Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): protocol for a pragmatic observational clinical study.

BACKGROUND: Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions. AIMS: The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder. METHOD: We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania (n = 12), depression (n = 12 with bipolar disorder and n = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features (n = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients. RESULTS: Recruitment is ongoing. CONCLUSIONS: This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.

Validation of the Spanish Childhood Trauma Questionnaire-Short Form in adolescents with suicide attempts.

Background: Child maltreatment is associated with a higher probability of mental disorders and suicidal behavior in adolescence. Therefore, accurate psychometric instruments are essential to assess this. Objective: To validate the Spanish version of the Childhood Trauma Questionnaire-Short Form (CTQ-SF) in adolescents with suicide attempts. Methods: Multisite cohort study of 208 adolescents with suicide attempts using data from the following scales: Mini International Neuropsychiatric Interview (MINI), Columbia Suicide Severity Rating Scale (C-SSRS), Patient Health Questionnaire (PHQ-9), and CTQ-SF. Statistical analysis: CTQ-SF scores analyzed by descriptive statistics. Internal consistency: McDonald's omega and Cronbach's alpha. Concurrent validity with PHQ-9 and C-SSRS scores: Spearman correlation coefficient. Structural validity: Confirmatory factor analysis. Results: Floor and ceiling effects: Physical abuse and neglect as well as sexual abuse demonstrated high floor effects (50.0, 35.1, and 61.1% of adolescents, respectively). No ceiling effects were found. The CTQ-SF had excellent internal consistency (McDonald's omega = 0.94), as did the majority of its subscales (Cronbach's alpha 0.925-0.831) except for physical neglect (0.624). Its concurrent validity was modest, and the emotional neglect subscale had the lowest Spearman correlation coefficients (0.067-0.244). Confirmatory factor analysis: Compared with alternative factor structures, the original CTQ-SF model (correlated 5-factor) exhibited a better fit [S-B χ 2 = 676.653, p < 0; RMSEA (90% CI = 0.076-0.097) = 0.087; SRMR = 0.078; CFI = 0.980; TLI = 0.978]. Conclusion: The Spanish CTQ-SF is a reliable, valid instrument for assessing traumatic experiences in adolescents at high risk of suicide. It appears appropriate for use in routine clinical practice to monitor maltreatment in this group.

The functioning assessment short test (FAST): Clinically meaningful response threshold in patients with major depressive disorder receiving antidepressant treatment.

BACKGROUND: Functional impairment is common in patients with major depressive disorder (MDD). The Functioning Assessment Short Test (FAST) provides a detailed clinician-rated assessment of functioning across multiple aspects of daily life. This study aimed to establish clinically relevant response thresholds for the FAST in patients with MDD receiving antidepressant treatment. METHODS: Data were derived from three 8-week clinical trials of antidepressant therapy in patients with MDD that included assessment of functioning using the FAST as a pre-specified endpoint. The minimal clinically important difference (MCID) and threshold for response in terms of change in FAST total score were determined using anchor-based methods. RESULTS: After 8 weeks of antidepressant treatment, the mean reduction in FAST total score in patients considered clinically minimally improved (Clinical Global Impression-Improvement [CGII] score of 3) was 7-9 points (~20 % reduction). The threshold for functional response (reduction in FAST total score from baseline in patients with a CGI-I score of ≤2 at week 8) was 16-19 points (~50 % reduction). The threshold for functional response was higher in patients with MDD and comorbid generalized anxiety disorder than in those with MDD alone (mean reduction in FAST total score at 8 weeks: 26 points [63 %]). LIMITATIONS: Short-term studies. CONCLUSIONS: These results provide further validation of the FAST for assessing functioning in patients with MDD. In patients with MDD, the suggested MCID for FAST total score is 7-9 points and the proposed threshold for response is a reduction from baseline of approximately 50 %.

Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.

