Impact of air pollution and climate change on mental health outcomes: an umbrella review of global evidence.

The impact of air pollution and climate change on mental health has recently raised strong concerns. However, a comprehensive overview analyzing the existing evidence while addressing relevant biases is lacking. This umbrella review systematically searched the PubMed/Medline, Scopus and PsycINFO databases (up to June 26, 2023) for any systematic review with meta-analysis investigating the association of air pollution or climate change with mental health outcomes. We used the R metaumbrella package to calculate and stratify the credibility of the evidence according to criteria (i.e., convincing, highly suggestive, suggestive, or weak) that address several biases, complemented by sensitivity analyses. We included 32 systematic reviews with meta-analysis that examined 284 individual studies and 237 associations of exposures to air pollution or climate change hazards and mental health outcomes. Most associations (n=195, 82.3%) involved air pollution, while the rest (n=42, 17.7%) regarded climate change hazards (mostly focusing on temperature: n=35, 14.8%). Mental health outcomes in most associations (n=185, 78.1%) involved mental disorders, followed by suicidal behavior (n=29, 12.4%), access to mental health care services (n=9, 3.7%), mental disorders-related symptomatology (n=8, 3.3%), and multiple categories together (n=6, 2.5%). Twelve associations (5.0%) achieved convincing (class I) or highly suggestive (class II) evidence. Regarding exposures to air pollution, there was convincing (class I) evidence for the association between long-term exposure to solvents and a higher incidence of dementia or cognitive impairment (odds ratio, OR=1.139), and highly suggestive (class II) evidence for the association between long-term exposure to some pollutants and higher risk for cognitive disorders (higher incidence of dementia with high vs. low levels of carbon monoxide, CO: OR=1.587; higher incidence of vascular dementia per 1 µg/m3 increase of nitrogen oxides, NOx: hazard ratio, HR=1.004). There was also highly suggestive (class II) evidence for the association between exposure to airborne particulate matter with diameter ≤10 µm (PM10) during the second trimester of pregnancy and the incidence of post-partum depression (OR=1.023 per 1 µg/m3 increase); and for the association between short-term exposure to sulfur dioxide (SO2) and schizophrenia relapse (risk ratio, RR=1.005 and 1.004 per 1 µg/m3 increase, respectively 5 and 7 days after exposure). Regarding climate change hazards, there was highly suggestive (class II) evidence for the association between short-term exposure to increased temperature and suicide- or mental disorders-related mortality (RR=1.024), suicidal behavior (RR=1.012), and hospital access (i.e., hospitalization or emergency department visits) due to suicidal behavior or mental disorders (RR=1.011) or mental disorders only (RR=1.009) (RR values per 1°C increase). There was also highly suggestive (class II) evidence for the association between short-term exposure to increased apparent temperature (i.e., the temperature equivalent perceived by humans) and suicidal behavior (RR=1.01 per 1°C increase). Finally, there was highly suggestive (class II) evidence for the association between the temporal proximity of cyclone exposure and severity of symptoms of post-traumatic stress disorder (r=0.275). Although most of the above associations were small in magnitude, they extend to the entire world population, and are therefore likely to have a substantial impact. This umbrella review classifies and quantifies for the first time the global negative impacts that air pollution and climate change can exert on mental health, identifying evidence-based targets that can inform future research and population health actions.

Anxious and depressive symptoms and health-related quality of life in a cohort of people who recently attempted suicide: A network analysis.

