Real-world effectiveness of antidepressants, antipsychotics and their combinations in the maintenance treatment of psychotic depression. Evidence from within-subject analyses of two nationwide cohorts.

Psychotic depression (PD) is a severe mental disorder leading to functional disability and high risk of suicide, but very little is known about the comparative effectiveness of medications used in its maintenance treatment. The objective of this study was to investigate the comparative effectiveness of specific antipsychotics and antidepressants, and their combinations, on the risk of psychiatric hospitalization among persons with PD in routine care. Persons aged 16-65 years with a first-time diagnosis of PD were identified from Finnish (years 2000-2018) and Swedish (years 2006-2021) nationwide registers of inpatient care, specialized outpatient care, sickness absence, and disability pension. The main exposures were specific antipsychotics and antidepressants, and the main outcome measure was psychiatric hospitalization as a marker of severe relapse. The risk of hospitalization associated with periods of use vs. non-use of medications (expressed as adjusted hazard ratio, aHR) was assessed by a within-individual design, using each individual as his/her own control, and analyzed with stratified Cox models. The two national cohorts were first analyzed separately, and then combined using a fixed-effect meta-analysis. The Finnish cohort included 19,330 persons (mean age: 39.8±14.7 years; 57.9% women) and the Swedish cohort 13,684 persons (mean age: 41.3±14.0 years; 53.5% women). Individual antidepressants associated with a decreased risk of relapse vs. non-use of antidepressants were bupropion (aHR=0.73, 95% CI: 0.63-0.85), vortioxetine (aHR=0.78, 95% CI: 0.63-0.96) and venlafaxine (aHR=0.92, 95% CI: 0.86-0.98). Any long-acting injectable antipsychotic (LAI) (aHR=0.60, 95% CI: 0.45-0.80) and clozapine (aHR=0.72, 95% CI: 0.57-0.91) were associated with a decreased risk of relapse vs. non-use of antipsychotics. Among monotherapies, only vortioxetine (aHR=0.67, 95% CI: 0.47-0.95) and bupropion (aHR=0.71, 95% CI: 0.56-0.89) were associated with a significantly decreased risk of relapse vs. non-use of both antidepressants and antipsychotics. In an exploratory analysis of antidepressant-antipsychotic combinations, a decreased relapse risk was found for amitriptyline-olanzapine (aHR=0.45, 95% CI: 0.28-0.71), sertraline-quetiapine (aHR=0.79, 95% CI: 0.67-0.93) and venlafaxine-quetiapine (aHR=0.82, 95% CI: 0.73-0.91) vs. non-use of antidepressants and antipsychotics. Benzodiazepines and related drugs (aHR=1.29, 95% CI: 1.24-1.34) and mirtazapine (aHR=1.17, 95% CI: 1.07-1.29) were associated with an increased risk of relapse. These data indicate that, in the maintenance treatment of PD, bupropion, vortioxetine, venlafaxine, any LAI, clozapine, and only few specific antidepressant-antipsychotic combinations are associated with a decreased risk of relapse. These findings challenge the current recommendation by treatment guidelines to combine an antipsychotic with an antidepressant (without further specification) as standard treatment in PD.

Astrocytes Regulate Neuronal Network Burst Frequency Through NMDA Receptors in a Species- and Donor-Specific Manner.

Background: Development of synaptic activity is a key neuronal characteristic that relies largely on interactions between neurons and astrocytes. Although astrocytes have known roles in regulating synaptic function and malfunction, the use of human- or donor-specific astrocytes in disease models is still rare. Rodent astrocytes are routinely used to enhance neuronal activity in cell cultures, but less is known about how human astrocytes influence neuronal activity. Methods: We established human induced pluripotent stem cell-derived neuron-astrocyte cocultures and studied their functional development on microelectrode array. We used cell lines from 5 neurotypical control individuals and 3 pairs of monozygotic twins discordant for schizophrenia. A method combining NGN2 overexpression and dual SMAD inhibition was used for neuronal differentiation. The neurons were cocultured with human induced pluripotent stem cell-derived astrocytes differentiated from 6-month-old astrospheres or rat astrocytes. Results: We found that the human induced pluripotent stem cell-derived cocultures developed complex network bursting activity similar to neuronal cocultures with rat astrocytes. However, the effect of NMDA receptors on neuronal network burst frequency (NBF) differed between cocultures containing human or rat astrocytes. By using cocultures derived from patients with schizophrenia and unaffected individuals, we found lowered NBF in the affected cells. We continued by demonstrating how astrocytes from an unaffected individual rescued the lowered NBF in the affected neurons by increasing NMDA receptor activity. Conclusions: Our results indicate that astrocytes participate in the regulation of neuronal NBF through a mechanism that involves NMDA receptors. These findings shed light on the importance of using human and donor-specific astrocytes in disease modeling.

