Early exposure to cannabis and bipolar disorder incidence: Findings from a 22-year birth cohort study in Brazil.

BACKGROUND AND OBJECTIVES: Bipolar disorder is a chronic condition affecting millions of people worldwide. Currently, there is some evidence to suggest that cannabis use during adolescence may be an environmental risk factor for its onset, however inconsistencies have been observed across the literature. Considering this, we aimed to assess whether early lifetime cannabis is associated with subsequent bipolar disorder in young adults between 18 and 22 years of age. METHODS: Using data from the 1993 Pelotas (Brazil) birth cohort (n = 5249), cannabis exposure was examined at age 18 by self-report, and bipolar disorder diagnosis was measured at age 22 using the Mini International Neuropsychiatric Interview (MINI). In order to control the analysis, we considered socioeconomic status index, sex, skin color, physical abuse by parents and lifetime cocaine use. RESULTS: A total of 3781 individuals were evaluated in 2015 aged 22 years, of whom 87 were diagnosed with the bipolar disorder onset after the age of 18. Lifetime cannabis use predicted bipolar disorder onset at 22 years old (OR 1.82, 95% CI [1.10, 2.93]), and the effect remained after adjusting for socioeconomic status, sex, skin color, and physical abuse by parents (OR 2.00, 95% CI [1.20, 3.25]). However, this association was attenuated to statistically non-significant after further adjustment for all available covariates, including lifetime cocaine use (OR 1.79, 95% CI [0.95, 3.19]). We also found similar results for early cocaine use, where the association with bipolar disorder onset did not maintain significance in the multivariate model (OR 1.35, 95% CI [0.62, 2.86]). Otherwise, when we considered cannabis or cocaine lifetime use as a unique feature, our findings showed that the adolescent exposure to cannabis or cocaine increased the odds by 1.95 times of developing bipolar disorder at 22 years age, even when controlling for all other study variables (OR 2.14, 95% CI [1.30, 3.47]). Finally, our models suggest that cocaine use may potentially exert a major influence on the effect of lifetime cannabis use on bipolar disorder onset, and that physical abuse by parents and sex may modify the effect of cannabis use for later bipolar disorder onset. CONCLUSION: Based on our findings, early cannabis exposure predicted bipolar disorder onset in young adults, but this association was confounded by cocaine use. Contrary to schizophrenia, cannabis as a sole exposure was not associated with bipolar disorder onset after adjusting for control variables.

Cannabidiol as an Adjunctive Treatment for Acute Bipolar Depression: A Pilot Study: Le cannabidiol comme traitement d'appoint de la dépression bipolaire aiguë : une étude pilote.

OBJECTIVE: The treatment of bipolar depression remains challenging due to the limited effective and safe therapeutic options available; thus, developing newer treatments that are effective and well tolerable is an urgent unmet need. The objective of the present trial was to test 150 to 300 mg/day of cannabidiol as an adjunctive treatment for bipolar depression. METHOD: A randomized, double-blind, placebo-controlled pilot study to assess the efficacy of adjunctive cannabidiol in bipolar depression was used. Efficacy parameters were changes in the Montgomery-Åsberg Depression Rating Scale (MADRS) from baseline to week 8. Secondary outcomes included response and remission rates, changes in anxiety and psychotic symptoms, and changes in functioning. Patients continued double-blind treatment until week 12 to monitor for adverse effects, laboratory analysis, and manic symptoms. Study registry: NCT03310593. RESULTS: A total of 35 participants were included. MADRS scores significantly decreased from baseline to the endpoint (placebo, -14.56; cannabidiol, -15.38), but there was no significant difference between the groups. Similarly, there were no other significant effects on the secondary outcomes. However, an exploratory analysis showed a significant effect of cannabidiol 300 mg/day in reducing MADRS scores from week 2 to week 8 (placebo, -6.64; cannabidiol, -13.72). There were no significant differences in the development of manic symptoms or any other adverse effects. CONCLUSION: Cannabidiol did not show significantly higher adverse effects than placebo. Despite the negative finding on the primary outcome, an exploratory analysis suggested that cannabidiol should be further studied in bipolar depression in higher doses of at least 300 mg/day and under research designs that could better control for high placebo response.

