Direct interrogation of context-dependent GPCR activity with a universal biosensor platform.

G protein-coupled receptors (GPCRs) are the largest family of druggable proteins encoded in the human genome, but progress in understanding and targeting them is hindered by the lack of tools to reliably measure their nuanced behavior in physiologically relevant contexts. Here, we developed a collection of compact ONE vector G-protein Optical (ONE-GO) biosensor constructs as a scalable platform that can be conveniently deployed to measure G-protein activation by virtually any GPCR with high fidelity even when expressed endogenously in primary cells. By characterizing dozens of GPCRs across many cell types like primary cardiovascular cells or neurons, we revealed insights into the molecular basis for G-protein coupling selectivity of GPCRs, pharmacogenomic profiles of anti-psychotics on naturally occurring GPCR variants, and G-protein subtype signaling bias by endogenous GPCRs depending on cell type or upon inducing disease-like states. In summary, this open-source platform makes the direct interrogation of context-dependent GPCR activity broadly accessible.

Predictive Processing: A Circuit Approach to Psychosis.

Predictive processing is a computational framework that aims to explain how the brain processes sensory information by making predictions about the environment and minimizing prediction errors. It can also be used to explain some of the key symptoms of psychotic disorders such as schizophrenia. In recent years, substantial advances have been made in our understanding of the neuronal circuitry that underlies predictive processing in cortex. In this review, we summarize these findings and how they might relate to psychosis and to observed cell type-specific effects of antipsychotic drugs. We argue that quantifying the effects of antipsychotic drugs on specific neuronal circuit elements is a promising approach to understanding not only the mechanism of action of antipsychotic drugs but also psychosis. Finally, we outline some of the key experiments that should be done. The aims of this review are to provide an overview of the current circuit-based approaches to psychosis and to encourage further research in this direction.

Multilayer network analysis reveals instability of brain dynamics in untreated first-episode schizophrenia.

Although aberrant static functional brain network activity has been reported in schizophrenia, little is known about how the dynamics of neural function are altered in first-episode schizophrenia and are modulated by antipsychotic treatment. The baseline resting-state functional magnetic resonance imaging data were acquired from 122 first-episode drug-naïve schizophrenia patients and 128 healthy controls (HCs), and 44 patients were rescanned after 1-year of antipsychotic treatment. Multilayer network analysis was applied to calculate the network switching rates between brain states. Compared to HCs, schizophrenia patients at baseline showed significantly increased network switching rates. This effect was observed mainly in the sensorimotor (SMN) and dorsal attention networks (DAN), and in temporal and parietal regions at the nodal level. Switching rates were reduced after 1-year of antipsychotic treatment at the global level and in DAN. Switching rates at baseline at the global level and in the inferior parietal lobule were correlated with the treatment-related reduction of negative symptoms. These findings suggest that instability of functional network activity plays an important role in the pathophysiology of acute psychosis in early-stage schizophrenia. The normalization of network stability after antipsychotic medication suggests that this effect may represent a systems-level mechanism for their therapeutic efficacy.

NMDA glutamate receptor antagonist MK-801 induces proteome changes in adult human brain slices which are partially counteracted by haloperidol and clozapine.

Deciphering the molecular pathways associated with N-methyl-D-aspartate receptor (NMDAr) hypofunction and its interaction with antipsychotics is necessary to advance our understanding of the basis of schizophrenia, as well as our capacity to treat this disease. In this regard, the development of human brain-derived models that are amenable to studying the neurobiology of schizophrenia may contribute to filling the gaps left by the widely employed animal models. Here, we assessed the proteomic changes induced by the NMDA glutamate receptor antagonist MK-801 on human brain slice cultures obtained from adult donors submitted to respective neurosurgery. Initially, we demonstrated that MK-801 diminishes NMDA glutamate receptor signaling in human brain slices in culture. Next, using mass-spectrometry-based proteomics and systems biology in silico analyses, we found that MK-801 led to alterations in proteins related to several pathways previously associated with schizophrenia pathophysiology, including ephrin, opioid, melatonin, sirtuin signaling, interleukin 8, endocannabinoid, and synaptic vesicle cycle. We also evaluated the impact of both typical and atypical antipsychotics on MK-801-induced proteome changes. Interestingly, the atypical antipsychotic clozapine showed a more significant capacity to counteract the protein alterations induced by NMDAr hypofunction than haloperidol. Finally, using our dataset, we identified potential modulators of the MK-801-induced proteome changes, which may be considered promising targets to treat NMDAr hypofunction in schizophrenia. This dataset is publicly available and may be helpful in further studies aimed at evaluating the effects of MK-801 and antipsychotics in the human brain.