Nerve cell connections called synapses are formed in interaction with astrocytes, the main non-neuronal cell type of the brain. In vitro work commonly uses rodent astrocytes to enhance activity in human-derived neuronal cell cultures, but differences in using rodent versus human astrocytes are not well understood. We found that the electrical activity of nerve cell networks in cultures consisting of human cortical nerve cells and human astrocytes is altered when the astrocytes are from patients with schizophrenia, relative to neurotypical individuals. The effect of human astrocytes on these networks differed from rodent astrocytes, indicating the potential importance of a fully human culture system.

Antipsychotic medications and sleep problems in patients with schizophrenia.

BACKGROUND: Sleep problems are common and related to a worse quality of life in patients with schizophrenia. Almost all patients with schizophrenia use antipsychotic medications, which usually increase sleep. Still, the differences in subjective sleep outcomes between different antipsychotic medications are not entirely clear. METHODS: This study assessed 5466 patients with schizophrenia and is part of the nationwide Finnish SUPER study. We examined how the five most common antipsychotic medications (clozapine, olanzapine, quetiapine, aripiprazole, and risperidone) associate with questionnaire-based sleep problems in logistic regression analyses, including head-to-head analyses between different antipsychotic medications. The sleep problems were difficulties initiating sleep, early morning awakenings, fatigue, poor sleep quality, short (≤6 h) and long sleep duration (≥10 h). RESULTS: The average number of antipsychotic medications was 1.59 per patient. Clozapine was associated with long sleep duration (49.0 % of clozapine users vs 30.2 % of other patients, OR = 2.05, 95 % CI 1.83-2.30, p < .001). Olanzapine and risperidone were in head-to-head analyses associated with less sleep problems than patients using aripiprazole, quetiapine, or no antipsychotic medication. Aripiprazole and quetiapine were associated with more insomnia symptoms and poorer sleep quality. Patients without antipsychotic medications (N = 159) had poorer sleep quality than patients with antipsychotic use, and short sleep duration was common (21.5 % of patients using antipsychotics vs 7.8 % of patients using antipsychotics, OR = 2.97, 95 % CI 1.98-4.44, p < .001). CONCLUSIONS: Prevalence of sleep problems is markedly related to the antipsychotic medication the patient uses. These findings underline the importance of considering and assessing sleep problems when treating schizophrenia patients with antipsychotics.

Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia.

Schizophrenia (SCZ) is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. The etiology behind the disorder remains elusive although it is hypothesized to be associated with the aberrant response to neurotransmitters, such as dopamine and glutamate. Therefore, investigating the link between dysregulated metabolites and distorted neurodevelopment holds promise to offer valuable insights into the underlying mechanism of this complex disorder. In this study, we aimed to explore a presumed correlation between the transcriptome and the metabolome in a SCZ model based on patient-derived induced pluripotent stem cells (iPSCs). For this, iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at various developmental stages, reflecting neuroepithelial-like cells, radial glia, young and mature neurons. The samples were analyzed by both RNA-sequencing and targeted metabolomics and the two modalities were used to construct integrative networks in silico. This multi-omics analysis revealed significant perturbations in the polyamine and gamma-aminobutyric acid (GABA) biosynthetic pathways during rosette maturation in SCZ lines. We particularly observed the downregulation of the glutamate decarboxylase encoding genes GAD1 and GAD2, as well as their protein product GAD65/67 and their biochemical product GABA in SCZ samples. Inhibition of ornithine decarboxylase resulted in further decrease of GABA levels suggesting a compensatory activation of the ornithine/putrescine pathway as an alternative route for GABA production. These findings indicate an imbalance of cortical excitatory/inhibitory dynamics occurring during early neurodevelopmental stages in SCZ. Our study supports the hypothesis of disruption of inhibitory circuits to be causative for SCZ and establishes a novel in silico approach that enables for integrative correlation of metabolic and transcriptomic data of psychiatric disease models.

Antipsychotic Use and Risk of Breast Cancer in Women With Severe Mental Illness: Replication of a Nationwide Nested Case-Control Database Study.