BACKGROUND: Suicide is an international health concern with immeasurable impact from the perspective of human and social suffering. Prior suicide attempts, anxious and depressive symptoms, and relatively lower health-related quality of life (HRQoL) are among the most replicated risk factors for suicide. Our goal was to visualize the distribution of these features and their interconnections with use of a network analysis approach in individuals who recently attempted suicide. METHODS: Individuals with a recent suicide attempt were recruited from nine University Hospitals across Spain as part of the SURVIVE cohort study. Anxious and depressive symptoms, and perceived HRQoL were included in the network analysis. Network structures were estimated with the EBICglasso model. Centrality measures and bridge symptoms connecting communities were explored. Subnetworks comparing younger and older individuals, and women and men were analyzed. RESULTS: A total of 1106 individuals with a recent suicide attempt were included. Depressed mood was the symptom with the greatest influence in the overall network, followed by anxiety symptoms such as feeling nervous, worrying, restless, and having difficulties to relax. Perceived general health was associated with increased suicidal ideation in the whole sample. Older people showed a specific connection between perceived general health and depressed mood. LIMITATIONS: The cross-sectional design does not allow determination of established causality. CONCLUSIONS: Depressed mood was the core network's symptom and, therefore, an important target in the management and prevention of suicide. HRQoL had more influence on the network of older populations, in which it should be a primary focus.

Pharmacological treatments for psychotic depression: a systematic review and network meta-analysis.

BACKGROUND: There are no recommendations based on the efficacy of specific drugs for the treatment of psychotic depression. To address this evidence gap, we did a network meta-analysis to assess and compare the efficacy and safety of pharmacological treatments for psychotic depression. METHODS: In this systematic review and network meta-analysis, we searched ClinicalTrials.gov, CENTRAL, Embase, PsycINFO, PubMed, Scopus, and Web of Science from inception to Nov 23, 2023 for randomised controlled trials published in any language that assessed pharmacological treatments for individuals of any age with a diagnosis of a major depressive episode with psychotic features, in the context of major depressive disorder or bipolar disorder in any setting. We excluded continuation or maintenance trials. We screened the study titles and abstracts identified, and we extracted data from relevant studies after full-text review. If full data were not available, we requested data from study authors twice. We analysed treatments for individual drugs (or drug combinations) and by grouping them on the basis of mechanisms of action. The primary outcomes were response rate (ie, the proportion of participants who responded to treatment) and acceptability (ie, the proportion who discontinued treatment for any reason). We calculated risk ratios and did separate frequentist network meta-analyses by using random-effects models. The risk of bias of individual studies was assessed with the Cochrane risk-of-bias tool and the confidence in the evidence with the Confidence-In-Network-Meta-Analysis (CINeMA). This study was registered with PROSPERO, CRD42023392926. FINDINGS: Of 6313 reports identified, 16 randomised controlled trials were included in the systematic review, and 14 were included in the network meta-analyses. The 16 trials included 1161 people with psychotic depression (mean age 50·5 years [SD 11·4]). 516 (44·4%) participants were female and 422 (36·3%) were male; sex data were not available for the other 223 (19·2%). 489 (42·1%) participants were White, 47 (4·0%) were African American, and 12 (1·0%) were Asian; race or ethnicity data were not available for the other 613 (52·8%). Only the combination of fluoxetine plus olanzapine was associated with a higher proportion of participants with a treatment response compared with placebo (risk ratio 1·91 [95% CI 1·27-2·85]), with no differences in terms of safety outcomes compared with placebo. When treatments were grouped by mechanism of action, the combination of a selective serotonin reuptake inhibitor with a second-generation antipsychotic was associated with a higher proportion of treatment responses than was placebo (1·89 [1·17-3·04]), with no differences in terms of safety outcomes. In head-to-head comparisons of active treatments, a significantly higher proportion of participants had a response to amitriptyline plus perphenazine (3·61 [1·23-10·56]) and amoxapine (3·14 [1·01-9·80]) than to perphenazine, and to fluoxetine plus olanzapine compared with olanzapine alone (1·60 [1·09-2·34]). Venlafaxine, venlafaxine plus quetiapine (2·25 [1·09-4·63]), and imipramine (1·95 [1·01-3·79]) were also associated with a higher proportion of treatment responses overall. In head-to-head comparisons grouped by mechanism of action, antipsychotic plus antidepressant combinations consistently outperformed monotherapies from either drug class in terms of the proportion of participants with treatment responses. Heterogeneity was low. No high-risk instances were identified in the bias assessment for our primary outcomes. INTERPRETATION: According to the available evidence, the combination of a selective serotonin reuptake inhibitor and a second-generation antipsychotic-and particularly of fluoxetine and olanzapine-could be the optimal treatment choice for psychotic depression. These findings should be taken into account in the development of clinical practice guidelines. However, these conclusions should be interpreted cautiously in view of the low number of included studies and the limitations of these studies. FUNDING: None.

