Large-scale brain connectivity changes following the administration of lysergic acid diethylamide, d-amphetamine, and 3,4-methylenedioxyamphetamine.

Psychedelics have recently attracted significant attention for their potential to mitigate symptoms associated with various psychiatric disorders. However, the precise neurobiological mechanisms responsible for these effects remain incompletely understood. A valuable approach to gaining insights into the specific mechanisms of action involves comparing psychedelics with substances that have partially overlapping neurophysiological effects, i.e., modulating the same neurotransmitter systems. Imaging data were obtained from the clinical trial NCT03019822, which explored the acute effects of lysergic acid diethylamide (LSD), d-amphetamine, and 3,4-methylenedioxymethamphetamine (MDMA) in 28 healthy volunteers. The clinical trial employed a double-blind, placebo-controlled, crossover design. Herein, various resting-state connectivity measures were examined, including within-network connectivity (integrity), between-network connectivity (segregation), seed-based connectivity of resting-state networks, and global connectivity. Differences between placebo and the active conditions were assessed using repeated-measures ANOVA, followed by post-hoc pairwise t-tests. Changes in voxel-wise seed-based connectivity were correlated with serotonin 2 A receptor density maps. Compared to placebo, all substances reduced integrity in several networks, indicating both common and unique effects. While LSD uniquely reduced integrity in the default-mode network (DMN), the amphetamines, in contrast to our expectations, reduced integrity in more networks than LSD. However, LSD exhibited more pronounced segregation effects, characterized solely by decreases, in contrast to the amphetamines, which also induced increases. Across all substances, seed-based connectivity mostly increased between networks, with LSD demonstrating more pronounced effects than both amphetamines. Finally, while all substances decreased global connectivity in visual areas, compared to placebo, LSD specifically increased global connectivity in the basal ganglia and thalamus. These findings advance our understanding of the distinctive neurobiological effects of psychedelics, prompting further exploration of their therapeutic potential.

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.

Longitudinal changes in resting-state functional connectivity as markers of vulnerability or resilience in first-degree relatives of patients with bipolar disorder.

BACKGROUND: There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives. METHODS: In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years. RESULTS: At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker. CONCLUSION: Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

Removing the effects of the site in brain imaging machine-learning - Measurement and extendable benchmark.

Multisite machine-learning neuroimaging studies, such as those conducted by the ENIGMA Consortium, need to remove the differences between sites to avoid effects of the site (EoS) that may prevent or fraudulently help the creation of prediction models, leading to impoverished or inflated prediction accuracy. Unfortunately, we have shown earlier that current Methods Aiming to Remove the EoS (MAREoS, e.g., ComBat) cannot remove complex EoS (e.g., including interactions between regions). And complex EoS may bias the accuracy. To overcome this hurdle, groups worldwide are developing novel MAREoS. However, we cannot assess their effectiveness because EoS may either inflate or shrink the accuracy, and MAREoS may both remove the EoS and degrade the data. In this work, we propose a strategy to measure the effectiveness of a MAREoS in removing different types of EoS. FOR MAREOS DEVELOPERS, we provide two multisite MRI datasets with only simple true effects (i.e., detectable by most machine-learning algorithms) and two with only simple EoS (i.e., removable by most MAREoS). First, they should use these datasets to fit machine-learning algorithms after applying the MAREoS. Second, they should use the formulas we provide to calculate the relative accuracy change associated with the MAREoS in each dataset and derive an EoS-removal effectiveness statistic. We also offer similar datasets and formulas for complex true effects and EoS that include first-order interactions. FOR MACHINE-LEARNING RESEARCHERS, we provide an extendable benchmark website to show: a) the types of EoS they should remove for each given machine-learning algorithm and b) the effectiveness of each MAREoS for removing each type of EoS. Relevantly, a MAREoS only able to remove the simple EoS may suffice for simple machine-learning algorithms, whereas more complex algorithms need a MAREoS that can remove more complex EoS. For instance, ComBat removes all simple EoS as needed for predictions based on simple lasso algorithms, but it leaves residual complex EoS that may bias the predictions based on standard support vector machine algorithms.

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.