BACKGROUND: Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MD detection. OBJECTIVE: In this paper, we overcame this data bottleneck and advanced the detection of acute MD episodes from wearables' data on the back of recent advances in self-supervised learning (SSL). This approach leverages unlabeled data to learn representations during pretraining, subsequently exploited for a supervised task. METHODS: We collected open access data sets recording with the Empatica E4 wristband spanning different, unrelated to MD monitoring, personal sensing tasks-from emotion recognition in Super Mario players to stress detection in undergraduates-and devised a preprocessing pipeline performing on-/off-body detection, sleep/wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduced E4SelfLearning, the largest-to-date open access collection, and its preprocessing pipeline. We developed a novel E4-tailored transformer (E4mer) architecture, serving as the blueprint for both SSL and fully supervised learning; we assessed whether and under which conditions self-supervised pretraining led to an improvement over fully supervised baselines (ie, the fully supervised E4mer and pre-deep learning algorithms) in detecting acute MD episodes from recording segments taken in 64 (n=32, 50%, acute, n=32, 50%, stable) patients. RESULTS: SSL significantly outperformed fully supervised pipelines using either our novel E4mer or extreme gradient boosting (XGBoost): n=3353 (81.23%) against n=3110 (75.35%; E4mer) and n=2973 (72.02%; XGBoost) correctly classified recording segments from a total of 4128 segments. SSL performance was strongly associated with the specific surrogate task used for pretraining, as well as with unlabeled data availability. CONCLUSIONS: We showed that SSL, a paradigm where a model is pretrained on unlabeled data with no need for human annotations before deployment on the supervised target task of interest, helps overcome the annotation bottleneck; the choice of the pretraining surrogate task and the size of unlabeled data for pretraining are key determinants of SSL success. We introduced E4mer, which can be used for SSL, and shared the E4SelfLearning collection, along with its preprocessing pipeline, which can foster and expedite future research into SSL for personal sensing.

Sleep-wake variations of electrodermal activity in bipolar disorder.

BACKGROUND: Affective states influence the sympathetic nervous system, inducing variations in electrodermal activity (EDA), however, EDA association with bipolar disorder (BD) remains uncertain in real-world settings due to confounders like physical activity and temperature. We analysed EDA separately during sleep and wakefulness due to varying confounders and potential differences in mood state discrimination capacities. METHODS: We monitored EDA from 102 participants with BD including 35 manic, 29 depressive, 38 euthymic patients, and 38 healthy controls (HC), for 48 h. Fifteen EDA features were inferred by mixed-effect models for repeated measures considering sleep state, group and covariates. RESULTS: Thirteen EDA feature models were significantly influenced by sleep state, notably including phasic peaks (p < 0.001). During wakefulness, phasic peaks showed different values for mania (M [SD] = 6.49 [5.74, 7.23]), euthymia (5.89 [4.83, 6.94]), HC (3.04 [1.65, 4.42]), and depression (3.00 [2.07, 3.92]). Four phasic features during wakefulness better discriminated between HC and mania or euthymia, and between depression and euthymia or mania, compared to sleep. Mixed symptoms, average skin temperature, and anticholinergic medication affected the models, while sex and age did not. CONCLUSION: EDA measured from awake recordings better distinguished between BD states than sleep recordings, when controlled by confounders.

Risk factors for suicide reattempt: a systematic review and meta-analysis.

BACKGROUND: Suicide is one of the main external causes of death worldwide. People who have already attempted suicide are at high risk of new suicidal behavior. However, there is a lack of information on the risk factors that facilitate the appearance of reattempts. The aim of this study was to calculate the risk of suicide reattempt in the presence of suicidal history and psychosocial risk factors and to estimate the effect of each individual risk factor. METHODS: This systematic review and meta-analysis were conducted following the PRISMA-2020 guidelines. Studies on suicide reattempt that measured risk factors were searched from inception to 2022. The risk factors studied were those directly related to suicide history: history of suicide prior to the index attempt, and those that mediate the transition from suicidal ideation to attempt (alcohol or drug misuse, impulsivity, trauma, and non-suicidal self-injury). RESULTS: The initial search resulted in 11 905 articles. Of these, 34 articles were selected for this meta-analysis, jointly presenting 52 different effect sizes. The pooled effect size across the risk factors was significant (OR 2.16). Reattempt risk may be increased in presence of any of the following risk factors: previous history, active suicidal ideation, trauma, alcohol misuse, and drug misuse. However, impulsivity, and non-suicidal self-injury did not show a significant effect on reattempt. CONCLUSION: Most of the risk factors traditionally associated with suicide are also relevant when talking about suicide reattempts. Knowing the traits that define reattempters can help develop better preventive and intervention plans.

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.

Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number.

Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician's office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen's κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.

Cognitive reserve moderates the relationship between childhood maltreatment, objective and subjective cognition, and psychosocial functioning in individuals with first-episode psychosis.