Clinical features in co-occuring obsessive-compulsive disorder and bipolar disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) frequently co-occurs with various psychiatric conditions and may impact as many as one-fifth of individuals diagnosed with bipolar disorder (BD). Despite the expanding body of literature on the coexistence of OCD and BD, there is a notable lack of comprehensive data pertaining to the distinct features of obsessive-compulsive symptoms that define this comorbidity. To bridge this knowledge gap, we conducted a systematic search of PubMed/MEDLINE, Scopus, EMBASE, and PsycINFO until August 7th, 2023. We performed random-effects meta-analyses to compare individuals with both OCD and BD to those with OCD in terms of OCD symptomatology as well as the specific categories of obsessions and compulsions. Out of the 10,393 records initially screened, 17 studies were ultimately incorporated into the qualitative assessment, with 15 of them being included in the quantitative analysis. Individuals with OCD and BD experienced fewer lifetime contamination obsessions (OR=0.71; 95 %CI=0.53, 0.95; p = 0.021) and more sexual obsessions (OR=1.77; 95 %CI=1.03, 3.04; p = 0.04) compared to individuals with OCD without BD. No significant difference was observed for other types of obsessions or compulsions or for the severity of OCD symptoms, although BD type may play a role according to meta-regression analyses. The detection of the presence of sexual or contamination obsessions through a detailed interview may be the focus of clinical attention when assessing OCD in the context of comorbid BD. Sub-phenotyping complex clinical presentation of comorbid psychiatric disorders can aid in making more informed decisions when choosing an appropriate treatment approach.

The Mixed Tendency in Bipolar Disorder: An Operational Proposal for the Integration of Mixed Episodes in Predominant Polarity.

Predominant Polarity (PP) is an established specifier of Bipolar Disorder (BD), holding significant clinical implications. Nevertheless, there exists no consensus on how to incorporate mixed states into PP, leaving patients prone to mixed recurrences that are unclassified. In a comprehensive study involving 701 euthymic BD patients, we sought to redefine PP by introducing a novel metric, the "mixed tendency", and establish a practical threshold to identify patients with a "mixed phenotype". Furthermore, we investigated potential associations between the mixed phenotype and specific PP categories. Our findings revealed that the mixed tendency correlated significantly with early BD type I, lifetime suicide attempts, self-aggressive behaviour, and lifetime number of affective episodes (>5). Using a ROC curve analysis, we determined an optimal cut-off point for the mixed tendency at 0.228, suggesting that patients with ~25% of lifetime mixed episodes relative to total affective episodes should be identified as having a mixed phenotype. Notably, the mixed phenotype was positively associated with undetermined PP and negatively with manic and depressive PP. This study introduces a promising approach to incorporating mixed episodes into the PP definition, potentially enabling tailored interventions for patients with a substantial history of mixed episodes. However, further research in large, longitudinal cohorts is essential to validate these findings.

Should perception of emotions be classified according to threat detection rather than emotional valence? An updated meta-analysis for a whole-brain atlas of emotional faces processing.