Antipsychotic drugs in first-episode psychosis: a target trial emulation in the FEP-CAUSAL Collaboration.

Good adherence to antipsychotic therapy helps prevent relapses in first-episode psychosis (FEP). We used data from the FEP-CAUSAL Collaboration, an international consortium of observational cohorts, to emulate a target trial comparing antipsychotics, with treatment discontinuation as the primary outcome. Other outcomes included all-cause hospitalization. We benchmarked our results to estimates from the European First Episode Schizophrenia Trial, a randomized trial conducted in the 2000s. We included 1097 patients with a psychotic disorder and less than 2 years since psychosis onset. Inverse-probability weighting was used to control for confounding. The estimated 12-month risks of discontinuation for aripiprazole, first-generation agents, olanzapine, paliperidone, quetiapine, and risperidone were 61.5% (95% CI, 52.5-70.6), 73.5% (95% CI, 60.5-84.9), 76.8% (95% CI, 67.2-85.3), 58.4% (95% CI, 40.4-77.4), 76.5% (95% CI, 62.1-88.5), and 74.4% (95% CI, 67.0-81.2), respectively. Compared with aripiprazole, the 12-month risk differences were -15.3% (95% CI, -30.0 to 0.0) for olanzapine, -12.8% (95% CI, -25.7 to -1.0) for risperidone, and 3.0% (95% CI, -21.5 to 30.8) for paliperidone. The 12-month risks of hospitalization were similar between agents. Our estimates support use of aripiprazole and paliperidone as first-line therapies for FEP. Benchmarking yielded similar results for discontinuation and absolute risks of hospitalization as in the original trial, suggesting that data from the FEP-CAUSAL Collaboration sufficed to remove confounding for these clinical questions. This article is part of a Special Collection on Mental Health.

Use of Model-Informed Drug Development to Streamline Development of Long-Acting Products: Can These Successes Be Translated to Long-Acting Hormonal Contraceptives?

Long-acting contraceptives are the most effective reversible contraceptive methods. Increasing patients' access to these contraceptives may translate into fewer unintended pregnancies and lead to substantial individual and public health benefits. However, development of long-acting products can be complex and challenging. This review provides (a) an overview of representative development programs for long-acting antipsychotics as cases for conceptual translation to long-acting contraceptives, (b) several case examples on how modeling and simulation have been used to streamline the development of long-acting products, and (c) examples of challenges andopportunities in developing long-acting contraceptives and information on how exposure-response relationships of commonly used progestins may enable regulators and developers to rely on prior findings of effectiveness and safety from an approved contraceptive to streamline the development of long-acting contraceptives. The US Food and Drug Administration is seeking assistance from stakeholders to provide data from studies in which pharmacokinetic and pharmacodynamic or clinical outcomes of hormonal contraceptives were evaluated and not previously submitted.

Efficacy difference of antipsychotics in Alzheimer's disease and schizophrenia: explained with network efficiency and pathway analysis methods.