OBJECTIVE: This study aimed to assess the relationship between childhood maltreatment (CM), objective and subjective cognition, and psychosocial functioning in adults with first-episode psychosis (FEP) by examining the moderating role of cognitive reserve (CR). A secondary objective was to explore whether unique CM subtypes (physical and/or emotional abuse, sexual abuse, physical and/or emotional neglect) were driving this relationship. METHOD: Sixty-six individuals with FEP (Mage = 27.3, SD = 7.2 years, 47% male) completed a comprehensive neuropsychological test battery, the Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA), the Functioning Assessment Short Test (FAST), the Childhood Trauma Questionnaire (CTQ), and the Cognitive Reserve Assessment Scale in Health (CRASH). Linear regression analyses were conducted to evaluate the interaction effect of CR between CM and cognitive and psychosocial variables, controlling for age, sex, and social desirability (CTQ-denial-minimization). RESULTS: In adults with FEP overall CM interacted with CR to predict COBRA-subjective cognitive complaints, but not neurocognitive or psychosocial functioning. Sexual abuse and physical neglect interacted with CR to predict verbal memory. Most of the CM subtypes interacted with CR to predict FAST-leisure time, whereas only emotional neglect interacted with CR to predict FAST-interpersonal relationships. Overall, greater CR was related to better functioning. CONCLUSIONS: The current results indicate that associations between specific CM subtypes, subjective and objective cognition, and psychosocial domains are moderated through CR with greater functioning. Early interventions focused on CR seeking to improve cognitive and psychosocial outcomes, with emphasis on improving subjective cognitive functions would be beneficial for individuals with FEP and CM. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Psychiatric profiles in suicidal attempters: Relationships with suicide behaviour features.

BACKGROUND: Suicide constitutes a major health concern worldwide, being a significant contributor of death, globally. The diagnosis of a mental disorder has been extensively linked to the varying forms of suicidal ideation and behaviour. The aim of our study was to identify the varying diagnostic profiles in a sample of suicide attempters. METHODS: A sample of 683 adults (71.3% females, 40.10±15.74 years) admitted at a hospital emergency department due to a suicide attempt was recruited. Latent class analysis was used to identify diagnostic profiles and logistic regression to study the relationship between comorbidity profile membership and sociodemographic and clinical variables. RESULTS: Two comorbidity profiles were identified (Class I: low comorbidity class, 71.3% of attempters; Class II: high comorbidity class, 28.7% of attempters). Class I members were featured by the diagnosis of depression and general anxiety disorder, and low comorbidity; by contrast, the high comorbidity profile was characterized by a higher probability of presenting two or more coexisting psychiatric disorders. Class II included more females, younger, with more depressive symptoms and with higher impulsivity levels. Moreover, Class II members showed more severe suicidal ideation, higher number of suicide behaviours and a greater number of previous suicide attempts (p<.01, for all the outcomes), compared to Class I members. CONCLUSIONS: Psychiatric profiles may be considered for treatment provision and personalized psychiatric treatment in suicidal attempters as well as tackle suicide risk.

Exploring Clinical Subgroups of Participants with Major Depressive Disorder that may Benefit from Adjunctive Minocycline Treatment.

Objective: : To explore illness-related factors in patients with major depressive disorder (MDD) recipients of adjunctive minocycline (200 mg/day) treatment. The analysis included participants experiencing MDD from a 12-week, double blind, placebo-controlled, randomized clinical trial (RCT). Methods: : This is a sub-analysis of a RCT of all 71 participants who took part in the trial. The impact of illness chronicity (illness duration and number of depressive episodes), systemic illness (endocrine, cardiovascular and obesity), adverse effects and minocycline were evaluated as change from baseline to endpoint (12-week) using ANCOVA. Results: : There was a consistent but statistically non-significant trend on all outcomes in favour of the use of adjunctive minocycline for participants without systemic illness, less illness chronicity, and fewer adverse effects. Conclusion: : Understanding the relationship between MDD and illness chronicity, comorbid systemic illness, and adverse effects, can potentially better characterise those individuals who are more likely to respond to adjunctive anti-inflammatory medications.

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.

Telepsychiatry: The future is already present.