BACKGROUND: Human navigation of social interactions relies on the processing of emotion on faces. This meta-analysis aimed to produce an updated brain atlas of emotional face processing from whole-brain studies based on a single emotional face-viewing paradigm (PROSPERO CRD42022251548). METHODS: We conducted a systematic literature search of Embase, MEDLINE and PsycINFO from May 2008 to October 2021. We used seed-based d mapping with permutation of subject images to conduct a quantitative meta-analysis of functional neuroimaging contrasts between emotional (e.g., angry, happy) and neutral faces. We conducted agglomerative hierarchical clustering of meta-analytic map contrasts of emotional faces relative to neutral faces. We investigated lateralization of emotional face processing. RESULTS: From 5549 studies identified, 55 data sets (1489 healthy participants) met our inclusion criteria. Relative to neutral faces, we found extensive activation clusters by fearful faces in the right inferior temporal gyrus, right fusiform area, left putamen and amygdala, right parahippocampalgyrus and cerebellum; we found smaller activation clusters by angry faces in the right cerebellum and right middle temporal gyrus (MTG) and by disgusted faces in the left MTG. Happy and sad faces did not reach statistical significance. Clustering analyses showed similar activation patterns of fearful and angry faces; activation patterns of happy and sad faces showed the least correlation with other emotional faces. Emotional face processing was predominantly left-lateralized in the amygdala and anterior insula, and right-lateralized in the ventromedial prefrontal cortex. LIMITATIONS: Reliance on discretized effect sizes based on peak coordinate location instead of statistical brain maps, and the varying level of statistical threshold reporting from original studies, could lead to underdetection of smaller clusters of activation. CONCLUSION: Processing of emotional faces appeared to be oriented toward identifying threats on faces, from highest (i.e., angry or fearful faces) to lowest level (i.e., happy or sad faces), with a more complex lateralization pattern than previously theorized. Emotional faces may be processed in latent grouping but organized by threat content rather than emotional valence.

Emotion dysregulation in bipolar disorder compared to other mental illnesses: a systematic review and meta-analysis.

People with bipolar disorder (BD) often present emotion dysregulation (ED), a pattern of emotional expression interfering with goal-directed behavior. ED is a transdiagnostic construct, and it is unclear whether it manifests itself similarly in other conditions, such as major depressive disorder (MDD) or borderline personality disorder (BPD), or has specific features in BD. The present systematic review and meta-analysis explored ED and adopted emotion regulation (ER) strategies in BD compared with other psychiatric conditions. PubMed/MEDLINE, EMBASE, Scopus, and PsycINFO databases were systematically searched from inception to April 28th, 2022. Studies implementing validated instruments assessing ED or ER strategies in BD and other psychiatric disorders were reviewed, and meta-analyses were conducted. Twenty-nine studies yielding multiple comparisons were included. BD was compared to MDD in 20 studies (n = 2451), to BPD in six studies (n = 1001), to attention deficit hyperactivity disorder in three studies (n = 232), to anxiety disorders in two studies (n = 320), to schizophrenia in one study (n = 223), and to post-traumatic stress disorder in one study (n = 31). BD patients did not differ from MDD patients in adopting most adaptive and maladaptive ER strategies. However, small-to-moderate differences in positive rumination and risk-taking behaviors were observed. In contrast, patients with BPD presented an overall higher degree of ED and more maladaptive ER strategies. There were insufficient data for a meta-analytic comparison with other psychiatric disorders. The present report further supports the idea that ED is a transdiagnostic construct spanning a continuum across different psychiatric disorders, outlining specific clinical features that could represent potential therapeutic targets.

Correlation between emotion dysregulation and mood symptoms of bipolar disorder: A systematic review and meta-analysis.