Approximately 50% of Alzheimer's disease (AD) patients will develop psychotic symptoms and these patients will experience severe rapid cognitive decline compared with those without psychosis (AD-P). Currently, no medication has been approved by the Food and Drug Administration for AD with psychosis (AD+P) specifically, although atypical antipsychotics are widely used in clinical practice. These drugs have demonstrated modest efficacy in managing psychosis in individuals with AD, with an increased frequency of adverse events, including excess mortality. We compared the differences between the genetic variations/genes associated with AD+P and schizophrenia from existing Genome-Wide Association Study and differentially expressed genes (DEGs). We also constructed disease-specific protein-protein interaction networks for AD+P and schizophrenia. Network efficiency was then calculated to characterize the topological structures of these two networks. The efficiency of antipsychotics in these two networks was calculated. A weight adjustment based on binding affinity to drug targets was later applied to refine our results, and 2013 and 2123 genes were identified as related to AD+P and schizophrenia, respectively, with only 115 genes shared. Antipsychotics showed a significantly lower efficiency in the AD+P network than in the schizophrenia network (P < 0.001) indicating that antipsychotics may have less impact in AD+P than in schizophrenia. AD+P may be caused by mechanisms distinct from those in schizophrenia which result in a decreased efficacy of antipsychotics in AD+P. In addition, the network analysis methods provided quantitative explanations of the lower efficacy of antipsychotics in AD+P.

Isolated central hypothyroidism: Underlying pathophysiology and relation to antidepressant and antipsychotic medications-A multi-centre South Wales study.

OBJECTIVE: Isolated biochemical central hypothyroidism is a presentation we are experiencing more frequently as endocrinologists, with variation in levels of investigation between physicians. We therefore conducted research to investigate the final diagnosis and clinical outcome of patients across multiple hospitals in South Wales with biochemical isolated central hypothyroidism; namely to establish whether this isolated biochemical picture was clinically significant. We also analysed whether there is an association between this biochemical picture and treatment with antidepressant and antipsychotic medications, and how common this is. DESIGN: We performed a retrospective observational study of patients across nine different hospitals in South Wales. We analysed patients referred to endocrinology at each site over a 6-year period with unexplained isolated biochemical central hypothyroidism. MATERIALS AND METHODOLOGY: 1022 individual patients' thyroid function test results were identified from our biochemical database using our inclusion criteria. After exclusion criteria were applied, 71 patients' results were analysed as to the final pathophysiology of their central hypothyroidism. RESULT: Of the 71 patients included in the study, none were found to have any clinically significant pathology on pituitary imaging. On reviewing their medications, 46/71 (65%) were found to be taking psychotropic medications. CONCLUSIONS: Our study strongly suggests isolated central hypothyroidism, in the absence of other pituitary hormone dysfunction or visual field defect, does not require further investigation, saving resources as well as sparing patients unnecessary anxiety. It also strongly supports a relationship between patients taking psychotropic medications and biochemical isolated central hypothyroidism, an association only described in a very limited amount of literature before this, and further supporting our previous single-centre study findings. The mechanism behind this is likely to be the suppression of thyrotropin secretion via antagonism of the dopamine-serotoninergic pathway. In our opinion, patients found to have isolated biochemical central hypothyroidism who are taking psychotropic medications can therefore be regarded to have a recognised cause for this biochemical finding and do not require further radiological investigation.

Outpatient Antipsychotic Use and Severe COVID-19: Avoiding the Impact of Age in a Real-World Data Study.

BACKGROUND: The association between use of antipsychotics and COVID-19 outcomes is inconsistent, which may be linked to use of these drugs in age-related diseases. Furthermore, there is little evidence regarding their effect in the nongeriatric population. We aim to assess the association between antipsychotic use and risk of disease progression and hospitalization due to COVID-19 among the general population, stratifying by age. METHODS: We conducted a population-based, multiple case-control study to assess risk of hospitalization, with cases being patients with a PCR(+) test who required hospitalization and controls being individuals without a PCR(+) test; and risk of progression to hospitalization, with cases being the same as those used in the hospitalization substudy and controls being nonhospitalized PCR(+) patients. We calculated adjusted odds-ratios (aOR) and 95% confidence intervals (CI), both overall and stratified by age. RESULTS: Antipsychotic treatment in patients younger than 65 years was not associated with a higher risk of hospitalization due to COVID-19 (aOR 0.94 [95%CI = 0.69-1.27]) and disease progression among PCR(+) patients (aOR 0.96 [95%CI = 0.70-1.33]). For patients aged 65 years or older, however, there was a significant, increased risk of hospitalization (aOR 1.58 [95% CI = 1.38-1.80]) and disease progression (aOR 1.31 [95% CI = 1.12-1.55]). CONCLUSIONS: The results of our large-scale real-world data study suggest that antipsychotic use is not associated with a greater risk of hospitalization due to COVID-19 and progression to hospitalization among patients younger than 65 years. The effect found in the group aged 65 years or older might be associated with off-label use of antipsychotics.