Inflammatory and oxidative stress markers in post-traumatic stress disorder: a systematic review and meta-analysis.

Post-traumatic stress disorder (PTSD) has been associated with persistent, low-degree inflammation, which could explain the increased prevalence of autoimmune conditions and accelerated aging among patients. The aim of the present study is to assess which inflammatory and oxidative stress markers are associated with PTSD. We carried out a meta-analytic and meta-regression analysis based on a systematic review of studies comparing inflammatory and oxidative stress markers between patients with PTSD and controls. We undertook meta-analyses whenever values of inflammatory and oxidative stress markers were available in two or more studies. Overall, 28,008 abstracts were identified, and 54 studies were included, with a total of 8394 participants. The Newcastle-Ottawa Quality Assessment Scale was used to evaluate the quality of the studies. Concentrations of C-reactive protein (SMD = 0.64; 95% CI: 0.21 to 1.06; p = 0.0031; k = 12), interleukin 6 (SMD = 0.94; 95% CI: 0.36 to 1.52; p = 0.0014; k = 32), and tumor necrosis factor-α (SMD = 0.89; 95% CI: 0.23 to 1.55; p = 0.0080; k = 24) were significantly increased in patients with PTSD in comparison with healthy controls. Interleukin 1ß levels almost reached the threshold for significance (SMD = 1.20; 95% CI: -0.04 to 2.44; p = 0.0569; k = 15). No oxidative stress marker was associated with PTSD. These findings may explain why PTSD is associated with accelerated aging and illnesses in which immune activation has a key role, such as cardiovascular diseases and diabetes. In addition, they pointed to the potential role of inflammatory markers as therapeutic targets.

Biomarkers of neuroprogression and late staging in bipolar disorder: A systematic review.

BACKGROUND: Bipolar disorder may undertake a progressive course in a subset of patients, and research efforts have been made to understand the biological basis underlying this process. This systematic review examined the literature available on biological markers associated with illness progression in bipolar disorder. METHODS: Peer-reviewed articles were assessed using Embase, PsycINFO and PubMed, as well as from external sources. After initial screening, a total of 871 citations from databases and other sources were identified. Participants with a diagnosis of bipolar disorder were included in our systematic review; however, studies with participants younger than 15 or older than 65 were excluded. All studies were assessed using the Newcastle-Ottawa Scale assessment tool, and data pertaining to the results were extracted into tabular form using Google Sheets and Google Documents. The systematic review was registered on PROSPERO international prospective register of systematic reviews (ID Number: CRD42020154305). RESULTS: A total of 35 studies were included in the systematic review. Increased ventricular size and reduction of grey matter volume were the most common brain changes associated with illness progression in bipolar disorder. Among the several biomarkers evaluated in this systematic review, findings also indicate a role of peripheral inflammatory markers in this process. DISCUSSION: The studies evaluating the biological basis of the illness progression in bipolar disorder are still scarce and heterogeneous. However, current evidence supports the notion of neuroprogression, the pathophysiological process related to progressive brain changes associated with clinical progression in patients with bipolar disorder. The increase in peripheral inflammatory biomarkers and the neuroanatomical changes in bipolar disorder suggest progressive systemic and structural brain alterations, respectively.

Data-driven cognitive phenotypes in subjects with bipolar disorder and their clinical markers of severity.