BACKGROUND: Emotion dysregulation (ED) is a transdiagnostic construct characterized by difficulties regulating intense emotions. People with bipolar disorder (BD) are more likely to show ED and use maladaptive emotion regulation strategies than adaptive ones. However, little is known about whether ED in BD is a trait or it is rather an epiphenomenon of mood symptoms. METHODS: We conducted a systematic review and meta-analysis of the evidence across major literature databases reporting correlations between measures of emotion regulation (overall ED and different emotion regulation strategies) and measures of depressive and (hypo)manic symptoms in BD from inception until April 12th, 2022. RESULTS: Fourteen studies involving 1371 individuals with BD were included in the qualitative synthesis, of which 11 reported quantitative information and were included in the meta-analysis. ED and maladaptive strategies were significantly higher during periods with more severe mood symptoms, especially depressive ones, while adaptive strategies were lower. CONCLUSION: ED significantly correlates with BD symptomatology, and it mainly occurs during mood alterations. ED may be a target for specific psychotherapeutic and pharmacological treatments, according to precision psychiatry. However, further studies are needed, including patients with mood episodes and longitudinal design, to provide more robust evidence and explore the causal direction of the associations.

Differences in facial emotion recognition between bipolar disorder and other clinical populations: A systematic review and meta-analysis.

Facial emotion (or expression) recognition (FER) is a domain of affective cognition impaired across various psychiatric conditions, including bipolar disorder (BD). We conducted a systematic review and meta-analysis searching for eligible articles published from inception to April 26, 2023, in PubMed/MEDLINE, Scopus, EMBASE, and PsycINFO to examine whether and to what extent FER would differ between people with BD and those with other mental disorders. Thirty-three studies comparing 1506 BD patients with 1973 clinical controls were included in the present systematic review, and twenty-six of them were analyzed in random-effects meta-analyses exploring the discrepancies in discriminating or identifying emotional stimuli at a general and specific level. Individuals with BD were more accurate in identifying each type of emotion during a FER task compared to individuals diagnosed with schizophrenia (SCZ) (SMD = 0.27; p-value = 0.006), with specific differences in the perception of anger (SMD = 0.46; p-value = 1.19e-06), fear (SMD = 0.38; p-value = 8.2e-04), and sadness (SMD = 0.33; p-value = 0.026). In contrast, BD patients were less accurate than individuals with major depressive disorder (MDD) in identifying each type of emotion (SMD = -0.24; p-value = 0.014), but these differences were more specific for sad emotional stimuli (SMD = -0.31; p-value = 0.009). No significant differences were observed when BD was compared with children and adolescents diagnosed with attention-deficit/hyperactivity disorder. FER emerges as a potential integrative instrument for guiding diagnosis by enabling discrimination between BD and SCZ or MDD. Enhancing the standardization of adopted tasks could further enhance the accuracy of this tool, leveraging FER potential as a therapeutic target.

Anxiety and depression played a central role in the COVID-19 mental distress: A network analysis.

INTRODUCTION: Psychological, socio-demographics, and clinical factors play an important role in patients with COVID-19, but their relationship is complex. The network approach might be used to disentangle complex interactions in different systems. Using data from a multicentre, cross-sectional, survey among patients with COVID-19 in Spain (July-November 2020), we investigated the network structure of mental disorders symptoms, social support, and psychological resilience, and changes in network structures according to the presence of a pre-existing mental disorder or hospitalization for COVID-19. METHODS: Subjects completed a survey to evaluate sociodemographic characteristics, COVID-19 infection status, resilience, social support, and symptoms of depression, anxiety disorders, post-traumatic stress disorder, panic attacks, and substance use disorder. 2084 patients with COVID-19 were included in the analysis. Network analysis was conducted to evaluate network and bridge centrality, and the network properties were compared between COVID-19 patients with and without a history of lifetime mental disorder, and between hospitalized and non-hospitalized patients. LIMITATIONS: Generalization of our findings may be difficult since differences in network connectivity may exist in different populations or samples. RESULTS: Anxiety and depression showed high centrality in patients with COVID-19 and anxiety showed the highest bridge influence in the network. Resilience and social support showed a low influence on mental disorder symptoms. Global network estimations show no statistically significant changes between patients with and without pre-existing mental disorders or between hospitalized and non-hospitalized patients. CONCLUSIONS: Anxiety might be a key treatment target in patients with COVID-19 since its treatment might prevent other mental health adverse outcomes.