Aberrant resting-state functional connectivity underlies cognitive and functional impairments in remitted patients with bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is commonly associated with cognitive impairments, that directly contribute to patients' functional disability. However, there is no effective treatment targeting cognition in BD. A key reason for the lack of pro-cognitive interventions is the limited insight into the brain correlates of cognitive impairments in these patients. This is the first study investigating the resting-state neural underpinnings of cognitive impairments in different neurocognitive subgroups of patients with BD. METHOD: Patients with BD in full or partial remission and healthy controls (final sample of n = 144 and n = 50, respectively) underwent neuropsychological assessment and resting-state functional magnetic resonance imaging. We classified the patients into cognitively impaired (n = 83) and cognitively normal (n = 61) subgroups using hierarchical cluster analysis of the four cognitive domains. We used independent component analysis (ICA) to investigate the differences between the neurocognitive subgroups and healthy controls in resting-state functional connectivity (rsFC) in the default mode network (DMN), executive central network (ECN), and frontoparietal network (FPN). RESULTS: Cognitively impaired patients displayed greater positive rsFC within the DMN and less negative rsFC within the ECN than healthy controls. Across cognitively impaired patients, lower positive connectivity within DMN and lower negative rsFC within ECN correlated with worse global cognitive performance. CONCLUSION: Cognitive impairments in BD seem to be associated with a hyper-connectivity within the DMN, which may explain the failure to suppress task-irrelevant DMN activity during the cognitive performance, and blunted anticorrelation in the ECN. Thus, aberrant connectivity within the DMN and ECN may serve as brain targets for pro-cognitive interventions.

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.

Psychological trauma as a transdiagnostic risk factor for mental disorder: an umbrella meta-analysis.

This umbrella review is the first to systematically examine psychological trauma as a transdiagnostic risk factor across psychiatric conditions. We searched Pubmed, Scopus, and PsycNET databases from inception until 01/05/2021 for systematic reviews/meta-analyses evaluating the association between psychological trauma and at least one diagnosed mental disorder. We re-calculated the odds ratio (OR), then classified the association as convincing, highly suggestive, suggestive, or weak, based on the number of cases and controls with and without psychological trauma, random-effects p value, the 95% confidence interval of the largest study, heterogeneity between studies, 95% prediction interval, small-study effect, and excess significance bias. Additional outcomes were the association between specific trauma types and specific mental disorders, and a sensitivity analysis for childhood trauma. Transdiagnosticity was assessed using TRANSD criteria. The review was pre-registered in Prospero CRD42020157308 and followed PRISMA/MOOSE guidelines. Fourteen reviews met inclusion criteria, comprising 16,277 cases and 77,586 controls. Psychological trauma met TRANSD criteria as a transdiagnostic factor across different diagnostic criteria and spectra. There was highly suggestive evidence of an association between psychological trauma at any time-point and any mental disorder (OR = 2.92) and between childhood trauma and any mental disorder (OR = 2.90). Regarding specific trauma types, convincing evidence linked physical abuse (OR = 2.36) and highly suggestive evidence linked sexual abuse (OR = 3.47) with a range of mental disorders, and convincing evidence linked emotional abuse to anxiety disorders (OR = 3.05); there were no data for emotional abuse with other disorders. These findings highlight the importance of preventing early traumatic events and providing trauma-informed care in early intervention and psychiatric services.

Functional neuroanatomy of craving in heroin use disorder: voxel-based meta-analysis of functional magnetic resonance imaging (fMRI) drug cue reactivity studies.

Background: The neuroanatomy of craving, typically investigated using the functional magnetic resonance imaging (fMRI) drug cue reactivity (FDCR) paradigm, has been shown to involve the mesocorticolimbic, nigrostriatal, and corticocerebellar systems in several substances. However, the neuroanatomy of craving in heroin use disorder is still unclear.Objective: The current meta-analysis examines previous research on the neuroanatomy of craving in abstinent individuals with opioid use disorder (OUD).Method: Seven databases were searched for studies comparing abstinent OUD versus healthy controls on drug > neutral contrast interaction at the whole-brain level. Voxel-based meta-analysis was performed using seed-based d mapping with permuted subject images (SDM-PSI). Thresholds were set at a family-wise error rate of less than 5% with the default pre-processing parameters of SDM-PSI.Results: A total of 10 studies were included (296 OUD and 187 controls). Four hyperactivated clusters were identified with Hedges' g of peaks that ranged from 0.51 to 0.82. These peaks and their associated clusters correspond to the three systems identified in the previous literature: a) mesocorticolimbic, b) nigrostriatal, and c) corticocerebellar. There were also newly revealed hyperactivation regions including the bilateral cingulate, precuneus, fusiform gyrus, pons, lingual gyrus, and inferior occipital gyrus. The meta-analysis did not reveal areas of hypoactivation.Conclusion: Recommendations based on the functional neuroanatomical findings of this meta-analysis include pharmacological interventions such as buprenorphine/naloxone and cognitive-behavioral treatments such as cue-exposure combined with HRV biofeedback. In addition, research should utilize FDCR as pre- and post-measurement to determine the effectiveness and mechanism of action of such interventions.

