male sex, have been routinely associated with these events, another hypothesized risk factor, severe mental illness, has been less reliably predictive. We isolated cases of mass murder perpetrated at least in part at schools, colleges, and universities from the Columbia Mass Murder Database (CMDD) and categorized them by location (within or outside of the US), and whether firearms were used. Demographic similarities and differences between groups were analyzed statistically wherever possible. We examined 82 incidents of mass murder, by any means, involving academic settings. Nearly half of all incidents (47.6%), and most involving firearms (63.2%), were U.S.-based, whereas those not involving firearms largely occurred elsewhere (88.0%). Consistent with previous reports, perpetrators of mass shootings involving academic settings are primarily Caucasian (66.7%) and male (100%). Severe mental illness (i.e., psychosis) was absent in the majority of perpetrators (firearms: 80.7%; nonfirearms: 68.0%). About half (45.6%) of mass school shootings ended with the perpetrator's suicide. When present, psychotic symptoms are more associated with mass murders in academic settings involving means other than firearms. The question of whether perpetrators of such incidents may perceive their actions as a kind of final act might enhance policy development and/or how law enforcement intervenes.

Mass murder, particularly mass shootings, constitutes a major, growing public health concern. Specific motivations for these acts are not well understood, often overattributed to severe mental illness. Identifying diverse factors motivating mass murders may facilitate prevention. We examined 1,725 global mass murders from 1900-2019, publicly described in English in print or online. We empirically categorized each into one of ten categories reflecting reported primary motivating factors, which were analyzed across mass murderers generally, as well as between U.S- and non-U.S.-based mass-shooters. Psychosis or disorganization related to mental illness were infrequently motivational factors (166; 9.6%), and were significantly more associated with mass murder committed using methods other than firearms. The vast majority (998, 57.86%) of incidents were impulsive and emotionally-driven, following adverse life circumstances. Most mass murderers prompted by emotional upset were found to be driven by despair or extreme sadness over life events (161, 16.13% within the category); romantic rejection or loss, or severe jealousy (204, 20.44% within the category); some specific non-romantic grudge (212, 21.24% within the category); or explosive, overwhelming rage following a dispute (266, 26.65% within the category). Results suggest that policies seeking to prevent mass murder should focus on criminal history, as well as subacute emotional disturbances not associated with severe mental illness in individuals with poor coping skills who have recently experienced negative life events.

Most research to date has focused on perpetrators of mass murder incidents. Hence, there is little information on victims. We examined 973 mass murders that occurred in the United States between 1900 and 2019 resulting in 5,273 total fatalities and 4,498 nonfatal injuries for a total of 9,771 victims (on average 10 victims per incident). Approximately 64% of victims of mass murder were White individuals, 13% were Black individuals, 6% were Asian individuals, and 14% were Latinx individuals. Given the higher number of nonfatal injuries per non-firearm mass murder event (11.0 vs. 2.8, p < .001), the total number of victims was only 50% higher for mass shootings (5,855 victims) vs. non-firearm mass murder events (3,916 victims). Among the 421 incidents of mass murder in the United States since 2000, Black, Asian, and Native American individuals were overrepresented among victims of mass shootings compared with their representation in the general U.S. population, and White individuals were underrepresented (all p ≤ .002). Findings of racial/ethnic differences were similar among victims of mass murder committed with means other than firearms for Black, Asian, and White individuals. These findings highlight different areas of victimology within the context of these incidents.

Background: Local gyrification index (lGI), indicative of the degree of cortical folding is a proxy marker for early cortical neurodevelopmental abnormalities. We studied the difference in lGI between those who do and do not convert to psychosis (non-converters) in a clinical high-risk (CHR) cohort, and whether lGI predicts conversion to psychosis.Methods: Seventy-two CHR participants with attenuated positive symptom syndrome were followed up for two years. The difference in baseline whole-brain lGI was examined on the T1-weighted MRIs between, i)CHR (N = 72) and healthy controls (N = 19), ii)Converters to psychosis (N = 24) and non-converters (N = 48), adjusting for age and sex, on Freesurfer-6.0. The significant cluster obtained in the converters versus non-converters com-parison was registered as a region of interest to individual images of all 72 participants and lGI values were extracted from this region. A cox proportional hazards model was applied with these values to study whether lGI predicts conversion to psychosis.Results: lGI was not different between CHR and healthy controls. lGI was increased in converters in the right -sided inferior parietal and lateral occipital areas (corrected cluster-wise -p-value = 0.009, cohen's f = 0.42) compared to non-converters, which significantly increased the risk of onset of psychosis (p = 0.029, hazard ratio = 1.471).Conclusions: Increased gyrification in the right-sided inferior parietal and lateral occipital area differentiates converters to psychosis in CHR, significantly increasing the risk of conversion to psychosis. This measure may reflect underlying traits in parts of the brain that develop earliest in-utero (parietal and occipital), conferring a heightened vulnerability to convert to syndromal psychosis subsequently.