Association between childhood maltreatment and social functioning in individuals with affective disorders: A systematic review and meta-analysis.

OBJECTIVE: Childhood maltreatment has been linked to impairments in social functioning and social cognition in adults with affective disorders. However, conclusions have been limited by inconsistent findings across different maltreatment subtypes and social domains. We conducted a systematic review and meta-analysis to quantify associations between childhood maltreatment (overall and subtypes - physical, emotional and/or sexual abuse, and/or physical and/or emotional neglect) and different domains of social functioning and social cognition in adults with affective disorders (bipolar disorder or major depressive disorder). We also examined effect moderators and mediators of these associations. METHODS: A systematic search was performed on 12.12.2022 which identified 29 studies included in qualitative synthesis (n = 3022 individuals with affective disorders), of which 27 (n = 2957) were pooled in meta-analyses. Across studies, five social functioning and five social cognition domains were examined, of which four domains of social functioning and two domains of social cognition had sufficient data for meta-analysis (PROSPERO CRD42022288976). RESULTS: Social functioning: childhood maltreatment was associated with lower global social functioning (r = -0.11 to -0.20), poorer interpersonal relations (r = -0.18 to -0.33), and with aggressive behaviour (r = 0.20-0.29) but was unrelated to vocational functioning. Emotional abuse and emotional neglect showed the largest magnitudes of effect. Social cognition: there was no meta-analytic evidence of associations between maltreatment and social cognition domains. Exploratory moderation analyses did not identify any consistent moderators. Narrative synthesis identified attachment style as possible moderator, and sensory patterns, anxiety, and depressive symptoms as possible mediators between childhood maltreatment and social outcomes. Overall, the available evidence was limited, particularly in relation to social cognition. CONCLUSIONS: Adults with affective disorders are at risk of social functioning difficulties after childhood maltreatment exposure, an effect observed across multiple maltreatment subtypes, social functioning domains, and diagnoses. Addressing social functioning problems may benefit maltreated adults with both bipolar disorder and major depressive disorder.

Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study.

BACKGROUND: Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture. OBJECTIVE: Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS: We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses. RESULTS: Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with "increased motor activity" (NMI>0.55), "insomnia" (NMI=0.6), and "motor inhibition" (NMI=0.75). EDA was associated with "aggressive behavior" (NMI=1.0) and "psychic anxiety" (NMI=0.52). CONCLUSIONS: Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.

Psychotropic drug repurposing for COVID-19: A Systematic Review and Meta-Analysis.

Several psychotropic drugs, including antidepressants (AD), mood stabilizers, and antipsychotics (AP) have been suggested to have favorable effects in the treatment of COVID-19. The aim of this systematic review and meta-analysis was to collect evidence from studies concerning the scientific evidence for the repurposing of psychotropic drugs in COVID-19 treatment. Two independent authors searched PubMed-MEDLINE, Scopus, PsycINFO, and ClinicalTrials.gov databases, and reviewed the reference lists of articles for eligible articles published up to 13th December 2021. All computational, preclinical and clinical (observational and/or RCTs) studies on the effect of any psychotropic drug on Sars-CoV-2 or patients with COVID-19 were considered for inclusion. We conducted random effect meta-analyses on clinical studies reporting the effect of AD or AP on COVID-19 outcomes. 29 studies were included in the synthesis: 15 clinical, 9 preclinical, and 5 computational studies. 9 clinical studies could be included in the quantitative analyses. AD did not increase the risk of severe COVID-19 (RR= 1.71; CI 0.65-4.51) or mortality (RR=0.94; CI 0.81-1.09). Fluvoxamine was associated with a reduced risk of mortality for COVID-19 (OR=0.15; CI 0.02-0.95). AP increased the risk of severe COVID-19 (RR=3.66; CI 2.76-4.85) and mortality (OR=1.53; CI 1.15-2.03). Fluvoxamine might be a possible candidate for psychotropic drug repurposing in COVID-19 due to its anti-inflammatory and antiviral potential, while evidence on other AD is still controversial. Although AP are associated with worse COVID-19 outcomes, their use should be evaluated case to case and ongoing treatment with antipsychotics should be not discontinued in psychiatric patients.