Increasing prevalence of self-harm, suicidal behavior and suicidal ideation throughout a three-year period in the context of COVID-19 pandemic in Spain.

The COVID-19 pandemic had a great impact on mental health both in the general population and in individuals with preexisting mental disorders. Lockdown, social restrictions, changes in daily habits and limited access to health services led to changes in consultations in mental health services. This study aimed to determine changing trends in psychiatric admissions by the inclusion of adult patients admitted to the Emergency Department (ED) of Hospital Clínic of Barcelona between 2019 and 2021. Acute admissions, social issues and psychiatric diagnoses were compared between years, seasons and considering the interaction between both years and seasons. A total of 13,677 individuals were included in the analysis. An overall reduction in consultations to the ED and a higher proportion of acute admissions was observed in 2020 in context of the COVID-19 outbreak. Increased prevalence of sleeping disorders and substance use disorders was found in 2020. Self-harming behavior, suicidal thoughts and suicidal behavior showed an increasing tendency over time, with their highest rates in 2021. Prevention and management strategies should be considered in order to address increasing needs in mental health care.

Do classic psychedelics increase the risk of seizures? A scoping review.

Seizures are a concerning adverse event frequently associated with the use of psychedelics, and hence, studies involving these substances tend to exclude patients with past history of epilepsy. This is especially relevant because epileptic seizures are markedly increased in the population suffering from mental disorders, and psychedelic assisted therapy is being researched as a promising treatment for several of them. To determine the extent of the current literature on the relationship between classic psychedelics and seizures, a scoping review was performed using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). The search was conducted in PubMed, Web of Science, Google scholar, LILACS and Scielo, and both animal and human models were included. A total of 16 publications on humans, and 11 on animals, were found. The results are heterogeneous, but globally suggest that psychedelics may not increase the risk of seizures in healthy individuals or animals in the absence of other drugs. However, concomitant use of other substances or drugs, such as kambo or lithium, could increase the risk of seizures. Additionally, these conclusions are drawn from data lacking sufficient external validity, so they should be interpreted with caution. Future paths for research and a summary on possible neurobiological underpinnings that might clarify the relationship between classical psychedelics and seizures are also provided.

Coping behaviors to reduce anxiety and depressive symptoms: A prospective repeated assessment study.

INTRODUCTION: Health institutions provide general recommendations to cope with global crises such as pandemics or geopolitical tensions. However, these recommendations are mainly based on cross-sectional evidence. The preregistered Repeated Assessment of Behaviors and Symptoms in the Population (RABSYPO) study sought to establish prospective longitudinal evidence from a cohort with a demographic distribution similar to that of the Spanish population to provide evidence for developing solid universal recommendations to reduce anxiety and depressive symptoms during times of uncertainty. MATERIAL AND METHODS: We first recruited via social networks a pool of Spanish individuals willing to participate and then randomly selected some within each stratum of age×gender×region×urbanicity to conduct a one-year-long bi-weekly online follow-up about the frequency of ten simple potential coping behaviors as well as anxiety (GAD-7) and depressive symptoms (PHQ-9). Mixed-effects autoregressive moving average models were used to analyze the relationship between past behaviors' frequency and subsequent symptom changes across the twenty-seven time points. RESULTS: Among the 1049 who started the follow-up, 942 completed it and were included in the analyses. Avoiding excessive exposure to distressing news and maintaining a healthy/balanced diet, followed by spending time outdoors and physical exercise, were the coping behaviors most strongly associated with short and long-term reductions of anxiety and depressive symptoms. Engaging in relaxing activities and drinking water to hydrate were only associated with short-term symptom reductions. Socializing was associated with symptom reductions in the long term. CONCLUSIONS: This study provides compelling prospective evidence that adopting a set of simple coping behaviors is associated with small but significant reductions in anxiety and depressive symptoms during times of uncertainty. It also includes a layman's summary of this evidence to help develop general recommendations that serve as universal tools for enhancing mental health and well-being.