The incidence risk of gynecological cancer by antipsychotic use: a meta-analysis of 50,402 patients.

BACKGROUND: Female gynecological cancers represent a serious public health problem, with 1,398,601 new diagnoses and 671,875 deaths per year worldwide. Antipsychotics are often used in psychiatric disorders, including schizophrenia, bipolar disorder, and major depression. It is estimated that the prescription of these drugs is linked to 1,800 deaths a year in the United States, but their association with cancer remains controversial. METHODS: We searched PubMed, Scopus, and Web of Science databases for studies reporting the correlation in the incidence risk of gynecological cancer by antipsychotic use. We used DerSimonian and Laird random-effect models to compute logit transformed odds ratio (OR) for the primary binary endpoint with 95% confidence interval (CI). Heterogeneity was assessed through effect size width along with I-squared and Tau-squared statistics. Review Manager 5.4.1. was used for statistical analyses. A p-value of < 0.05 denoted statistically significant. RESULTS: 50,402 patients were included, of whom 778 (1,54%) took antipsychotic medication for at least 1 year. 1,086 (2,15%) with ovarian cancer and 49,316 (97,85%) with endometrial cancer. Antipsychotic use (OR 1.50; 1.06 to 2.13 95% CI; p-value 0.02), hypertension (OR 1.50; 95% CI 1.06 to 2.13; p-value < 0.01), nulliparity (OR 1.98; 95% CI 1.53 to 2.57; p-value < 0.01) and multiparity (OR 0.53; 95% CI 0.41 to 0.69; p-value < 0.01) showed significantly different distributions between groups of cancer and cancer-free patients. The primary endpoint of incidence risk of gynecological cancer by antipsychotic therapy showed a statistically significant difference (OR 1.67; 95% CI 1.02 to 2.73; p-value < 0.05) against the use of antipsychotic drugs. CONCLUSIONS: Our meta-analysis showed that the use of antipsychotic drugs increases the risk of gynecological cancers, particularly endometrial cancer. This result should be weighed against the potential effects of treatment for a balanced prescribing decision.

Identifying clinically relevant agranulocytosis in people registered on the UK clozapine Central Non-Rechallenge Database: retrospective cohort study.

BACKGROUND: Clozapine is the most effective antipsychotic for treatment-resistant psychosis. However, clozapine is underutilised in part because of potential agranulocytosis. Accumulating evidence indicates that below-threshold haematological readings in isolation are not diagnostic of life-threatening clozapine-induced agranulocytosis (CIA). AIMS: To examine the prevalence and timing of CIA using different diagnostic criteria and to explore demographic differences of CIA in patients registered on the UK Central Non-Rechallenge Database (CNRD). METHOD: We analysed data of all patients registered on the UK Clozaril® Patient Monitoring Service Central Non-Rechallenge Database (at least one absolute neutrophil count (ANC) < 1.5 × 109/L and/or white blood cell count < 3.0 × 109/L) between May 2000 and February 2021. We calculated prevalence rates of agranulocytosis using threshold-based and pattern-based criteria, stratified by demographic factors (gender, age and ethnicity). Differences in epidemiology based on rechallenge status and clozapine indication were explored. The proportion of patients who recorded agranulocytosis from a normal ANC was explored. RESULTS: Of the 3029 patients registered on the CNRD with 283 726 blood measurements, 593 (19.6%) were determined to have threshold-based agranulocytosis and 348 (11.4%) pattern-based agranulocytosis. In the total sample (75 533), the prevalence of threshold-based agranulocytosis and pattern-based agranulocytosis was 0.8% and 0.5%, respectively. The median time to threshold-based agranulocytosis was 32 weeks (IQR 184) and 15 (IQR 170) weeks for pattern-based agranulocytosis. Among age groups, the prevalence of pattern-based agranulocytosis and threshold-based agranulocytosis was highest in the >48 age group. Prevalence rates were greatest for White (18%) and male individuals (13%), and lowest for Black individuals (0.1%). The proportion of people who were determined to have pattern-based agranulocytosis without passing through neutropenia was 70%. CONCLUSIONS: Threshold-based definition of agranulocytosis may over-diagnose CIA. Monitoring schemes should take into consideration neutrophil patterns to correctly identify clinically relevant CIA. In marked contrast to previous studies, CIA occurred least in Black individuals and most in White individuals.