BACKGROUND AND HYPOTHESIS: Breast cancer is more prevalent in women with severe mental illness than in the general population, and use of prolactin-increasing antipsychotics may be a contributing factor. STUDY DESIGN: A nested case-control study was conducted using the Swedish nationwide registers (inpatient/outpatient care, sickness absence, disability pension, prescribed drugs, cancers). All women aged 18-85 years with schizophrenia/schizoaffective/other nonaffective psychotic disorder/bipolar disorder and breast cancer (cases) were matched for age, primary psychiatric diagnosis, and disease duration with five women without cancer (controls). The association between cumulative exposure to prolactin-increasing/prolactin-sparing antipsychotics and breast cancer was analyzed using conditional logistic regression, adjusted for comorbidities and co-medications. STUDY RESULTS: Among 132 061 women, 1642 (1.24%) developed breast cancer between 2010 and 2021, at a mean age of 63.3 ±â€…11.8 years. Compared with 8173 matched controls, the odds of breast cancer increased in women with prior exposure to prolactin-increasing antipsychotics for 1-4 years (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI] = 1.03-1.41), and for ≥ 5 years (aOR = 1.47, 95%CI = 1.26-1.71). There were no increased or decreased odds of breast cancer with exposure to prolactin-sparing antipsychotics of either 1-4 years (aOR = 1.17, 95%CI = 0.98-1.40) or ≥5 years (aOR = 0.99, 95%CI = 0.78-1.26). The results were consistent across all sensitivity analyses (ie, according to different age groups, cancer types, and primary psychiatric diagnosis). CONCLUSIONS: Although causality remains uncertain, exposure to prolactin-elevating antipsychotics for ≥ 1 year was associated with increased odds of breast cancer in women with severe mental illness. When prescribing antipsychotics, a shared decision-making process should consider individual risk factors for breast cancer.

Genetic contribution to microglial activation in schizophrenia.

Several lines of evidence indicate the involvement of neuroinflammatory processes in the pathophysiology of schizophrenia (SCZ). Microglia are brain resident immune cells responding toward invading pathogens and injury-related products, and additionally, have a critical role in improving neurogenesis and synaptic functions. Aberrant activation of microglia in SCZ is one of the leading hypotheses for disease pathogenesis, but due to the lack of proper human cell models, the role of microglia in SCZ is not well studied. We used monozygotic twins discordant for SCZ and healthy individuals to generate human induced pluripotent stem cell-derived microglia to assess the transcriptional and functional differences in microglia between healthy controls, affected twins and unaffected twins. The microglia from affected twins had increased expression of several common inflammation-related genes compared to healthy individuals. Microglia from affected twins had also reduced response to interleukin 1 beta (IL1ß) treatment, but no significant differences in migration or phagocytotic activity. Ingenuity Pathway Analysis (IPA) showed abnormalities related to extracellular matrix signaling. RNA sequencing predicted downregulation of extracellular matrix structure constituent Gene Ontology (GO) terms and hepatic fibrosis pathway activation that were shared by microglia of both affected and unaffected twins, but the upregulation of major histocompatibility complex (MHC) class II receptors was observed only in affected twin microglia. Also, the microglia of affected twins had heterogeneous response to clozapine, minocycline, and sulforaphane treatments. Overall, despite the increased expression of inflammatory genes, we observed no clear functional signs of hyperactivation in microglia from patients with SCZ. We conclude that microglia of the patients with SCZ have gene expression aberrations related to inflammation response and extracellular matrix without contributing to increased microglial activation.

Development and Validation of a Machine Learning-Based Model of Mortality Risk in First-Episode Psychosis.

Importance: There is an absence of mortality risk assessment tools in first-episode psychosis (FEP) that could enable personalized interventions. Objective: To examine the feasibility of machine learning (ML) in discerning mortality risk in FEP and to assess whether such risk predictions can inform pharmacotherapy choices. Design, Setting, and Participants: In this prognostic study, Swedish nationwide cohort data (from July 1, 2006, to December 31, 2021) were harnessed for model development and validation. Finnish cohort data (from January 1, 1998, to December 31, 2017) were used for external validation. Data analyses were completed between December 2022 and December 2023. Main Outcomes and Measures: Fifty-one nationwide register variables, encompassing demographics and clinical and work-related histories, were subjected to ML to predict future mortality risk. The ML model's performance was evaluated by calculating the area under the receiver operating characteristic curve (AUROC). The comparative effectiveness of pharmacotherapies in patients was assessed and was stratified by the ML model to those with predicted high mortality risk (vs low risk), using the between-individual hazard ratio (HR). The 5 most important variables were then identified and a model was retrained using these variables in the discovery sample. Results: This study included 24 052 Swedish participants (20 000 in the discovery sample and 4052 in the validation sample) and 1490 Finnish participants (in the validation sample). Swedish participants had a mean (SD) age of 29.1 (8.1) years, 62.1% were men, and 418 died with 2 years. Finnish participants had a mean (SD) age of 29.7 (8.0) years, 61.7% were men, and 31 died within 2 years. The discovery sample achieved an AUROC of 0.71 (95% CI, 0.68-0.74) for 2-year mortality prediction. Using the 5 most important variables (ie, the top 10% [substance use comorbidities, first hospitalization duration due to FEP, male sex, prior somatic hospitalizations, and age]), the final model resulted in an AUROC of 0.70 (95% CI, 0.63-0.76) in the Swedish sample and 0.67 (95% CI, 0.56-0.78) in the Finnish sample. Individuals with predicted high mortality risk had an elevated 15-year risk in the Swedish sample (HR, 3.77 [95% CI, 2.92-4.88]) and an elevated 20-year risk in the Finnish sample (HR, 3.72 [95% CI, 2.67-5.18]). For those with predicted high mortality risk, long-acting injectable antipsychotics (HR, 0.45 [95% CI, 0.23-0.88]) and mood stabilizers (HR, 0.64 [95% CI, 0.46-0.90]) were associated with decreased mortality risk. Conversely, for those predicted to survive, only oral aripiprazole (HR, 0.38 [95% CI, 0.20-0.69]) and risperidone (HR, 0.38 [95% CI, 0.18-0.82]) were associated with decreased mortality risk. Conclusions and Relevance: In this prognostic study, an ML-based model was developed and validated to predict mortality risk in FEP. These findings may help to develop personalized interventions to mitigate mortality risk in FEP.

