Understanding the relationship between childhood abuse and affective symptoms in bipolar disorder: New insights from a network analysis.

The impact of childhood abuse on the presentation of bipolar disorder could be further elucidated by comparing the networks of affective symptoms among individuals with and with no history of childhood abuse. Data from 476 participants in the Clinical Health Outcomes Initiative in Comparative Effectiveness for Bipolar Disorder study were used to fit several regularised Gaussian Graphical Models. Differences in the presentation of depressive and manic symptoms were uncovered: only among participants with a history of childhood abuse, inadequacy and pessimism were central symptoms in the network of depressive symptoms, while racing thoughts was an important symptom in the network of manic symptoms. Following network theory, focusing treatments at the symptom-level and on central symptoms - like inadequacy, pessimism, and racing thoughts - could be an effective approach for managing affective symptoms among the sizeable proportion of people with bipolar disorder who have experienced childhood abuse. This study contributes a thorough investigation of the networks of affective symptoms among participants with and with no history of childhood abuse, albeit limited by the use of a binary, self-report measure of childhood abuse, thereby emphasising the importance of assessing for childhood abuse and taking needed steps towards identifying novel targets for treating bipolar disorder.

Prenatal environmental risk factors for autism spectrum disorder and their potential mechanisms.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is globally increasing in prevalence. The rise of ASD can be partially attributed to diagnostic expansion and advocacy efforts; however, the interplay between genetic predisposition and modern environmental exposures is likely driving a true increase in incidence. A range of evidence indicates that prenatal exposures are critical. Infection during pregnancy, gestational diabetes, and maternal obesity are established risk factors for ASD. Emerging areas of research include the effects of maternal use of selective serotonin reuptake inhibitors, antibiotics, and exposure to toxicants during pregnancy on brain development and subsequent ASD. The underlying pathways of these risk factors remain uncertain, with varying levels of evidence implicating immune dysregulation, mitochondrial dysfunction, oxidative stress, gut microbiome alterations, and hormonal disruptions. This narrative review assesses the evidence of contributing prenatal environmental factors for ASD and associated mechanisms as potential targets for novel prevention strategies.

Multiscale heterogeneity of white matter morphometry in psychiatric disorders.

Background: Inter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear. Methods: We applied Warped Bayesian Linear Regression normative models to T1-weighted magnetic resonance imaging data and mapped inter-individual variability in person-specific white matter volume deviations in 1,294 cases (58% male) diagnosed with one of six disorders (attention-deficit/hyperactivity, autism, bipolar, major depressive, obsessive-compulsive and schizophrenia) and 1,465 matched controls (54% male) recruited across 25 scan sites. We developed a framework to characterize deviation heterogeneity at multiple spatial scales, from individual voxels, through inter-regional connections, specific brain regions, and spatially extended brain networks. Results: The specific locations of white matter volume deviations were highly heterogeneous across participants, affecting the same voxel in fewer than 8% of individuals with the same diagnosis. For autism and schizophrenia, negative deviations (i.e., areas where volume is lower than normative expectations) aggregated into common tracts, regions and large-scale networks in up to 35% of individuals. Conclusions: The prevalence of white matter volume deviations was lower than previously observed in grey matter, and the specific location of these deviations was highly heterogeneous when considering voxel-wise spatial resolution. Evidence of aggregation within common pathways and networks was apparent in schizophrenia and autism but not other disorders.

Sleep Capital: Linking Brain Health to Wellbeing and Economic Productivity Across the Lifespan.

INTRODUCTION AND FRAMEWORK: Sleep capital contributes to individual and societal wellbeing, productivity, and economic outcomes and involves a novel aspect of brain capital. It encompasses the quality and quantity of sleep as integral components that influence cognitive abilities, mental and brain health, and physical health, affecting workplace productivity, learning, decision-making, and overall economic performance. Here, we bring a framework to understand the complex relationship between sleep quality, health, wellbeing, and economic productivity. Then we outline the multilevel impact of sleep on cognitive abilities, mental/brain health, and economic indicators, providing evidence for the substantial returns on investment in sleep health initiatives. Moreover, sleep capital is a key factor when considering brain health across the lifespan, especially for the aging population. DISCUSSION: We propose specific elements and main variables to develop specific indexes of sleep capital to address its impacts on health, wellbeing and productivity. CONCLUSION: Finally, we suggest policy recommendations, workplace interventions, and individual strategies to promote sleep health and brain capital. Investing in sleep capital is essential for fostering a healthier, happier, fairer and more productive society.