This review paper analyzes the state of knowledge on Telepsychiatry (TP) after the crisis caused by COVID and the resulting need to use new modalities of care. Six essential aspects of TP are addressed: patient's and mental health staff satisfaction, diagnostic reliability, effectiveness of TP interventions, cost-effectiveness in terms of opportunity cost (or efficiency), legal aspects inherent to confidentiality and privacy in particular and the attitude of professionals toward TP. Satisfaction with TP is acceptable among both patients and professionals, the latter being the most reluctant. Diagnostic reliability has been demonstrated, but requires further studies to confirm this reliability in different diagnoses and healthcare settings. The efficacy of TP treatments is not inferior to face-to-face care, as has been proven in specific psychotherapies. Finally, it should be noted that the attitude of the psychiatrist is the most decisive element that limits or facilitates the implementation of TP.

The kynurenine pathway in major depressive disorder, bipolar disorder, and schizophrenia: a systematic review and meta-analysis of cerebrospinal fluid studies

Objectives: The kynurenine (KYN) pathway has been attracting attention as a relevant pathway in schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). We conducted a systematic review and meta-analysis of studies examining KYN pathway metabolites from cerebrospinal fluid (CSF) samples in SZ, BD, and MDD. Methods: The PubMed and Scopus databases were systematically searched to identify peer-reviewed case-control studies published until April 2022 that assessed KYN metabolites, namely, tryptophan (TRP), KYN, kynurenic acid (KA), quinolinic acid (QA), and 3-hydroxykynurenine (3-HK), in subjects with SZ, BD, or MDD compared with healthy controls (HC). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The random effects model method was selected for comparison of standardized mean differences (SMD) between two groups. Results: Twenty-three articles met the inclusion criteria (k = 8, k = 8, k = 11, for SZ, BD, and MDD, respectively). In SZ, KA levels were increased (SMD = 2.64, confidence interval [CI] = 1.16 to 4.13, p = 0.0005, I2 = 96%, k = 6, n=384). TRP (k = 5) and KYN (k = 4) did not differ significantly. In BD, TRP levels (k = 7) did not differ significantly. The level of KA was increased in MDD (k = 2), but the small number of studies precluded evaluation of statistical significance. Finally, in MDD, although some studies tended to show an increased level of KYN in those with remission vs. decreased levels in those with current depression, no significant difference was found in any KYN metabolite levels. Similarly, an increased level of QA was found, but the number of studies (k = 2) was small. Conclusion: KA, which has possibly neuroprotective effects, is increased in SZ. QA, which has neurotoxic effects, may be increased in MDD. There were no alterations in BD. Alterations in the KYN pathway may occur based on population characteristics and mood states. Future studies should explore the utility of these metabolites as biomarkers.

The Role of Ketamine in the Treatment of Bipolar Depression: A Scoping Review.

Bipolar depression remains a clinical challenge with a quarter of patients failing to respond to initial conventional treatments. Although ketamine has been extensively studied in unipolar depression, its role in bipolar disorder remains inconclusive. The aim of our scoping review was to comprehensively synthesize the current clinical literature around ketamine use in bipolar depression. A total of 10 clinical studies (5 randomized controlled trials and 5 open label studies) were selected. The preliminary evidence, albeit weak, suggests that ketamine is a promising treatment and calls for further interest from the research community. Overall, ketamine treatment appeared to be tolerable with minimal risk for manic/hypomanic switching and showed some effectiveness across parameters of depression and suicidality. Moreover, ketamine is a potential treatment agent in patients with treatment-resistant bipolar depression with promising data extracted from extant controlled trials and real-world effectiveness studies. Future studies are needed to identify ketamine's role in acute and maintenance treatment phases of bipolar depression. Moreover, future researchers should study the recurrence prevention and anti-suicidal effects of ketamine in the treatment of bipolar depression.

Effectiveness of vortioxetine in patients with major depressive disorder and early-stage dementia: The MEMORY study.