Genetic contribution to disease-course severity and progression in the SUPER-Finland study, a cohort of 10,403 individuals with psychotic disorders.

Genetic factors contribute to the susceptibility of psychotic disorders, but less is known how they affect psychotic disease-course development. Utilizing polygenic scores (PGSs) in combination with longitudinal healthcare data with decades of follow-up we investigated the contributing genetics to psychotic disease-course severity and diagnostic shifts in the SUPER-Finland study, encompassing 10 403 genotyped individuals with a psychotic disorder. To longitudinally track the study participants' past disease-course severity, we created a psychiatric hospitalization burden metric using the full-coverage and nation-wide Finnish in-hospital registry (data from 1969 and onwards). Using a hierarchical model, ranking the psychotic diagnoses according to clinical severity, we show that high schizophrenia PGS (SZ-PGS) was associated with progression from lower ranked psychotic disorders to schizophrenia (OR = 1.32 [1.23-1.43], p = 1.26e-12). This development manifested already at psychotic illness onset as a higher psychiatric hospitalization burden, the proxy for disease-course severity. In schizophrenia (n = 5 479), both a high SZ-PGS and a low educational attainment PGS (EA-PGS) were associated with increased psychiatric hospitalization burden (p = 1.00e-04 and p = 4.53e-10). The SZ-PGS and the EA-PGS associated with distinct patterns of hospital usage. In individuals with high SZ-PGS, the increased hospitalization burden was composed of longer individual hospital stays, while low EA-PGS associated with shorter but more frequent hospital visits. The negative effect of a low EA-PGS was found to be partly mediated via substance use disorder, a major risk factor for hospitalizations. In conclusion, we show that high SZ-PGS and low EA-PGS both impacted psychotic disease-course development negatively but resulted in different disease-course trajectories.

Association of antidepressant and benzodiazepine use, and anticholinergic burden with cognitive performance in schizophrenia.

Schizophrenia is characterized by cognitive impairment affecting everyday functioning. Earlier research has hypothesized that antidepressants may associate with better cognitive functioning, but results are mixed. This study explored the association between antidepressant use and cognitive performance in terms of reaction time and visual learning in a clinical sample. In addition, we examined benzodiazepine use and anticholinergic burden. Study participants were drawn from the SUPER-Finland cohort, collected among patients with psychotic illnesses in 2016-2018 throughout Finland (n = 10,410). The analysis included adults with a schizophrenia diagnosis (F20) and results from a cognitive assessment (n = 3365). Information about medications and psychosocial factors were gathered through questionnaire and interview. Cognitive performance was assessed with the Cambridge Neuropsychological Test Automated Battery (CANTAB) with two subtests measuring reaction time and visual learning. Almost 36 % of participants used at least one antidepressant. The use of antidepressants in general was not associated with performance in the reaction time and visual learning tasks. However, the use of SNRI antidepressants was associated with a faster reaction time. Benzodiazepine use and a higher anticholinergic burden were associated with poorer performance in both tests. The results strengthen earlier findings that there is no association between antidepressant use in general and cognitive performance in schizophrenia. However, the association of SNRI medications with a faster reaction time warrants further research. Moreover, the results suggest that more attention should be paid to the anticholinergic burden of the medications used by patients with schizophrenia, as well as avoiding continuous benzodiazepine use.

Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study.

Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.

Effect of severity of depression on augmentation of antidepressant medication in young adults with depression.