Plasma neurofilament light protein is differentially associated with age in individuals with treatment-resistant schizophrenia and bipolar affective disorder compared to controls.

Accelerated brain ageing has been observed in multiple psychiatric disorders. This study examined whether relationships between age and plasma neurofilament light (NfL) protein differed in individuals with psychiatric disorders (major depressive disorder (n = 42), bipolar affective disorder (n = 121), treatment-resistant schizophrenia (TRS, n = 82)) compared to two healthy control (HC) groups (n = 1,926 and n = 59). Compared to two independent HC samples, individuals with TRS demonstrated a stronger positive relationship between age and NfL levels. Individuals with BPAD had a stronger negative relationship between age and NfL levels compared to the large normative HC cohort, but not locally-acquired HCs. These findings show that plasma NfL levels are differentially associated with age in individuals with TRS and BPAD compared to healthy individuals.

Efficacy and tolerability of monoamine oxidase inhibitors for the treatment of depressive episodes in mood disorders: A systematic review and network meta-analysis.

BACKGROUND: Monoamine oxidase inhibitors (MAOIs) are considered third-line treatments for treatment resistant depression; however, they are underused in clinical practice. AIMS: This study aimed to assess the efficacy, tolerability, and acceptability of MAOIs for the treatment of depression in comparison with other antidepressant treatments. METHODS: A systematic review and network meta-analysis of randomised clinical trials was performed to compare the efficacy, tolerability and acceptability between MAOIs and other antidepressant treatments for the treatment of depressive episodes. RESULTS: A total of 83 double-blinded, randomised controlled trials were included in the analysis, with 7765 participants assigned to an active treatment and 1844 assigned to placebo. Several MAOIs, including isocarboxazid, phenelzine, tranylcypromine and moclobemide, showed significantly higher efficacy compared with placebo. The tolerability and acceptability of MAOIs was comparable to other antidepressants. LIMITATIONS: A disproportionate number of studies investigating the most commonly used MAOIs, such as moclobemide and phenelzine, and a lack of specific studies focusing on treatment-resistant and atypical depression. CONCLUSIONS: MAOIs are similar in efficacy to other antidepressants for the treatment of depression. However, more studies are needed comparing MAOI treatment in people with treatment-resistant, atypical and bipolar depression.

Nutraceuticals and phytoceuticals in the treatment of schizophrenia: a systematic review and network meta-analysis "Nutra NMA SCZ".

Sub-optimal response in schizophrenia is frequent, warranting augmentation strategies over treatment-as-usual (TAU). We assessed nutraceuticals/phytoceutical augmentation strategies via network meta-analysis. Randomized controlled trials in schizophrenia/schizoaffective disorder were identified via the following databases: PubMed, MEDLINE, EMBASE, Scopus, PsycINFO, CENTRAL, and ClinicalTrials.gov. Change (Standardized Mean Difference = SMD) in total symptomatology and acceptability (Risk Ratio = RR) were co-primary outcomes. Secondary outcomes were positive, negative, cognitive, and depressive symptom changes, general psychopathology, tolerability, and response rates. We conducted subset analyses by disease phase and sensitivity analyses by risk of bias and assessed global/local inconsistency, publication bias, risk of bias, and confidence in the evidence. The systematic review included 49 records documenting 50 studies (n = 2384) documenting 22 interventions. Citicoline (SMD =-1.05,95%CI = -1.85; -0.24), L-lysine (SMD = -1.04,95%CI = -1.84; -0.25), N-acetylcysteine (SMD = -0.87, 95%CI = -1.27; -0.47) and sarcosine (SMD = -0.5,95%CI = -0.87-0.13) outperformed placebo for total symptomatology. High heterogeneity (tau2 = 0.10, I2 = 55.9%) and global inconsistency (Q = 40.79, df = 18, p = 0.002) emerged without publication bias (Egger's test, p = 0.42). Sarcosine improved negative symptoms (SMD = -0.65, 95%CI = -1.10; -0.19). N-acetylcysteine improved negative symptoms (SMD = -0.90, 95%CI = -1.42; -0.39)/general psychopathology (SMD = -0.76, 95%CI = -1.39; -0.13). No compound improved total symptomatology within acute phase studies (k = 7, n = 422). Sarcosine (SMD = -1.26,95%CI = -1.91; -0.60), citicoline (SMD = -1.05,95%CI = -1.65;-0.44), and N-acetylcysteine (SMD = -0.55,95%CI = -0.92,-0.19) outperformed placebo augmentation in clinically stable participants. Sensitivity analyses removing high-risk-of-bias studies confirmed overall findings in all phases and clinically stable samples. In contrast, the acute phase analysis restricted to low risk-of-bias studies showed a superior effect vs. placebo for N-acetylcysteine (SMD = -1.10, 95%CI = -1.75,-0.45), L-lysine (SMD = -1.05,95%CI = -1.55, -0.19), omega-3 fatty acids (SMD = -0.83,95%CI = -1.31, -0.34) and withania somnifera (SMD = -0.71,95%CI = -1.21,-0.22). Citicoline (SMD = -1.05,95%CI = -1.86,-0.23), L-lysine (SMD = -1.04,95%CI = -1.84,-0.24), N-acetylcysteine (SMD = -0.89,95%CI = -1.35,-0.43) and sarcosine (SMD = -0.61,95%CI = -1.02,-0.21) outperformed placebo augmentation of TAU ("any phase"). Drop-out due to any cause or adverse events did not differ between nutraceutical/phytoceutical vs. placebo+TAU. Sarcosine, citicoline, and N-acetylcysteine are promising augmentation interventions in stable patients with schizophrenia, yet the quality of evidence is low to very low. Further high-quality trials in acute phases/specific outcomes/difficult-to-treat schizophrenia are warranted.