Measuring the impact of therapy on medication use: data-linkage study.

BACKGROUND: The psychological therapies service (PTS) in the Northern Health and Social Care Trust, in Northern Ireland, provides therapies to adults with moderate or severe mental health difficulties. Psychometric outcomes data are routinely collected to assess if a patient demonstrates significant improvement in their main presenting problem area following therapy. The wider impact of therapy is not fully measured in the outcomes database as this would be disproportionately burdensome for both patient and therapist. The present study, to our knowledge, is the first to use data linkage to link patient therapy outcomes data with prescriptions data. AIMS: To widen our understanding of patient medication use before and after therapy. METHOD: Using Health and Care Number as a unique identifier, the Psychological Therapies Service - Routine Outcome Measurement Database (n = 3625) and data from 72 500 controls were linked with data from the Enhanced Prescribing Database (EPD). The EPD data were sourced from the Honest Broker Service. RESULTS: Key findings from the study were: (a) the odds of PTS clients using antipsychotics in the year before therapy were 25 times greater compared with controls (odds ratio (OR) = 24.53, 95% CI 20.16-29.84); (b) in the 1st year post discharge, PTS clients who clinically improved post therapy discharge were more likely than 'non-engagers' and 'non-improvers' to come off antianxiety medication (OR = 0.61, 95%, CI 0.38-0.98); and (c) therapy did not have an impact on antidepressant use. CONCLUSIONS: The results highlight the need for discussion between therapy services, GPs and psychiatry about whether more engagement and collaboration is needed to plan phased reduction in medication.

Clozapine, relapse, and adverse events: a 10-year electronic cohort study in Canada.

BACKGROUND: Clozapine is the most effective medication for treatment-resistant psychoses, but the balance of benefits and risks is understudied in real-world settings. AIMS: To examine the relative re-hospitalisation rates for mental health relapse and adverse events associated with clozapine and other antipsychotics in adult and child/youth cohorts. METHOD: Data were obtained from the Canadian Institute of Health Information for adults (n = 45 616) and children/youth (n = 1476) initially hospitalised for mental health conditions in British Columbia, Manitoba and Saskatchewan from 2008 to 2018. Patient demographics and hospitalisations were linked with antipsychotic prescriptions dispensed following the initial visit. Recurrent events survival analysis for relapse and adverse events were created and compared between clozapine and other antipsychotics. RESULTS: In adults, clozapine was associated with a 14% lower relapse rate versus other drugs (adjusted hazard ratio: 0.86, 95% CI: 0.83-0.90) over the 10-year follow-up. In the first 21 months, the relapse rate was higher for clozapine but then reversed. Over 1000 person-months, clozapine-treated adults could be expected to have 38 relapse hospitalisations compared with 45 for other drugs. In children/youth, clozapine had a 38% lower relapse rate compared with other antipsychotic medications (adjusted hazard ratio: 0.62, 95% CI: 0.49-0.78) over the follow-up period. This equates to 29 hospitalisations for clozapine and 48 for other drugs over 1000 person-months. In adults, clozapine had a higher risk for adverse events (hazard ratio: 1.34, 95% CI: 1.18-1.54) over the entire follow-up compared with other antipsychotics. This equates to 1.77 and 1.30 hospitalisations over 1000 person-months for clozapine and other drugs, respectively. CONCLUSIONS: Clozapine was associated with lower relapse overall, but this was accompanied by higher adverse events for adults. For children/youth, clozapine was associated with lower relapse all throughout and had no difference in adverse events compared with other antipsychotics.