BACKGROUND: Subjects with bipolar disorder (BD) show heterogeneous cognitive profile and that not necessarily the disease will lead to unfavorable clinical outcomes. We aimed to identify clinical markers of severity among cognitive clusters in individuals with BD through data-driven methods. METHODS: We recruited 167 outpatients with BD and 100 unaffected volunteers from Brazil and Spain that underwent a neuropsychological assessment. Cognitive functions assessed were inhibitory control, processing speed, cognitive flexibility, verbal fluency, working memory, short- and long-term verbal memory. We performed hierarchical cluster analysis and discriminant function analysis to determine and confirm cognitive clusters, respectively. Then, we used classification and regression tree (CART) algorithm to determine clinical and sociodemographic variables of the previously defined cognitive clusters. RESULTS: We identified three neuropsychological subgroups in individuals with BD: intact (35.3%), selectively impaired (34.7%), and severely impaired individuals (29.9%). The most important predictors of cognitive subgroups were years of education, the number of hospitalizations, and age, respectively. The model with CART algorithm showed sensitivity 45.8%, specificity 78.4%, balanced accuracy 62.1%, and the area under the ROC curve was 0.61. Of 10 attributes included in the model, only three variables were able to separate cognitive clusters in BD individuals: years of education, number of hospitalizations, and age. CONCLUSION: These results corroborate with recent findings of neuropsychological heterogeneity in BD, and suggest an overlapping between premorbid and morbid aspects that influence distinct cognitive courses of the disease.

Prediction of suicide attempts in a prospective cohort study with a nationally representative sample of the US population.

BACKGROUND: There is still little knowledge of objective suicide risk stratification. METHODS: This study aims to develop models using machine-learning approaches to predict suicide attempt (1) among survey participants in a nationally representative sample and (2) among participants with lifetime major depressive episodes. We used a cohort called the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) that was conducted in two waves and included a nationally representative sample of the adult population in the United States. Wave 1 involved 43 093 respondents and wave 2 involved 34 653 completed face-to-face reinterviews with wave 1 participants. Predictor variables included clinical, stressful life events, and sociodemographic variables from wave 1; outcome included suicide attempt between wave 1 and wave 2. RESULTS: The model built with elastic net regularization distinguished individuals who had attempted suicide from those who had not with an area under the ROC curve (AUC) of 0.89, balanced accuracy 81.86%, specificity 89.22%, and sensitivity 74.51% for the general population. For participants with lifetime major depressive episodes, AUC was 0.89, balanced accuracy 81.64%, specificity 85.86%, and sensitivity 77.42%. The most important predictor variables were a diagnosis of borderline personality disorder, post-traumatic stress disorder, and being of Asian descent for the model in all participants; and previous suicide attempt, borderline personality disorder, and overnight stay in hospital because of depressive symptoms for the model in participants with lifetime major depressive episodes. Random forest and artificial neural networks had similar performance. CONCLUSIONS: Risk for suicide attempt can be estimated with high accuracy.

Network properties of intracortical myelin associated with psychosocial functioning in bipolar I disorder.

OBJECTIVE: Psychosocial functioning in bipolar disorder (BD) persists even during euthymia and has repeatedly been associated with illness progression and cognitive function. Its neurobiological correlates remain largely unexplored. Using a structural covariance approach, we explored whole cortex intracortical myelin (ICM) and psychosocial functioning in 39 BD type I and 58 matched controls. METHOD: T1 -weighted images (3T) optimized for ICM measurement were analyzed using a surface-based approach. The ICM signal was sampled at cortical mid-depth using the MarsAtlas parcellation, and psychosocial functioning was measured via the Functioning Assessment Short Test (FAST). Following construction of structural covariance matrices, graph theoretical measures were calculated for each subject. Within BD and HC groups separately, correlations between network measures and FAST were explored. After accounting for multiple comparisons, significant correlations were tested formally using rank-based regressions accounting for sex differences. RESULTS: In BD only, psychosocial functioning was associated with global efficiency (ß = -0.312, pcorr  = 0.03), local efficiency in the right rostral dorsolateral prefrontal cortex (ß = 0.545, pcorr  = 0.001) and clustering coefficient in this region (ß = 0.497, pcorr  = 0.0002) as well as in the right ventromedial prefrontal cortex (ß = 0.428, pcorr  = 0.002). All results excepting global efficiency remained significant after accounting for severity of depressive symptoms. In contrast, no significant associations between functioning and network measures were observed in the HC group. CONCLUSION: These results uncovered a novel brain-behaviour relationship between intracortical myelin signal changes and psychosocial functioning in BD.

Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force.

BACKGROUND: The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established. OBJECTIVES: To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators. METHODS: We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668). RESULTS: The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators. CONCLUSION: We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.

Functional and cognitive impairment in the first episode of depression: A systematic review.

OBJECTIVES: To describe the cognitive and functional impairment in individuals with the first episode of major depressive disorder (MDD) as compared to controls and individuals with recurrent MDD. Also to describe the functional and cognitive trajectory after the first episode of MDD. METHODS: A total of 52 studies were included in our systematic review. 32 studies compared the cognitive performance between first episode of depression (FED) and controls, 11 studies compared the cognitive performance between recurrent depression (RD) and FED, 10 compared global functioning between RD and FED, four studies assessed cognition in FED over time, and two studies assessed global functioning in FED over time. RESULTS: The majority of studies (n = 22/32, 68.8%) found that FED subjects performed significantly worse than controls on cognitive tests, with processing speed (n = 12) and executive/working memory (n = 11) being the most commonly impaired domains. Seven out of 11 studies (63.6%) found that RD performed significantly worse than FED, with verbal learning and memory being the most commonly impaired domain (n = 4). Most studies (n = 7/10, 70%) did not find a significant difference in global functioning between RD and FED. In three of four longitudinal studies assessing cognition, subgroup analyses were used instead of directly assessing cognition in FED over time while the remaining study found significant cognitive declines over time in FED when compared to controls. The two longitudinal studies assessing functional trajectory found that functioning significantly improved over time, possibly due to the improvement of depressive symptoms. CONCLUSION: There is strong evidence that cognitive impairment is present during the first episode of depression, and individuals with multiple episodes display greater cognitive impairment than individuals with a single episode. Future studies aimed at identifying predictors of cognitive and functional impairment after the first episode of depression are needed to describe the functional and cognitive trajectory of individuals with the first episode of MDD over time.

Clinical predictors of depressive symptom remission and response after racemic ketamine and esketamine infusion in treatment-resistant depression.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide and most people do not achieve symptom remission. Treatment-resistant depression (TRD) is characterized by the failure of at least one adequate trial of a major class of antidepressant, with adequate time and dosage. We aimed to identify clinical predictors of depressive symptom remission and response 24 h and 7 days after racemic ketamine and esketamine infusions. METHODS: A randomized, double-blind, active-controlled, non-inferiority trial using ketamine and esketamine in TRD. Individuals diagnosed with MDD according to Diagnostic and Statistical Manual of Mental Disorders version IV and fulfilling TRD criteria were recruited from March 2017 to June 2018. Participants received a single subanesthetic dose of ketamine (0.5 mg/kg) or esketamine (0.25 mg/kg) for 40 min. Depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) and symptom remission was defined as a MADRS score ≤7 and response defined as ≥50% reduction in depressive symptom severity, 24 h and 7 days after the infusion. Clinical variables were selected based on previous clinical trials. Stepwise backward logistic regression was used, considering a confidence level of 95%. RESULTS: 61 subjects were included: 39 (63.9%) were females with a mean age of 47.2 ± 14.9. Higher number of therapeutic failures (Odds Ratio (OR) = 0.677; 95% confidence interval (CI): 0.47-0.97) and higher severity of illness (OR = 0.912; 95% CI: 0.83-0.99) were associated with fewer remissions of depressive symptoms 7 days after intervention, and with fewer response in 24 h (OR = 0.583; 95% CI: 0,40; 0,84 and OR = 0.909; 95% CI: 0,83; 0,99, respectively). CONCLUSION: Number of treatment failures and severity of illness were predictors of fewer remissions and responses of depressive symptoms in this TRD population. Study of predictors of remission may contribute to better selection patients that may benefit from receiving ketamine.