Is a vegetarian diet beneficial for bipolar disorder? Relationship between dietary patterns, exercise and pharmacological treatments with metabolic syndrome and course of disease in bipolar disorder.

BACKGROUND: Lifestyle factors are being increasingly studied in bipolar disorder (BD) due to their possible effects on both course of disease and physical health. The aim of this study was to jointly describe and explore the interrelations between diet patterns, exercise, pharmacological treatment with course of disease and metabolic profile in BD. METHODS: The sample consisted of 66 euthymic or mild depressive individuals with BD. Clinical and metabolic outcomes were assessed, as well as pharmacological treatment or lifestyle habits (diet and exercise). Correlations were explored for different interrelations and a factor analysis of dietary patterns was performed. RESULTS: Adherence to the Mediterranean diet was low, seen in 37.9% of the patients and was positively associated with perceived quality of life. The amount of exercise was negatively associated with cholesterol levels, with 32.8% of participants rated as low active by International Physical Activity Questionnaire. There was a high prevalence of obesity (40.6%) and metabolic syndrome (29.7%). Users of lithium showed the best metabolic profile. Interestingly, three dietary patterns were identified: "vegetarian," "omnivore" and "Western." The key finding was the overall positive impact of the "vegetarian" pattern in BD, which was associated with reduced depression scores, better psychosocial functioning, and perceived quality of life, decreased body mass index, cholesterol, LDL and diastolic blood pressure. Nuts consumption was associated with a better metabolic profile. CONCLUSIONS: A vegetarian diet pattern was associated with both, better clinical and metabolic parameters, in patients with BD. Future studies should prioritize prospective and randomized designs to determine causal relationships, and potentially inform clinical recommendations.

Development of a harmonized sociodemographic and clinical questionnaire for mental health research: A Delphi-method-based consensus recommendation.

OBJECTIVE: Harmonized tools are essential for reliable data sharing and accurate identification of relevant factors in mental health research. The primary objective of this study was to create a harmonized questionnaire to collect demographic, clinical and behavioral data in diverse clinical trials in adult psychiatry. METHODS: We conducted a literature review and examined 24 questionnaires used in previously published randomized controlled trials in psychiatry, identifying a total of 27 domains previously explored. Using a Delphi-method process, a task force team comprising experts in psychiatry, epidemiology and statistics selected 15 essential domains for inclusion in the final questionnaire. RESULTS: The final selection resulted in a concise set of 22 questions. These questions cover factors such as age, sex, gender, ancestry, education, living arrangement, employment status, home location, relationship status, and history of medical and mental illness. Behavioral factors like physical activity, diet, smoking, alcohol and illicit drug use were also included, along with one question addressing family history of mental illness. Income was excluded due to high confounding and redundancy, while language was included as a measure of migration status. CONCLUSION: The recommendation and adoption of this harmonized tool for the assessment of demographic, clinical and behavioral data in mental health research can enhance data consistency and enable comparability across clinical trials.

Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method.