Use of antipsychotic medication, benzodiazepines, and psychiatric hospitalization in cannabis-related versus cannabis-unrelated schizophrenia - a nationwide, register-based cohort study.

BACKGROUND: Evidence suggests that cannabis may be a causal factor for development of schizophrenia. We aimed to investigate whether use of antipsychotic medication, benzodiazepines, and psychiatric service use differs among patients with schizophrenia depending on whether psychosis was precipitated by a diagnosis of cannabis use disorder (CUD). METHODS: We utilized the nationwide Danish registries to identify all individuals with an incident diagnosis of schizophrenia from 1995 to 2016. We also collected information on whether first CUD diagnosis preceded schizophrenia and thus defined a group of potentially cannabis-related schizophrenia. We compared the cannabis-related schizophrenia group both with all non-cannabis-related patients with schizophrenia and with non-cannabis-related patients with schizophrenia that were propensity-score matched to cases using a range of potentially confounding variables. RESULTS: We included 35 714 people with incident schizophrenia, including 4116 (11.5%) that were cannabis-related. In the unmatched-comparison analyses, there were no clear differences over time in use of antipsychotics and benzodiazepines related to whether the diagnosis of schizophrenia was cannabis-related. After propensity-score matching, use of antipsychotics and benzodiazepines was significantly lower among cannabis-related cases of schizophrenia. In the unmatched comparison, the cannabis-related group had significantly more days admitted than the non-cannabis-related group. This was markedly attenuated after propensity-score matching. CONCLUSIONS: Our findings indicate the importance of considering cannabis-related cases of schizophrenia as a potentially distinct disorder in terms of prognosis. It is unclear, however, if these differences are due to different biological types of schizophrenia being compared or if they rather indicate behavioral differences such as reduced adherence and treatment-seeking.

Deprescribing antipsychotics in patients with schizophrenia: findings from a specialized clinic.

BACKGROUND: While antipsychotic medication reduces the risk of relapse for patients with schizophrenia, high prevalence of adverse effects results in low adherence. Lower doses of antipsychotics have been associated with increased level of function but also with increased risk of relapse. This study presents findings from a specialized deprescribing clinic. In addition, we aim to identify clinical predictors for relapse. METHODS: Patients diagnosed with schizophrenia were referred to the clinic, which offers a six-month guided tapering program. Antipsychotic dose was reduced by 10% every four weeks. Patients were monitored closely for symptom progression or decrease in level of function, with defined cut-offs prompting a pause in or cessation of dose reduction. RESULTS: After 12 months, the antipsychotic dose was reduced from 404 (±320 mg) to 255 (±236 mg) chlorpromazine equivalent. Of the 88 patients included, 22 (27%) experienced relapse during the six-month tapering period, while 29 (37%) experienced relapse at the 12-month follow-up visit and nine patients were antipsychotic free. Patients who remained stable experienced a slightly increased level of functioning and markedly fewer side effects (p < 0.001). Following relapse, patients were clinically stabilized and showed an improved attitude toward antipsychotic medication. The predictive models were weak. CONCLUSIONS: We show that most patients undergoing guided antipsychotic tapering remained stable after one year and improved in level of function, while most patients who relapsed were quickly stabilized. Our inability to create strong predictive models could be due to limitations in the study design, warranting future studies exploring tapering of antipsychotics in patients with schizophrenia.

Cardiotoxic effects of common and emerging drugs: role of cannabinoid receptors.