BACKGROUND: Antipsychotics (AP) have been used to augment antidepressant (AD) medication in treatment-resistant depression. In this study we examined factors (including severity of depression and initial antidepressant) affecting AP augmentation, as well as which APs were initiated as augmentation in young adults. METHODS: Data were extracted from Finnish nationwide registers. Of persons aged 18-29 years diagnosed with a depression during 2004-2017 we focused on incident AD users (who initiated AD 6 months before and after the diagnosis) whose severity level of depression was recorded (N = 21,966). AP augmentation was studied during 1 year after diagnosis of depression. Persons diagnosed with severe depression with psychotic features (n = 1486) were excluded from main analyses and analyzed separately. RESULTS: Overall, 8.4% of new antidepressant users initiated AP augmentation. Risk of augmentation increased with severity of depression as 3.9%, 5.8%, and 14.0% of persons with mild, moderate, and severe depression, respectively, initiated augmentation. Male sex, comorbid anxiety and personality disorders, substance abuse and selfharm/suicide attempt were positively associated with augmentation. Compared to citalopram, use of tricyclic antidepressant, paroxetine and venlafaxine were associated with increased risk of augmentation, while use of bupropion was associated with a decreased risk. Quetiapine and risperidone were the most common APs used in augmentation. Among persons with severe depression with psychotic features, use of sertraline was associated with AP augmentation, whereas use of fluoxetine decreased risk of augmentation. CONCLUSIONS: Use of APs as augmentation of AD therapy was common in severe depression. Comorbidities had only a small effect to augmentation, but selection of initial AD was more closely associated to risk of augmentation. Interestingly, use of bupropion decreased risk of augmentation, which warrants further studies, as well as the decrease in risk of augmentation when fluoxetine in case of psychotic depression was used.

Efficacy of immersive extended reality (XR) interventions on different symptom domains of schizophrenia spectrum disorders. A systematic review.

Introduction: Extended reality (XR) is an umbrella term for virtual reality (VR) and augmented reality (AR), both novel vectors for therapeutic intervention modalities. In VR, head-mounted devices (HMD) allow interaction with three-dimensional virtual environments and simulated avatars, while AR overlaps virtual, simulated objects to observe physical reality. Treatment through immersive VR has been studied in psychiatry, including patients suffering from schizophrenia spectrum disorders, while there has not been much attention to AR technologies in psychiatry. Our systematic review aimed to examine the currently available literature regarding the treatment efficacy of immersive VR or AR technologies on different symptom domains of schizophrenia spectrum disorders, screen for potential adverse effects, and gather data on the technological and human resource requirements of such interventions to help guide future research. Methods: We conducted a systematic literature review with database searches carried out between 9/2021 and 8/2022 through PubMed, Scopus, EBSCOhost Academic Search Premier, and Web of Science. Results: We identified 2,157 records, 214 were assessed further for eligibility and 12 met inclusion criteria. All included articles studied immersive VR and none used AR technology. Included studies were heterogenous in nature, including AVATAR therapy (3) and CBT-based (5) VR interventions, as well as cognitive (2), social (1), and relaxation (1) training through VR. The comparison groups were either passive controls (waitlist and treatment as usual), therapeutic interventions (CBT and Integrated psychological treatment), passive VR environments, or traditional, comparable, non-virtual treatment modalities (social roleplay and progressive muscle relaxation training). Pooled together, the included studies on VR show positive treatment effects in all major symptom domains of schizophrenia spectrum disorders with hardly any adverse effects related to the intervention modalities. Conclusions: In this review, we have showcased how different symptom domains can be targeted through VR interventions, highlighting VR as a potential new vector for a diverse range of psychosocial therapeutic modalities that allow for completely new possibilities in the treatment of schizophrenia spectrum disorders. VR technology still requires more research and validation. Our review also shows that there are currently no studies examining AR technology in the treatment of schizophrenia spectrum disorders, indicating a distinctive research gap.

Real-world use of pharmacological treatments for incident bipolar disorder: A Finnish nationwide cohort study.

BACKGROUND: Pharmacotherapy remains crucial for treating bipolar disorder (BD), but knowledge on the treatments actually used by newly diagnosed patients in real-world settings is sparse. METHODS: Individuals newly diagnosed with BD during 1996-2018, aged 15-65 years, were identified from national Finnish registers. The patients' use of different drug classes (mood stabilizers, antipsychotics and antidepressants) or combinations of these drug classes were followed from initial pharmacotherapy (first line) after BD diagnosis until the fifth line of treatment or until the two-year follow-up time ended. Clinical and sociodemographic factors associated with antidepressants-only as the first treatment line were assessed with logistic regression. RESULTS: 82.6 % of all patients used BD medication during the follow-up. 33.9 % had antidepressants-only as the first, 22.9 % as the second and 19.7 % as the third treatment line. Use of combinations of mood stabilizers, antipsychotics and antidepressants increased by successive treatment lines. Factors associated with antidepressants-only as the first treatment line included older age (>45 years aOR 2.20, 95% CI: 2.01-2.40, 25-45 years: 1.55, 1.42-1.68, compared with those aged <25), diabetes (1.35, 1.17-1.55) and female sex (1.29, 1.21-1.37). BD diagnosis registered in 2016-2018 (0.48, 0.42-0.55) and substance abuse (0.77, 0.71-0.83) were associated with decreased odds. LIMITATIONS: Due to the register-based nature of this study, not all potentially important clinical factors influencing medication use could be controlled for. CONCLUSIONS: A large proportion of patients with bipolar disorder are not treated according to treatment guidelines, as use of antidepressants alone is common. Reasons for not following evidence-based recommendations need to be further researched.