Given the polygenic nature of antipsychotic-induced weight gain (AIWG), we investigated whether polygenic risk scores (PRS) for various psychiatric and metabolic traits were associated with AIWG. We included individuals with schizophrenia (SCZ) of European ancestry from two cohorts (N = 151, age = 40.3 ± 11.8 and N = 138, age = 36.5 ± 10.8). We investigated associations of AIWG defined as binary and continuous variables with PRS calculated from genome-wide association studies of body mass index (BMI), coronary artery disease (CAD), fasting glucose, fasting insulin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides, type 1 and 2 diabetes mellitus, and SCZ, using regression models. We observed nominal associations (uncorrected p < 0.05) between PRSs for BMI, CAD, and LDL-C, type 1 diabetes, and SCZ with AIWG. While results became non-significant after correction for multiple testing, these preliminary results suggest that PRS analyses might contribute to identifying risk factors of AIWG and might help to elucidate mechanisms at play in AIWG.

Duration of untreated psychosis (DUP) is defined as the time from the onset of psychotic symptoms until the first treatment. Studies have shown that longer DUP is associated with poorer response rates to antipsychotic medications and impaired cognition, yet the neurobiologic correlates of DUP are poorly understood. Moreover, it has been hypothesized that untreated psychosis may be neurotoxic. Here, we conducted a comprehensive review of studies that have examined the neurobiology of DUP. Specifically, we included studies that evaluated DUP using a range of neurobiologic and imaging techniques and identified 83 articles that met inclusion and exclusion criteria. Overall, 27 out of the total 83 studies (32.5%) reported a significant neurobiological correlate with DUP. These results provide evidence against the notion of psychosis as structurally or functionally neurotoxic on a global scale and suggest that specific regions of the brain, such as temporal regions, may be more vulnerable to the effects of DUP. It is also possible that current methodologies lack the resolution needed to more accurately examine the effects of DUP on the brain, such as effects on synaptic density. Newer methodologies, such as MR scanners with stronger magnets, PET imaging with newer ligands capable of measuring subcellular structures (e.g., the PET ligand [11C]UCB-J) may be better able to capture these limited neuropathologic processes. Lastly, to ensure robust and replicable results, future studies of DUP should be adequately powered and specifically designed to test for the effects of DUP on localized brain structure and function with careful attention paid to potential confounds and methodological issues.

The phenotype of schizophrenia, regardless of etiology, represents the most studied psychotic disorder with respect to neurobiology and distinct phases of illness. The early phase of illness represents a unique opportunity to provide effective and individualized interventions that can alter illness trajectories. Developmental age and illness stage, including temporal variation in neurobiology, can be targeted to develop phase-specific clinical assessment, biomarkers, and interventions. We review an earlier model whereby an initial glutamate signaling deficit progresses through different phases of allostatic adaptation, moving from potentially reversible functional abnormalities associated with early psychosis and working memory dysfunction, and ending with difficult-to-reverse structural changes after chronic illness. We integrate this model with evidence of dopaminergic abnormalities, including cortical D1 dysfunction, which develop during adolescence. We discuss how this model and a focus on a potential critical window of intervention in the early stages of schizophrenia impact the approach to research design and clinical care. This impact includes stage-specific considerations for symptom assessment as well as genetic, cognitive, and neurophysiological biomarkers. We examine how phase-specific biomarkers of illness phase and brain development can be incorporated into current strategies for large-scale research and clinical programs implementing coordinated specialty care. We highlight working memory and D1 dysfunction as early treatment targets that can substantially affect functional outcome.

This study examines the association between increased hippocampal glutamate and higher total positive symptom severity in converters to psychosis.