BACKGROUND: Depression and dementia are highly prevalent in older adults and often co-occur. This Phase IV study investigated the effectiveness and tolerability of vortioxetine in improving depressive symptoms, cognitive performance, daily and global functioning and health-related quality of life (HRQoL) in patients with major depressive disorder (MDD) and comorbid early-stage dementia. METHODS: Patients (n = 82) aged 55-85 years with a primary diagnosis of MDD (onset before age 55 years) and comorbid early-stage dementia (diagnosed ≥6 months before screening and after onset of MDD; Mini-Mental State Examination-2 total score, 20-24) received vortioxetine for 12 weeks (initiated at 5 mg/day and up-titrated to 10 mg/day at day 8, with flexible dosing thereafter [5-20 mg/day]). The primary endpoint was change from baseline in Montgomery-Åsberg Depression Rating Scale (MADRS) total score at week 12. RESULTS: Significant improvement in depressive symptom severity was seen from week 1 onwards (P < 0.0001). At week 12, the least-square mean (standard error) change in MADRS total score from baseline was -12.4 (0.78). Significant improvements in cognitive performance were observed (from week 1 for the Digit Symbol Substitution Test and week 4 for the Rey Auditory Verbal Learning Test). Patients also experienced significant improvements in daily and global functioning, and HRQoL. Vortioxetine was well tolerated. From week 4 onwards, more than 50 % of patients were receiving 20 mg/day. LIMITATIONS: Open-label study. CONCLUSIONS: Vortioxetine demonstrated effectiveness in clinically significantly improving depressive symptoms, cognitive performance, daily and global functioning, and HRQoL in patients with MDD and comorbid early-stage dementia treated for 12 weeks. TRIAL REGISTRATION: ClinicalTrials.gov/ct2/show/NCT04294654.

The kynurenine pathway in major depressive disorder, bipolar disorder, and schizophrenia: a systematic review and meta-analysis of cerebrospinal fluid studies.

INTRODUCTION: The kynurenine pathway has been attracting attention as a relevant pathway in schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). We conducted a systematic review and meta-analysis of the kynurenine pathway metabolites from cerebrospinal fluid (CSF) samples in SZ, BD, and MDD. METHODS: PubMed and Scopus databases were systematically searched to identify peer-reviewed case-control studies until April 2022 that assessed kynurenine metabolites, namely, tryptophan (TRP), kynurenine (KYN), kynurenic acid (KA), quinolinic acid (QA), and 3- hydroxykynurenine (3-HK) in SZ, BD, or MDD subjects compared with healthy controls (HC). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The random effects model method was selected when comparing the standardized mean differences (SMD) between two groups. RESULTS: There were 23 articles that met the inclusion criteria (k=8, k=8, k=11, for SZ, BD, and MDD, respectively). In SZ, KA levels were increased [SMD=2.64, confidence interval (CI) =1.16 to 4.13, p=0.0005, I2=96%, k=6, n=384 subjects]. TRP (k=5) and KYN (k=4) did not differ significantly. In BD, TRP levels (k=7) did not differ significantly. The level of KA was increased in MDD (k=2), but the small number of studies made not possible for statistical significance evaluation. Finally, in MDD, although some studies tended to have an increased level of KYN in those with remission versus decreased levels in those with current depression, no significant difference was found in any of the kynurenine metabolite levels. Similarly, there was an increased level of QA (k=2) but the number of studies (k= 2) was small. CONCLUSION: KA, which has possibly neuroprotective effects, is increased in SZ. QA, which has neurotoxic effects, may be increased in MDD. There were no alterations in BD. There may be alterations in this pathway based on population characteristics and mood states. Future studies should explore the utility of these metabolites as biomarkers.

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.

Risk of suicide attempt repetition after an index attempt: A systematic review and meta-analysis.

OBJECTIVES: To estimate the risk of suicide attempt repetition among individuals with an index attempt. It also aims to study the role of risk factors and prevention programme in repetition. METHODS: This systematic review and meta-analysis was conducted in keeping with the PRISMA 2020 guidelines. Studies on attempt repetition (both cohort studies and intervention studies) were searched from inception to 2022. RESULTS: A total of 110 studies comprising 248,829 attempters was reviewed. The overall repetition rate was 0.20 (0.17, 0.22). Repetition risk linearly increased over time. A higher risk of attempt repetition was associated with female sex and index attempts in which self-cutting methods were used. Moreover, a mental disorder diagnosis was associated with an increasing repetition risk (OR = 2.02, p < .01). The delivery of a preventive programme reduced the repetition risk, OR = 0.76, p < .05; however, this effect was significant for psychotherapy interventions, OR = 0.38, p < .01. CONCLUSION: One in five suicide attempters will engage in a new suicide attempt. An elevated repetition risk is associated with being female, more severe index methods and psychiatric disorder diagnosis. Preventive programmes, particularly psychotherapy, may contribute to reducing repetition risk and eventually save lives.