Investigating biological rhythms disruptions across the menstrual cycle in women with comorbid bipolar disorder and premenstrual dysphoric disorder.

We investigated whether women diagnosed with comorbid bipolar disorder (BD) and premenstrual dysphoric disorder (PMDD) experience higher disruptions in biological rhythms in two independent study samples. The first study has a population-based sample of 727 women, including 104 women with PMDD only, 43 women with BD only, 24 women with comorbid PMDD and BD, and 556 women without BD or PMDD (controls). Biological rhythm disruptions were cross-sectionally evaluated using the Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN). The second study enrolled 77 outpatient women who completed prospective assessments at two timepoints: during the mid-follicular and the late-luteal phases of their menstrual cycles, using the BRIAN, and included 19 women with PMDD, 16 with BD, 17 with comorbid PMDD and BD, and 25 controls. In the population-based sample, all the diagnostic groups (BD, PMDD, BDPMDD) presented greater biological rhythm disruption than controls. In addition, women with BD presented greater overall biological rhythms disruption, and greater disruption in sleep, activity, and eating patterns, than women with PMDD. In the outpatient sample study, women with BDPMDD showed greater disruption in the social domain than women with PMDD. In the outpatient sample, women with BDPMDD reported significantly higher disruptions in biological rhythms across both the follicular and the luteal phases of the menstrual cycle. The comorbidity between BD and PMDD may affect biological rhythms beyond the luteal phase of the menstrual cycle. These results support previous literature on the increased illness burden of women diagnosed with comorbid BD and PMDD.

Consensus on nomenclature for clinical staging models in bipolar disorder: A narrative review from the International Society for Bipolar Disorders (ISBD) Staging Task Force.

OBJECTIVES: Clinical staging is widely used in medicine to map disease progression, inform prognosis, and guide treatment decisions; in psychiatry, however, staging remains a hypothetical construct. To facilitate future research in bipolar disorders (BD), a well-defined nomenclature is needed, especially since diagnosis is often imprecise with blurred boundaries, and a full understanding of pathophysiology is lacking. METHODS: Under the auspices of the International Society of Bipolar Disorders, a Task Force of international experts was convened to review, discuss, and integrate findings from the scientific literature relevant to the development of a consensus staging model and standardize a terminology that could be used to advance future research including staging of BD and related disorders. RESULTS: Consensus opinion and areas of uncertainty or difference were identified in regard to terms referring to staging as it may apply to BD, to at-risk status and subthreshold stages, and to various clinical stages of BD as it is currently diagnosed. CONCLUSION: The use of a standardized nomenclature about the clinical stages of BD will facilitate communication about research on clinical and pathological components of this heterogeneous group of disorders. The concepts presented are based on current evidence, but the template provided allows for further refinements as etiological advances come to light.

Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) recommendations for the management of patients with bipolar disorder with mixed presentations.

OBJECTIVES: The 2018 Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) guidelines provided clinicians with pragmatic treatment recommendations for bipolar disorder (BD). While these guidelines included commentary on how mixed features may direct treatment selection, specific recommendations were not provided-a critical gap which the current update aims to address. METHOD: Overview of research regarding mixed presentations in BD, with treatment recommendations developed using a modified CANMAT/ISBD rating methodology. Limitations are discussed, including the dearth of high-quality data and reliance on expert opinion. RESULTS: No agents met threshold for first-line treatment of DSM-5 manic or depressive episodes with mixed features. For mania + mixed features second-line treatment options include asenapine, cariprazine, divalproex, and aripiprazole. In depression + mixed features, cariprazine and lurasidone are recommended as second-line options. For DSM-IV defined mixed episodes, with a longer history of research, asenapine and aripiprazole are first-line, and olanzapine (monotherapy or combination), carbamazepine, and divalproex are second-line. Research on maintenance treatments following a DSM-5 mixed presentation is extremely limited, with third-line recommendations based on expert opinion. For maintenance treatment following a DSM-IV mixed episode, quetiapine (monotherapy or combination) is first-line, and lithium and olanzapine identified as second-line options. CONCLUSION: The CANMAT and ISBD groups hope these guidelines provide valuable support for clinicians providing care to patients experiencing mixed presentations, as well as further influence investment in research to improve diagnosis and treatment of this common and complex clinical state.