Melancholic features and typical neurovegetative symptoms of major depressive disorder show specific polygenic patterns.

BACKGROUND: Major depressive disorder (MDD) is a highly prevalent psychiatric condition characterised by a heterogeneous clinical presentation and an estimated twin-based heritability of ~40-50 %. Different clinical MDD subtypes might partly reflect distinctive underlying genetics. This study aims to investigate if polygenic risk scores (PRSs) for different psychiatric disorders, personality traits, and substance use-related traits may be associated with different clinical subtypes of MDD (i.e., MDD with melancholic or psychotic features), higher symptom severity, or different clusters of depressive symptoms (i.e., sadness symptoms, typical neurovegetative symptoms, detachment symptoms, and negative thoughts). METHODS: The target sample included 1149 patients with MDD, recruited by the European Group for the Study of Resistant Depression. PRSs for 25 psychiatric disorders and traits were computed based on the most recent publicly available summary statistics of the largest genome-wide association studies. PRSs were then used as predictors in regression models, adjusting for age, sex, population stratification, and recruitment sites. RESULTS: Patients with MDD having higher PRS for MDD and loneliness were more likely to exhibit melancholic features of MDD (p = 0.0009 and p = 0.005, respectively). Moreover, patients with higher PRS for alcohol intake and post-traumatic stress disorder were more likely to experience greater typical neurovegetative symptoms (p = 0.0012 and p = 0.0045, respectively). LIMITATIONS: The proportion of phenotypic variance explained by the PRSs was limited. CONCLUSIONS: This study suggests that melancholic features and typical neurovegetative symptoms of MDD may show distinctive underlying genetics. Our findings provide a new contribution to the understanding of the genetic heterogeneity of MDD.

Affective temperaments mediate aggressive dimensions in bipolar disorders: A cluster analysis from a large, cross-sectional, international study.

BACKGROUND: Affective temperaments show potential for aggressive behavior (AB) preventive strategies in bipolar disorder (BD). We aim to define intra-diagnostic subgroups of patients with BD based on homogeneous behaviors related to AB. Subsequently, to assess whether affective temperament dimensions may contribute to the presence and severity of AB. METHODS: Patients with BD were recruited. AB was evaluated through the modified overt aggression scale (MOAS); affective temperaments were assessed with the TEMPS-A. A cluster analysis was conducted based on TEMPS-A and MOAS scores. Stepwise backward logistic regression models were used to identify the predictive factors of cluster membership. RESULTS: 799 patients with BD were enrolled. Three clusters were determined: non-aggressive (55.5 %), self-aggressive (18 %), and hetero-aggressive (26.5 %). Depressive, irritable, and anxious temperament scores significantly increased from the non-aggressive (lower) to the self-aggressive (intermediate) and the hetero-aggressive group (highest). A positive history of a suicide attempt (B = 5.131; OR = 169.2, 95 % CI 75.9; 377) and rapid cycling (B = -0.97; OR = 0.40, 95 % CI 0.17; 0.95) predicted self-aggressive cluster membership. Atypical antipsychotics (B = 1.19; OR = 3.28, 95 % CI 2.13; 5.06) or SNRI treatment (B = 1.09; OR = 3, 95 % CI 1.57; 5.71), psychotic symptoms (B = 0.73; OR = 2.09, 95 % CI 1.34; 3.26), and history of a suicide attempt (B = -1.56; OR = 0.20, 95 % CI 0.11; 0.38) predicted hetero-aggressive cluster membership. LIMITATIONS: Recall bias might have affected the recollection of AB. CONCLUSIONS: Clinical factors orientate the prevention of different ABs in BD. Affective temperaments might play a role in preventing AB since patients with more pronounced affective temperaments might have an increased risk of showing AB, in particular hetero-AB.