Drug-induced cardiotoxicity has become one of the most common and detrimental health concerns, which causes significant loss to public health and drug resources. Cannabinoid receptors (CBRs) have recently achieved great attention for their vital roles in the regulation of heart health and disease, with mounting evidence linking CBRs with the pathogenesis and progression of drug-induced cardiotoxicity. This review aims to summarize fundamental characteristics of two well-documented CBRs (CB1R and CB2R) from aspects of molecular structure, signaling and their functions in cardiovascular physiology and pathophysiology. Moreover, we describe the roles of CB1R and CB2R in the occurrence of cardiotoxicity induced by common drugs such as antipsychotics, anti-cancer drugs, marijuana, and some emerging synthetic cannabinoids. We highlight the 'yin-yang' relationship between CB1R and CB2R in drug-induced cardiotoxicity and propose future perspectives for CBR-based translational medicine toward cardiotoxicity curation and clinical monitoring.

Differential Effects of Neonatal Ventral Hippocampus Lesion on Behavior and Corticolimbic Plasticity in Wistar-Kyoto and Spontaneously Hypertensive Rats.

Dysfunction of the corticolimbic system, particularly at the dendritic spine level, is a recognized core mechanism in neurodevelopmental disorders such as schizophrenia. Neonatal ventral hippocampus lesion (NVHL) in Sprague-Dawley rats induces both a schizophrenia-related behavioral phenotype and dendritic spine pathology (reduced total number and mature spines) in corticolimbic areas, which is mitigated by antipsychotics. However, there is limited information on the impact of rat strain on NVHL outcomes and antipsychotic effects. We compared the behavioral performance in the open field, novel object recognition (NORT), and social interaction tests, as well as structural neuroplasticity with the Golgi-Cox stain in Wistar-Kyoto (WKY) and spontaneously hypertensive (SH) male rats with and without NVHL. Additionally, we explored the effect of the atypical antipsychotic risperidone (RISP). WKY rats with NVHL displayed motor hyperactivity without impairments in memory and social behavior, accompanied by dendritic spine pathology in the neurons of the prefrontal cortex (PFC) layer 3 and basolateral amygdala. RISP treatment reduced motor activity and had subtle and selective effects on the neuroplasticity alterations. In SH rats, NVHL increased the time spent in the border area during the open field test, impaired the short-term performance in NORT, and reduced social interaction time, deficits that were corrected after RISP administration. The NVHL caused dendritic spine pathology in the PFC layers 3 and 5 of SH rats, which RISP treatment ameliorated. Our results support the utility of the NVHL model for exploring neuroplasticity mechanisms in schizophrenia and understanding pharmacotherapy.

Patterns of pharmacotherapy for bipolar disorder: A GBC survey.

OBJECTIVES: To understand treatment practices for bipolar disorders (BD), this study leveraged the Global Bipolar Cohort collaborative network to investigate pharmacotherapeutic treatment patterns in multiple cohorts of well-characterized individuals with BD in North America, Europe, and Australia. METHODS: Data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities were provided from each participating cohort. Individual site and regional pooled proportional meta-analyses with generalized linear mixed methods were conducted to identify prescription patterns. RESULTS: This study included 10,351 individuals from North America (n = 3985), Europe (n = 3822), and Australia (n = 2544). Overall, participants were predominantly female (60%) with BD-I (60%; vs. BD-II = 33%). Cross-sectionally, mood-stabilizing anticonvulsants (44%), second-generation antipsychotics (42%), and antidepressants (38%) were the most prescribed medications. Lithium was prescribed in 29% of patients, primarily in the Australian (31%) and European (36%) cohorts. First-generation antipsychotics were prescribed in 24% of the European versus 1% in the North American cohort. Antidepressant prescription rates were higher in BD-II (47%) compared to BD-I (35%). Major limitations were significant differences among cohorts based on inclusion/exclusion criteria, data source, and time/year of enrollment into cohort. CONCLUSIONS: Mood-stabilizing anticonvulsants, second-generation antipsychotics, and antidepressants were the most prescribed medications suggesting prescription patterns that are not necessarily guideline concordant. Significant differences exist in the prescription practices across different geographic regions, especially the underutilization of lithium in the North American cohorts and the higher utilization of first-generation antipsychotics in the European cohorts. There is a need to conduct future longitudinal studies to further explore these differences and their impact on outcomes, and to inform and implement evidence-based guidelines to help improve treatment practices in BD.