BACKGROUND: Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD. METHODS: A longitudinal study was conducted, involving 9936 (5,231 women and 4705 men) initially healthy, community-dwelling Australians aged 70 years or more from the ASPirin in Reducing Events in the Elderly (ASPREE) study and ASPREE Longitudinal Study of Older Persons, with a median follow-up time of 6.4 years. Variable categorisation, variable selection (using machine learning (ML) models; Elastic Net and extreme gradient boosting) and Cox-regression were employed separately by binary gender to identity socialisation factors (n=25 considered) associated with CVD. RESULTS: Different socialisation factors were identified using the ML models. In the Cox model, for both genders, being married/partnered was associated with a reduced risk of CVD (men: HR 0.76, 95% CI 0.60 to 0.96; women: HR 0.67, 95% CI 0.58 to 0.95). For men, having 3-8 relatives they felt close to and could call on for help (HR 0.76, 95% CI 0.58 to 0.99; reference <3 relatives), having 3-8 relatives they felt at ease talking with about private matters (HR 0.70, 95% CI 0.55 to 0.90; reference <3 relatives) or playing games such as chess or cards (HR 0.82, 95% CI 0.67 to 1.00) was associated with reduced risk of CVD. For women, living with others (HR 0.71, 95% CI 0.55 to 0.91) or having ≥3 friends they felt at ease talking with about private matters (HR 0.74, 95% CI 0.58 to 0.95; reference <3 friends) was associated with a lower risk of CVD. CONCLUSIONS: This study demonstrates the need to prioritise gender-specific social factors to improve cardiovascular health in older adults.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

A phase 3 randomised double-blind placebo-controlled trial of mirtazapine as a pharmacotherapy for methamphetamine use disorder: a study protocol for the Tina Trial.

BACKGROUND: There are no approved pharmacotherapies for methamphetamine use disorder. Two preliminary phase 2 randomised controlled trials have found mirtazapine, a tetracyclic antidepressant, to be effective in reducing methamphetamine use. The proposed Tina Trial is the first phase 3 placebo-controlled randomised trial to examine the effectiveness and safety of mirtazapine as an outpatient pharmacotherapy for methamphetamine use disorder. METHODS: This is a multi-site phase 3 randomised, double-blind, placebo-controlled parallel trial. Participants are randomly allocated (1:1) to receive either mirtazapine (30 mg/day for 12 weeks) or matched placebo, delivered as a take-home medication. The target population is 340 people aged 18-65 years who have moderate to severe methamphetamine use disorder. The trial is being conducted through outpatient alcohol and other drug treatment clinics in Australia. The primary outcome is measured as self-reported days of methamphetamine use in the past 4 weeks at week 12. Secondary outcomes are methamphetamine-negative oral fluid samples, depressive symptoms, sleep quality, HIV risk behaviour and quality of life. Other outcomes include safety (adverse events), tolerability, and health service use. Medication adherence is being monitored using MEMS® Smart Caps fitted to medication bottles. DISCUSSION: This trial will provide information on the safety and effectiveness of mirtazapine as a pharmacotherapy for methamphetamine use disorder when delivered as an outpatient medication in routine clinical practice. If found to be safe and effective, this trial will support an application for methamphetamine use disorder to be included as a therapeutic indication for the prescription of mirtazapine. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12622000235707. Registered on February 9, 2022.

Machine Learning in Electroconvulsive Therapy: A Systematic Review.

ABSTRACT: Despite years of research, we are still not able to reliably predict who might benefit from electroconvulsive therapy (ECT) treatment. As we exhaust what is possible using traditional statistical analysis, ECT remains a good candidate for machine learning approaches due to the large data sets with data captured through electroencephalography (EEG) and other objective measures. A systematic review of 6 databases led to the full-text examination of 26 articles using machine learning approaches in examining data predicting response to ECT treatment. The identified articles used a wide variety of data types covering structural and functional imaging data (n = 15), clinical data (n = 5), a combination of clinical and imaging data (n = 2), EEG (n = 3), and social media posts (n = 1). The clinical indications in which response prediction was assessed were depression (n = 21) and psychosis (n = 4). Changes in multiple anatomical regions in the brain were identified as holding a predictive value for response to ECT. These primarily centered on the limbic system and associated networks. Clinical features predicting good response to ECT in depression included shorter duration, lower severity, higher medication dose, psychotic features, low cortisol levels, and positive family history. It has also been possible to predict the likelihood of relapse of readmission with psychosis after ECT treatment, including a better response if higher transfer entropy was calculated from EEG signals. A transdisciplinary approach with an international consortium collecting a wide range of retrospective and prospective data may help to refine and extend these outcomes and translate them into clinical practice.