Real-world effectiveness of pharmacological treatments for bipolar disorder: register-based national cohort study.

BACKGROUND: Pharmacological treatment patterns for bipolar disorder have changed during recent years, but for better or worse? AIMS: To investigate the comparative real-world effectiveness of antipsychotics and mood stabilisers in bipolar disorder. METHOD: Register-based cohort study including all Finnish residents aged 16-65 with a diagnosis of bipolar disorder from in-patient care, specialised out-patient care, sickness absence and disability pensions registers between 1996 and 2018, with a mean follow-up of 9.3 years (s.d. = 6.4). Antipsychotic and mood stabiliser use was modelled using the PRE2DUP method and risk for hospital admission for psychiatric and non-psychiatric reasons when using versus not using medications was estimated using within-individual Cox models. RESULTS: Among 60 045 individuals (56.4% female; mean age 41.7 years, s.d. = 15.8), the five medications associated with lowest risk of psychiatric admissions were olanzapine long-acting injection (LAI) (aHR = 0.54, 95% CI 0.37-0.80), haloperidol LAI (aHR = 0.62, 0.47-0.81), zuclopenthixol LAI (aHR = 0.66, 95% CI 0.52-0.85), lithium (aHR = 0.74, 95% CI 0.71-0.76) and clozapine (aHR = 0.75, 95% CI 0.64-0.87). Only ziprasidone (aHR = 1.26, 95% CI 1.07-1.49) was associated with a statistically higher risk. For non-psychiatric (somatic) admissions, only lithium (aHR = 0.77, 95% CI 0.74-0.81) and carbamazepine (aHR = 0.91, 95% CI 0.85-0.97) were associated with significantly reduced risk, whereas pregabalin, gabapentin and several oral antipsychotics, including quetiapine, were associated with an increased risk. Results for a subcohort of first-episode patients (26 395 individuals, 54.9% female; mean age 38.2 years, s.d. = 13.0) were in line with those of the total cohort. CONCLUSIONS: Lithium and certain LAI antipsychotics were associated with lowest risks of psychiatric admission. Lithium was the only treatment associated with decreased risk of both psychiatric and somatic admissions.

Effects of Substance Use and Antisocial Personality on Neuroimaging-Based Machine Learning Prediction of Schizophrenia.

BACKGROUND AND HYPOTHESIS: Neuroimaging-based machine learning (ML) algorithms have the potential to aid the clinical diagnosis of schizophrenia. However, literature on the effect of prevalent comorbidities such as substance use disorder (SUD) and antisocial personality (ASPD) on these models' performance has remained unexplored. We investigated whether the presence of SUD or ASPD affects the performance of neuroimaging-based ML models trained to discern patients with schizophrenia (SCH) from controls. STUDY DESIGN: We trained an ML model on structural MRI data from public datasets to distinguish between SCH and controls (SCH = 347, controls = 341). We then investigated the model's performance in two independent samples of individuals undergoing forensic psychiatric examination: sample 1 was used for sensitivity analysis to discern ASPD (N = 52) from SCH (N = 66), and sample 2 was used for specificity analysis to discern ASPD (N = 26) from controls (N = 25). Both samples included individuals with SUD. STUDY RESULTS: In sample 1, 94.4% of SCH with comorbid ASPD and SUD were classified as SCH, followed by patients with SCH + SUD (78.8% classified as SCH) and patients with SCH (60.0% classified as SCH). The model failed to discern SCH without comorbidities from ASPD + SUD (AUC = 0.562, 95%CI = 0.400-0.723). In sample 2, the model's specificity to predict controls was 84.0%. In both samples, about half of the ASPD + SUD were misclassified as SCH. Data-driven functional characterization revealed associations between the classification as SCH and cognition-related brain regions. CONCLUSION: Altogether, ASPD and SUD appear to have effects on ML prediction performance, which potentially results from converging cognition-related brain abnormalities between SCH, ASPD, and SUD.