Predicting remission after acute phase pharmacotherapy in patients with bipolar I depression: A machine learning approach with cross-trial and cross-drug replication.

OBJECTIVES: Interpatient variability in bipolar I depression (BP-D) symptoms challenges the ability to predict pharmacotherapeutic outcomes. A machine learning workflow was developed to predict remission after 8 weeks of pharmacotherapy (total score of ≤8 on the Montgomery Åsberg Depression Rating Scale [MADRS]). METHODS: Supervised machine learning models were trained on data from BP-D patients treated with olanzapine (N = 168) and were externally validated on patients treated with olanzapine/fluoxetine combination (OFC; N = 131) and lamotrigine (LTG; N = 126). Top predictors were used to develop a prognosis rule informing how many symptoms should change and by how much within 4 weeks to increase the odds of achieving remission. RESULTS: An AUC of 0.76 (NIR:0.59; p = 0.17) was established to predict remission in olanzapine-treated subjects. These trained models achieved AUCs of 0.70 with OFC (NIR:0.52; p < 0.03) and 0.73 with LTG (NIR:0.52; p < 0.003), demonstrating external replication of prediction performance. Week-4 changes in four MADRS symptoms (reported sadness, reduced sleep, reduced appetite, and concentration difficulties) were top predictors of remission. Across all pharmacotherapies, three or more of these symptoms needed to improve by ≥2 points at Week-4 to have a 65% chance of achieving remission at 8 weeks (OR: 3.74, 95% CI: 2.45-5.76; p < 9.3E-11). CONCLUSION: Machine learning strategies achieved cross-trial and cross-drug replication in predicting remission after 8 weeks of pharmacotherapy for BP-D. Interpretable prognoses rules required only a limited number of depressive symptoms, providing a promising foundation for developing simple quantitative decision aids that may, in the future, serve as companions to clinical judgment at the point of care.

Early use of long-acting injectable antipsychotics in bipolar disorder type I: An expert consensus.

INTRODUCTION: Long-acting injectable antipsychotics (LAIs) are not routinely offered to patients living with bipolar disorder type I (BP-I), despite widespread evidence that supports their benefits over oral antipsychotics, particularly in early disease. METHODS: A round-table meeting of psychiatrists convened to discuss barriers and opportunities and provide consensus recommendations around the early use of LAIs for BP-I. RESULTS: LAIs are rarely prescribed to treat BP-I unless a patient has severe symptoms, sub-optimal adherence to oral antipsychotics, or has experienced multiple relapses. Beyond country-specific accessibility issues (e.g., healthcare infrastructure and availability/approval status), primary barriers to the effective use of LAIs were identified as attitudinal and knowledge/experience-based. Direct discussions between healthcare providers and patients about treatment preferences may not occur due to a preconceived notion that patients prefer oral antipsychotics. Moreover, as LAIs have historically been limited to the treatment of schizophrenia and the most severe cases of BP-I, healthcare providers might be unaware of the benefits LAIs provide in the overall management of BP-I. Improved treatment adherence associated with LAIs compared to oral antipsychotics may support improved outcomes for patients (e.g., reduced relapse and hospitalization). Involvement of all stakeholders (healthcare providers, patients, and their supporters) participating in the patient journey is critical in early and shared decision-making processes. Clinical and database studies could potentially bridge knowledge gaps to facilitate acceptance of LAIs. CONCLUSION: This review discusses the benefits of LAIs in the management of BP-I and identifies barriers to use, while providing expert consensus recommendations for potential solutions to support informed treatment decision-making.