Patterns of antipsychotic prescription and accelerometer-based physical activity levels in people with schizophrenia spectrum disorders: a multicenter, prospective study.

Antipsychotic polypharmacy (APP) in patients with schizophrenia spectrum disorders (SSDs) is usually not recommended, though it is very common in clinical practice. Both APP and SSDs have been linked to worse health outcomes and decreased levels of physical activity, which in turn is an important risk factor for cardiovascular diseases and premature mortality. This real-world, observational study aimed to investigate antipsychotic prescribing patterns and physical activity in residential patients and outpatients with SSDs. A total of 620 patients and 114 healthy controls were recruited in 37 centers across Italy. Each participant underwent a comprehensive sociodemographic and clinical evaluation. Physical activity was monitored for seven consecutive days through accelerometer-based biosensors. High rates of APP were found in all patients, with residential patients receiving more APP than outpatients, probably because of greater psychopathological severity. Physical activity was lower in patients compared to controls. However, patients on APP showed trends of reduced sedentariness and higher levels of light physical activity than those in monopharmacy. Rehabilitation efforts in psychiatric residential treatment facilities were likely to result in improved physical activity performances in residential patients. Our findings may have important public health implications, as they indicate the importance of reducing APP and encouraging physical activity.

Defining clinical characteristics of emotion dysregulation in bipolar disorder: A systematic review and meta-analysis.

Emotion dysregulation (ED) is characterized by rigid and frequent use of maladaptive emotion regulation (ER) strategies. Conceptualized as a transdiagnostic feature, ED may occur in both clinical and non-clinical populations, including people diagnosed with bipolar disorder (BD) and their first-degree relatives (FDRs), though expected to manifest with differential clinical features. To this end, we conducted a systematic review and meta-analysis of the literature comparing people with BD to healthy controls (HCs) or FDRs, from inception up to November 25, 2021, across major databases. Random-effects meta-analyses considered twenty-eight studies assessing ER/ED with a validated scale. Patients with BD differed from HCs in adopting more maladaptive ER strategies, such as rumination, risk-taking behaviors, negative focus, and less adaptive ones. Unaffected FDRs differed from people with BD, yet to a lower extent, suggesting that ED may span a continuum. ED in BD should be widely explored to better understand its course and management, with specific interventions aimed at reducing its burden on both high-risk and full-threshold populations.

Machine Learning Prediction of Comorbid Substance Use Disorders among People with Bipolar Disorder.

Substance use disorder (SUD) is a common comorbidity in individuals with bipolar disorder (BD), and it is associated with a severe course of illness, making early identification of the risk factors for SUD in BD warranted. We aimed to identify, through machine-learning models, the factors associated with different types of SUD in BD. We recruited 508 individuals with BD from a specialized unit. Lifetime SUDs were defined according to the DSM criteria. Random forest (RF) models were trained to identify the presence of (i) any (SUD) in the total sample, (ii) alcohol use disorder (AUD) in the total sample, (iii) AUD co-occurrence with at least another SUD in the total sample (AUD+SUD), and (iv) any other SUD among BD patients with AUD. Relevant variables selected by the RFs were considered as independent variables in multiple logistic regressions to predict SUDs, adjusting for relevant covariates. AUD+SUD could be predicted in BD at an individual level with a sensitivity of 75% and a specificity of 75%. The presence of AUD+SUD was positively associated with having hypomania as the first affective episode (OR = 4.34 95% CI = 1.42-13.31), and the presence of hetero-aggressive behavior (OR = 3.15 95% CI = 1.48-6.74). Machine-learning models might be useful instruments to predict the risk of SUD in BD, but their efficacy is limited when considering socio-demographic or clinical factors alone.