The cumulative effect of multiple dimensions of lifestyle on risky drinking during the Covid-19 pandemic.

Lifestyle impacts morbidity and mortality worldwide. Herein, we evaluated the association of a multidimensional lifestyle measure and its domains (diet/nutrition, substance use, physical activity, social, stress management, sleep, environmental exposure) with risky drinking. Also, we analyzed the cumulative effect of unhealthy domains in the likelihood of presenting risky drinking. To reach these objectives, data from a web survey conducted in Brazil and Spain was analyzed. The main outcome was risky drinking assessed by the AUDIT-C. Lifestyle was measured using the Short Multidimensional Inventory Lifestyle Evaluation (SMILE). Fixed logistic models were used to evaluate associations between lifestyle and risky drinking. Between April and May 2020, 22,785 individuals answered the survey. The prevalence of risky drinking was 45.6% in Brazil and 30.8% in Spain. The SMILE score was lower (unhealthier lifestyle) among at-risk drinkers. Worse scores on Diet, Substance use, Stress management and Environment were associated with an increased likelihood of risky drinking. The higher the number of unhealthy domains, the higher the likelihood of presenting risky drinking: adjusted odds ratio (aOR) for risky drinking was 1.15 (IC95% 0.98-1.35) and 23.42 (IC95% 3.08-178.02) for those presenting worse lifestyle in 1 and 5 domains, respectively. Finally, interactions suggest that improvement in lifestyle domains would have a larger effect in Spain than in Brazil. Our results suggest that future interventions aiming at reducing Risky drinking may benefit from strategies targeting multiple domains of lifestyle.

Bipolar disorder and frontotemporal dementia: A systematic review.

OBJECTIVES: To detail the biological, clinical and neurocognitive characteristics differentiating bipolar disorder (BD) from frontotemporal dementia (FTD) and to investigate whether BD is a risk factor for FTD. METHODS: A total of 16 studies were included in this systematic review. Five studies described biological and/or neurocognitive characteristics between patients with BD and FTD, and 11 studies investigated whether BD was a risk factor for FTD. RESULTS: Individuals with FTD presented higher levels of serum neurofilament light chain, greater grey matter reduction in frontal, parietal and temporal lobes, and increased slow wave oscillations in channels F3, F4, T3, T5, T4 and T6 within an electroencephalogram (EEG), relative to individuals with BD. Patients with FTD presented greater deficits in executive function and theory of mind compared to patients with BD in a euthymic state, and more deficits in verbal fluency compared to patients with BD in a current mood episode. Patients with BD in a current mood episode showed greater impairment in attention, working memory, verbal memory and executive function relative to individuals with FTD. In addition, retrospective studies showed that 10.2%-11.6% of patients with behavioural variant FTD (bvFTD) had a preceding history of BD. CONCLUSION: Biological and neurocognitive characteristics help to distinguish between BD and FTD, and it may help to reach a more precise diagnosis. In addition, individuals with BD are at higher risk of developing FTD. More studies are needed to identify the predictors of the conversion between BD to FTD.

History of suicide attempts in patients with bipolar disorder type I: socio-demographic and clinical factors, quality of life and functioning.