Lateralized grey matter volume changes in adolescents versus adults with major depression: SDM-PSI meta-analysis.

The current study is the first meta-analysis to examine grey matter volume (GMV) changes in adolescents and across the lifespan in major depressive disorder (MDD). Seed-based d mapping-with permutation of subject images (SDM-PSI) has advantages over previous coordinate-based meta-analytical methods (CBMA), such as reducing bias (via the MetaNSUE algorithm) and including non-statistically significant unreported effects. SDM-PSI was used to analyze 105 whole-brain GMV voxel-based morphometry (VBM) studies comparing 6,530 individuals with MDD versus 6,821 age-matched healthy controls (HC). A laterality effect was observed in which adults with MDD showed lower GMV than adult HC in left fronto-temporo-parietal structures (superior temporal gyrus, insula, Rolandic operculum, and inferior frontal gyrus). However, these abnormalities were not statistically significant for adolescent MDD versus adolescent HC. Instead, adolescent MDD showed lower GMV than adult MDD in right temporo-parietal structures (angular gyrus and middle temporal gyrus). These regional differences may be used as potential biomarkers to predict and monitor treatment outcomes as well as to choose the most effective treatments in adolescents versus adults. Finally, due to the paucity of youth, older adult, and longitudinal studies, future studies should attempt to replicate these GMV findings and examine whether they correlate with treatment response and illness severity.

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.

Development and Validation of a Smartphone-Based App for the Longitudinal Assessment of Anxiety in Daily Life.

Current methods to assess human anxiety often ignore that anxiety is a dynamic process and have limitations such as high recall bias and low generalizability to real life. Smartphone apps using ecological momentary assessment (EMA) may overcome such limitations. We developed a smartphone app for the longitudinal evaluation of anxiety symptoms using EMA. We assessed the feasibility (retention and compliance) and psychometric properties (reliability and validity) of the app over 6 months in a sample of 99 participants with different levels of anxiety. The EMA-based smartphone app was highly feasible. It showed excellent within-person and between-person reliability, high convergent and moderate discriminant validity, and significant incremental validity. Assessing anxiety longitudinally using a smartphone and following EMA principles is feasible and can be reliable and valid. Studies combining EMA-based anxiety longitudinal assessments with other assessment methods deserve further research and may offer novel insights into human anxiety.

Study protocol - elucidating the neural correlates of functional remediation for older adults with bipolar disorder.

Introduction: Beyond mood abnormalities, bipolar disorder (BD) includes cognitive impairments that worsen psychosocial functioning and quality of life. These deficits are especially severe in older adults with BD (OABD), a condition expected to represent most individuals with BD in the upcoming years. Restoring the psychosocial functioning of this population will thus soon represent a public health priority. To help tackle the problem, the Bipolar and Depressive Disorders Unit at the Hospital Clínic of Barcelona has recently adapted its Functional Remediation (FR) program to that population, calling it FROA-BD. However, while scarce previous studies localize the neural mechanisms of cognitive remediation interventions in the dorsal prefrontal cortex, the specific mechanisms are seldom unknown. In the present project, we will investigate the neural correlates of FR-OABD to understand its mechanisms better and inform for potential optimization. The aim is to investigate the brain features and changes associated with FROA-BD efficacy. Methods: Thirty-two individuals with OABD in full or partial remission will undergo a magnetic resonance imaging (MRI) session before receiving FR-OABD. After completing the FR-OABD intervention, they will undergo another MRI session. The MRI sessions will include structural, diffusion-weighted imaging (DWI), functional MRI (fMRI) with working memory (n-back) and verbal learning tasks, and frontal spectroscopy. We will correlate the pre-post change in dorsolateral and dorsomedial prefrontal cortices activation during the n-back task with the change in psychosocial functioning [measured with the Functioning Assessment Short Test (FAST)]. We will also conduct exploratory whole-brain correlation analyses between baseline or pre-post changes in MRI data and other clinical and cognitive outcomes to provide more insights into the mechanisms and explore potential brain markers that may predict a better treatment response. We will also conduct separate analyses by sex. Discussion: The results of this study may provide insights into how FROA-BD and other cognitive remediations modulate brain function and thus could optimize these interventions.

Meta-analysis of the effects of adjuvant drugs in co-occurring bipolar and substance use disorder.