The neglected association between schizophrenia and bone fragility: a systematic review and meta-analyses.

Schizophrenia is associated with increased risk of medical comorbidity, possibly including osteoporosis, which is a public health concern due to its significant social and health consequences. In this systematic review and meta-analysis, we aimed to determine whether schizophrenia is associated with bone fragility. The protocol for this review has been registered with PROSPERO (CRD42020171959). The research question and inclusion/exclusion criteria were developed and presented according to the PECO (Population, Exposure, Comparison, Outcome) framework. Schizophrenia was identified from medical records, DSM-IV/5 or the ICD. The outcomes for this review were bone fragility [i.e., bone mineral density (BMD), fracture, bone turnover markers, bone quality]. A search strategy was developed and implemented for the electronic databases. A narrative synthesis was undertaken for all included studies; the results from eligible studies reporting on BMD and fracture were pooled using a random effects model to complete a meta-analysis. The conduct of the review and reporting of results adhered to PRISMA guidelines. Our search yielded 3103 studies, of which 29 met the predetermined eligibility criteria. Thirty-seven reports from 29 studies constituted 17 studies investigating BMD, eight investigating fracture, three investigating bone quality and nine investigating bone turnover markers. The meta-analyses revealed that people with schizophrenia had lower BMD at the lumbar spine [standardised mean difference (SMD) -0.74, 95% CI -1.27, -0.20; Z = -2.71, p = 0.01] and at the femoral neck (SMD -0.78, 95% CI -1.03, -0.53; Z = -6.18, p ≤ 0.001). Also observed was a higher risk of fracture (OR 1.43, 95% CI 1.27, 1.61; Z = 5.88, p ≤ 0.001). Following adjustment for publication bias, the association between schizophrenia and femoral neck BMD (SMD -0.63, 95% CI -0.97, -0.29) and fracture (OR 1.32, 95% CI 1.28, 1.35) remained. Significantly increased risk of bone fragility was observed in people with schizophrenia. This association was independent of sex, participant number, methodological quality and year of publication.

Current Pharmacotherapies for Smoking Cessation and Promising Emerging Drugs.

OBJECTIVE: Pharmacotherapy is commonly used during quit attempts and has shown an increase in the likelihood of achieving abstinence. However, with established pharmacotherapies, abstinence rates following a quit attempt remain low, and relapse is common. This review aims to investigate the efficacy and harm profiles of current and emerging pharmacotherapies. METHODS: Literature review of current and emerging pharmacotherapies for smoking cessation and tobacco use disorder. RESULTS: Emerging pharmacotherapies include new formulations of existing therapies, drug repurposing and some new treatments. New treatments are welcome and may incorporate different mechanisms of action or different safety and tolerability profiles compared to existing treatments. However, emerging pharmacotherapies have yet to demonstrate greater efficacy compared to existing treatments. The emergence of Electronic Nicotine Delivery Systems (ENDS) or 'vaping' is a feature of the current debate around tobacco use disorder. ENDS appear to facilitate switching but not quitting and are controversial as a harm minimisation strategy. LIMITATIONS: Studies included a broad range of therapies and trial designs that should be compared with their differences taken into consideration. CONCLUSION: Strategies to successfully quit smoking vary between individuals and may extend beyond pharmacotherapy and involve complex psychosocial factors and pathways.

New Advances in the Pharmacology and Toxicology of Lithium: A Neurobiologically Oriented Overview.