General and violent recidivism of former forensic psychiatric patients in Finland.

Background: Forensic psychiatric care in Finland is provided to individuals who have committed a crime due to a serious mental disorder and are in need of psychiatric care. The reconviction (recidivism) rates for this patient group vary in time and between countries, likely due to different treatment practices and requirements for forensic care. Materials and methods: We set out to study criminal recidivism in a national cohort of all patients released from forensic psychiatric care in Finland between 1999 and 2018. National registries were used to identify the patients and gain information on their criminal sentences. Forensic psychiatric examinations were used to record demographic information for the cohort. The cohort was followed up from hospital discharge to the end of 2019. Results: We identified a total of 501 patients who were released from forensic psychiatric care (mean age: 46.6 years [SD 13.4), 434 (86.6%) were male). The mean and median times spent in treatment for the cohort was 10.0 years [SD 6.5] and 8.7 years, respectively. 91% of the patients had schizophrenia spectrum disorder (F2*), and 63.5% had a substance use disorder. A total of 83 patients (16.6%) committed any crime after being released from care, and the mean time to recidivism was 3.8 years. The recidivism rate was 2015 per 100,000 person years. A total of 48 patients (9.6%) committed a violent crime. The mean time to violent recidivism was 4.2 years. The violent recidivism rate was 1,083 per 100,000 person years. A longer duration of treatment was associated with a decreased risk of general recidivism (HR 0.95, 95% CI 0.90 to 1.00, p = 0.05). Factors associated with higher recidivism were male sex, having a comorbid substance use disorder and younger age at discharge. Conclusion: The recidivism rate in Finland was markedly lower than has been previously reported for other Western countries, and the mean duration of treatment was also longer. A longer treatment time may reduce the risk of criminal recidivism in forensic psychiatric patients. The results suggest, as previous studies have found, that more effort is indicated on the treatment of substance abuse.

Cause-specific excess mortality after first diagnosis of bipolar disorder: population-based cohort study.

BACKGROUND: Bipolar disorder (BD) is associated with increased mortality, but evidence on cause-specific mortality is limited. OBJECTIVE: To investigate cause-specific premature excess mortality in BD. METHODS: Finnish nationwide cohort study of individuals with and without a diagnosis of BD who were aged 15-64 years during 2004-2018. Standardised mortality ratios (SMRs) with 95% CIs were calculated for BD using the mortality rates in the Finnish general population without BD as weights. Causes of death were defined by the International Classification of Diseases, 10th revision codes. FINDINGS: Of the included 47 018 individuals with BD, 3300 (7%) died during follow-up. Individuals with BD had sixfold higher mortality due to external causes (SMR: 6.01, 95% CI: 5.68, 6.34) and twofold higher mortality due to somatic causes (SMR: 2.06, 95% CI: 1.97, 2.15). Of the deaths due to external causes, 83% (1061/1273) were excess deaths, whereas 51% (1043/2027) of the deaths due to somatic causes were excess. About twice the number of potential years of life were lost in excess due to external causes than due to somatic causes. Alcohol-related causes contributed more to excess mortality than deaths due to cardiovascular disease. CONCLUSION: External causes of death contributed more to the mortality gap than somatic causes after controlling for age-specific background general population mortality. CLINICAL IMPLICATION: A balanced consideration between therapeutic response, different treatment options and risk of cause-specific mortality is needed to prevent premature mortality in BD and to reduce the mortality gap.

Comparative Effectiveness of Pharmacotherapies for the Risk of Attempted or Completed Suicide Among Persons With Borderline Personality Disorder.