BACKGROUND: Individuals with bipolar disorder (BD) often have co-occurring substance use disorders (SUDs), which substantially impoverish the course of illness. Despite the importance of this dual diagnosis, the evidence of the efficacy and safety of adjuvant treatments is mostly unknown. OBJECTIVE: To perform a meta-analysis to evaluate the efficacy and safety of adjuvant drugs in patients with co-occurring BD and SUD. METHODS: We searched PubMed, Scopus, and Web of Knowledge until 30th April 2022 for randomized clinical trials (RCT) evaluating the efficacy and safety of adjuvant drugs compared to placebo in patients with a dual diagnosis of BD and SUD. We meta-analyzed the effect of adjuvant drugs on general outcomes (illness severity, mania, depression, anxiety, abstinence, substance craving, substance use, gamma-GT, adherence, and adverse events) and used the results to objectively assess the quality of the evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. For completeness, we also report the specific effects of specific adjuvant drugs in patients with specific substance disorders. RESULTS: We included 15 RCT studies (9 alcohol, 3 cocaine, 2 nicotine, and 1 cannabis) comprising 628 patients allocated to treatment and 622 to placebo. There was low-quality evidence that adjuvant drugs may reduce illness severity (g=-0.25, 95% CI: -0.44, -0.06), and very-low quality evidence that they may decrease substance use (g=-0.23, 95% CI: -0.44, -0.02) and increase substance abstinence (g=0.21, 95% CI: 0.04, 0.38). DISCUSSION: There is low-quality evidence that adjuvant drugs may help reduce illness severity, probably via facilitating abstinence and lower substance use. However, the evidence is weak; thus, these results should be considered cautiously until better evidence exists.

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.

Upward trends in eating disorders, self-harm, and suicide attempt emergency admissions in female adolescents after COVID-19 lockdown.

INTRODUCTION: Increased mental health problems have been reported in children and adolescents related to the COVID-19 lockdown and its immediate aftermath, especially among adolescent females. However, the longer-term impact of persistent quarantine measures and social restrictions on this population is yet to be further explored. MATERIALS AND METHODS: We compared the number of children/adolescents admissions to the psychiatric emergency department (ED) of Hospital Clínic de Barcelona during the COVID-19 lockdown and the following year with the numbers of admissions the year before lockdown, adjusting for variations in the population. We also conducted separate analyses by gender, age group, and diagnostic categories. Finally, we also repeated the analyses considering the cumulated deficit/excess since the start of the lockdown. Statistical significance was estimated using binomial tests with Bonferroni correction. RESULTS: A total of 2425 admissions were recorded. Globally, admission rates decreased during the lockdown (46%) and progressively increased during the one-year aftermath (43% by spring 2021). This increase was particularly high in adolescent females (85%) while unclear in children and/or males. The main diagnostic categories involved were anxiety, depressive, and eating disorders, as well as self-harm behavior, suicidal ideation, and suicide attempts. The increase in eating disorders, self-harm behavior, and suicide attempts admissions in female adolescents remained statistically significant when considering the cumulated deficit/excess. CONCLUSIONS: We found increased ED admissions during the aftermath of the COVID-19 lockdown among adolescent females. We recommend strengthening the attention to this population to provide adequate specialized care and prevention strategies.

Improved estimation of the risk of manic relapse by combining clinical and brain scan data.

INTRODUCTION: Estimating the risk of manic relapse could help the psychiatrist individually adjust the treatment to the risk. Some authors have attempted to estimate this risk from baseline clinical data. Still, no studies have assessed whether the estimation could improve by adding structural magnetic resonance imaging (MRI) data. We aimed to evaluate it. MATERIAL AND METHODS: We followed a cohort of 78 patients with a manic episode without mixed symptoms (bipolar type I or schizoaffective disorder) at 2-4-6-9-12-15-18 months and up to 10 years. Within a cross-validation scheme, we created and evaluated a Cox lasso model to estimate the risk of manic relapse using both clinical and MRI data. RESULTS: The model successfully estimated the risk of manic relapse (Cox regression of the time to relapse as a function of the estimated risk: hazard ratio (HR)=2.35, p=0.027; area under the curve (AUC)=0.65, expected calibration error (ECE)<0.2). The most relevant variables included in the model were the diagnosis of schizoaffective disorder, poor impulse control, unusual thought content, and cerebellum volume decrease. The estimations were poorer when we used clinical or MRI data separately. CONCLUSION: Combining clinical and MRI data may improve the risk of manic relapse estimation after a manic episode. We provide a website that estimates the risk according to the model to facilitate replication by independent groups before translation to clinical settings.