Over the last six decades, lithium has been considered the gold standard treatment for the long-term management of bipolar disorder due to its efficacy in preventing both manic and depressive episodes as well as suicidal behaviors. Nevertheless, despite numerous observed effects on various cellular pathways and biologic systems, the precise mechanism through which lithium stabilizes mood remains elusive. Furthermore, there is recent support for the therapeutic potential of lithium in other brain diseases. This review offers a comprehensive examination of contemporary understanding and predominant theories concerning the diverse mechanisms underlying lithium's effects. These findings are based on investigations utilizing cellular and animal models of neurodegenerative and psychiatric disorders. Recent studies have provided additional support for the significance of glycogen synthase kinase-3 (GSK3) inhibition as a crucial mechanism. Furthermore, research has shed more light on the interconnections between GSK3-mediated neuroprotective, antioxidant, and neuroplasticity processes. Moreover, recent advancements in animal and human models have provided valuable insights into how lithium-induced modifications at the homeostatic synaptic plasticity level may play a pivotal role in its clinical effectiveness. We focused on findings from translational studies suggesting that lithium may interface with microRNA expression. Finally, we are exploring the repurposing potential of lithium beyond bipolar disorder. These recent findings on the therapeutic mechanisms of lithium have provided important clues toward developing predictive models of response to lithium treatment and identifying new biologic targets. SIGNIFICANCE STATEMENT: Lithium is the drug of choice for the treatment of bipolar disorder, but its mechanism of action in stabilizing mood remains elusive. This review presents the latest evidence on lithium's various mechanisms of action. Recent evidence has strengthened glycogen synthase kinase-3 (GSK3) inhibition, changes at the level of homeostatic synaptic plasticity, and regulation of microRNA expression as key mechanisms, providing an intriguing perspective that may help bridge the mechanistic gap between molecular functions and its clinical efficacy as a mood stabilizer.

The contribution of alexithymia, childhood maltreatment, impulsivity, C-reactive protein, lipid profile, and thyroid hormones to aggression and psychological distress (depression and anxiety) in schizophrenia.

There are individual effects of alexithymia, childhood maltreatment, impulsivity, and some biological markers on aggression and psychological distress in schizophrenia. However, the combined effects of these psychological and biological markers have not yet been fully studied. This study therefore aimed to investigate the influence of these psychological and biological markers on aggression and psychological distress (e.g., depression and anxiety) in inpatients with schizophrenia (n = 355). Participants completed self-report and clinician-rated scales, and blood samples were collected. There were no significant differences between patients with and without alexithymia regarding biological markers. Patients with childhood maltreatment exhibited higher levels of free triiodothyronine (FT3) and C-reactive protein (CRP), as well as lower total cholesterol (TC) levels, compared to non-traumatized individuals. Aggression was positively predicted by psychological distress, alexithymia, childhood maltreatment, impulsivity, CRP, and FT3, and negatively by TC and low-density lipoprotein cholesterol. Negative symptoms, childhood maltreatment, alexithymia, aggression, and CRP positively, and high-density lipoprotein cholesterol negatively emerged as predictors of psychological distress. The study highlights the connections between childhood maltreatment, alexithymia, impulsivity, and potentially related biological dysregulation in explaining aggression and negative mood states as a bio-psychological model of aggression and mood in schizophrenia.

A Brief Workplace Training Program to Support Help-Seeking for Mental Ill-Health: Protocol for the Helipad Cluster Randomized Controlled Trial.

BACKGROUND: Most people with mental health problems do not seek help, with delays of even decades in seeking professional help. Lack of engagement with professional mental health services can lead to poor outcomes and functional impairment. However, few effective interventions have been identified to improve help-seeking in adults, and those that exist are not widely implemented to deliver public health impact. Co-designing interventions with people with lived experience of mental ill-health and other relevant stakeholders is critical to increase the likelihood of uptake and engagement with these programs. OBJECTIVE: This study aims to (1) test the effectiveness of a co-designed help-seeking program on increasing professional help-seeking intentions in employees in a workplace setting; (2) determine whether the program reduces mental illness stigma and improves help-seeking intentions and behavior, mental health literacy, mental health symptoms, and work and activity functioning relative to the control condition; (3) explore factors that facilitate broader implementation of the co-designed program; and (4) explore the cost-effectiveness of the co-designed program compared to the control condition over 6 months. METHODS: A 2-arm cluster randomized controlled trial will be conducted (target sample: N=900 from 30 to 36 workplaces, with n=25 to 35 participants per workplace). The trial will compare the relative effectiveness of an enhanced interactive program (intervention condition) with a standard psychoeducation-alone program (active control condition) on the primary outcome of professional help-seeking intentions as measured by the General Help-Seeking Questionnaire. Secondary outcomes include the impact on mental illness stigma; mental health literacy; help-seeking attitudes and behavior; work and activity functioning; quality of life; and symptoms of mental ill-health including depression, anxiety, and general psychological distress. RESULTS: Facilitators of and risks to the trial are identified and addressed in this protocol. Recruitment of workplaces is scheduled to commence in the first quarter of 2024. CONCLUSIONS: If effective, the program has the potential to be ready for rapid dissemination throughout Australia, with the potential to increase appropriate and efficient service use across the spectrum of evidence-based services. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12623000270617p; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=385376. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/55529.