Importance: Suicidal behavior is a significant clinical concern in individuals with borderline personality disorder (BPD), but the effectiveness of pharmacotherapy on reducing suicide risk has remained unknown. Objective: To study the comparative effectiveness of different pharmacotherapies in preventing attempted or completed suicides in patients with BPD in Sweden. Design, Setting and Participants: In this comparative effectiveness research study, nationwide Swedish register databases of inpatient care, specialized outpatient care, sickness absences, and disability pensions were used to identify patients aged 16 to 65 years with registered treatment contact due to BPD during 2006 to 2021. Data were analyzed from September to December 2022. A within-individual design was used, in which each patient was used as their own control to eliminate selection bias. To control protopathic bias, sensitivity analyses were conducted, in which the first 1 or 2 months of medication exposure were omitted from the analyses. Main outcomes and Measures: Hazard ratio (HR) for attempted or completed suicide. Results: A total of 22 601 patients with BPD (3540 [15.7%] men; mean [SD] age, 29.2 [9.9] years) were included. During the 16-year follow-up (mean [SD] follow-up, 6.9 [5.1] years), 8513 hospitalizations due to attempted suicide and 316 completed suicides were observed. Attention-deficit/hyperactive disorder (ADHD) medication treatment, compared with its nonuse, was associated with a decrease in the risk of attempted or completed suicide (HR, 0.83; 95% CI, 0.73-0.95; false discovery rate [FDR]-corrected P = .001). Treatment with mood stabilizers did not have a statistically significant association with the main outcome (HR, 0.97; 95% CI, 0.87-1.08; FDR-corrected P = .99). Antidepressant (HR, 1.38; 95% CI, 1.25-1.53; FDR-corrected P < .001) and antipsychotic (HR, 1.18; 95% CI, 1.07-1.30; FDR-corrected P < .001) treatments were associated with an elevated risk of attempted or completed suicide. Of the investigated pharmacotherapies, treatment with benzodiazepines was associated with the highest risk of attempted or completed suicide (HR, 1.61; 95% CI, 1.45-1.78; FDR-corrected P < .001). These results remained similar when controlling for potential protopathic bias. Conclusions and Relevance: In this comparative effectiveness research study of a Swedish nationwide cohort, ADHD medication was the only pharmacological treatment associated with reduced risk of suicidal behavior among patients with BPD. Conversely, the findings suggest that benzodiazepines should be used with care among patients with BPD due to their association with increased risk of suicide.

Patterns of risk-Using machine learning and structural neuroimaging to identify pedophilic offenders.

Background: Child sexual abuse (CSA) has become a focal point for lawmakers, law enforcement, and mental health professionals. With high prevalence rates around the world and far-reaching, often chronic, individual, and societal implications, CSA and its leading risk factor, pedophilia, have been well investigated. This has led to a wide range of clinical tools and actuarial instruments for diagnosis and risk assessment regarding CSA. However, the neurobiological underpinnings of pedosexual behavior, specifically regarding hands-on pedophilic offenders (PO), remain elusive. Such biomarkers for PO individuals could potentially improve the early detection of high-risk PO individuals and enhance efforts to prevent future CSA. Aim: To use machine learning and MRI data to identify PO individuals. Methods: From a single-center male cohort of 14 PO individuals and 15 matched healthy control (HC) individuals, we acquired diffusion tensor imaging data (anisotropy, diffusivity, and fiber tracking) in literature-based regions of interest (prefrontal cortex, anterior cingulate cortex, amygdala, and corpus callosum). We trained a linear support vector machine to discriminate between PO and HC individuals using these WM microstructure data. Post hoc, we investigated the PO model decision scores with respect to sociodemographic (age, education, and IQ) and forensic characteristics (psychopathy, sexual deviance, and future risk of sexual violence) in the PO subpopulation. We assessed model specificity in an external cohort of 53 HC individuals. Results: The classifier discriminated PO from HC individuals with a balanced accuracy of 75.5% (sensitivity = 64.3%, specificity = 86.7%, P 5000 = 0.018) and an out-of-sample specificity to correctly identify HC individuals of 94.3%. The predictive brain pattern contained bilateral fractional anisotropy in the anterior cingulate cortex, diffusivity in the left amygdala, and structural prefrontal cortex-amygdala connectivity in both hemispheres. This brain pattern was associated with the number of previous child victims, the current stance on sexuality, and the professionally assessed risk of future sexual violent reoffending. Conclusion: Aberrant white matter microstructure in the prefronto-temporo-limbic circuit could be a potential neurobiological correlate for PO individuals at high-risk of reoffending with CSA. Although preliminary and exploratory at this point, our findings highlight the general potential of MRI-based biomarkers and particularly WM microstructure patterns for future CSA risk assessment and preventive efforts.

Real-world effectiveness of antidepressant use in persons with schizophrenia: within-individual study of 61,889 subjects.

The aim of this study was to investigate the real-world effectiveness of antidepressant use in persons with schizophrenia. The register-based study cohort included all 61,889 persons treated in inpatient care due to schizophrenia during 1972-2014 in Finland. The main outcome was hospitalization due to psychosis and secondary outcomes included non-psychiatric hospitalization and all-cause mortality. We used within-individual design to compare the risk of hospitalization-based outcomes during the time periods of antidepressant use to antidepressant non-use periods within the same person, and traditional between-individual Cox models for mortality. The risk of psychosis hospitalization was lower during antidepressant use as compared to non-use (adjusted Hazard Ratio, aHR, 0.93, 95% CI 0.92-0.95). Antidepressants were associated with a decreased risk of mortality (aHR 0.80, 95% CI 0.76-0.85) and a slightly increased risk of non-psychiatric hospitalization (aHR 1.03, 95% CI 1.01-1.06). In conclusion, these results indicate that antidepressants might be useful and relatively safe to use in this population.