INTRODUCTION: This study aims to evaluate sociodemographic and clinical factors, quality of life (QoL) and functioning associated with history of suicide attempts (SA) in a sample of bipolar disorder (BD) type I patients. METHODS: A total of 417 BD type I patients, with and without history of SA were recruited from two Brazilian specialized Mood Disorder Centers. They were assessed with a sociodemographic and clinical questionnaire, the Young Mania Rating Scale, the Hamilton Depression Rating Scale, the Structured Clinical Interviews for DSM-IV Axis I Disorders, the World Health Organization Quality of Life-BREF, and the Sheehan Disability Scale. RESULTS: One hundred and seventy-nine (42.9%) patients had a history of SA. There were no statistically significant sociodemographic differences between BD patients with and without a history of SA. Logistic regression found that lifetime hospitalization, comorbid anxiety disorders, depressive polarity in the first episode, current intensity of depressive symptoms, history of rapid cycling, family history of suicide and age at onset were significantly associated with SA in BD. Multiple linear regression showed that SA had no effect on QoL and functioning, which were affected mainly by comorbid anxiety disorders and current intensity of depressive symptoms, even in patients considered euthymic. CONCLUSION: Suicidal behavior in patients with BD is a complex phenomenon and reflects a more severe course of illness. Patients with history of SA may have worse QoL and functional impairment not because of its direct effect, but because of the greater association with clinical factors related to poor prognosis.

Current understandings of the trajectory and emerging correlates of cognitive impairment in bipolar disorder: An overview of evidence.

OBJECTIVES: Cognitive dysfunction affects a significant proportion of people with bipolar disorder (BD), but the cause, trajectory and correlates of such dysfunction remains unclear. Increased understanding of these factors is required to progress treatment development for this symptom dimension. METHODS: This paper provides a critical overview of the literature concerning the trajectories and emerging correlates of cognitive functioning in BD. It is a narrative review in which we provide a qualitative synthesis of current evidence concerning clinical, molecular, neural and lifestyle correlates of cognitive impairment in BD across the lifespan (in premorbid, prodromal, early onset, post-onset, elderly cohorts). RESULTS: There is emerging evidence of empirical links between cognitive impairment and an increased inflammatory state, brain structural abnormalities and reduced neuroprotection in BD. However, evidence regarding the progressive nature of cognitive impairment is mixed, since consensus between different cross-sectional data is lacking and does not align to the outcomes of the limited longitudinal studies available. Increased recognition of cognitive heterogeneity in BD may help to explain some inconsistencies in the extant literature. CONCLUSIONS: Large, longitudinally focussed studies of cognition and its covariation alongside biological and lifestyle factors are required to better define cognitive trajectories in BD, and eventually pave the way for the application of a precision medicine approach for individual patients in clinical practice.

Differential biomarker signatures in unipolar and bipolar depression: A machine learning approach.

OBJECTIVE: This study used machine learning techniques combined with peripheral biomarker measurements to build signatures to help differentiating (1) patients with bipolar depression from patients with unipolar depression, and (2) patients with bipolar depression or unipolar depression from healthy controls. METHODS: We assessed serum levels of interleukin-2, interleukin-4, interleukin-6, interleukin-10, tumor necrosis factor-α, interferon-γ, interleukin-17A, brain-derived neurotrophic factor, lipid peroxidation and oxidative protein damage in 54 outpatients with bipolar depression, 54 outpatients with unipolar depression and 54 healthy controls, matched by sex and age. Depressive symptoms were assessed using the Hamilton Depression Rating Scale. Variable selection was performed with recursive feature elimination with a linear support vector machine kernel, and the leave-one-out cross-validation method was used to test and validate our model. RESULTS: Bipolar vs unipolar depression classification achieved an area under the receiver operating characteristics (ROC) curve (AUC) of 0.69, with 0.62 sensitivity and 0.66 specificity using three selected biomarkers (interleukin-4, thiobarbituric acid reactive substances and interleukin-10). For the comparison of bipolar depression vs healthy controls, the model retained five variables (interleukin-6, interleukin-4, thiobarbituric acid reactive substances, carbonyl and interleukin-17A), with an AUC of 0.70, 0.62 sensitivity and 0.7 specificity. Finally, unipolar depression vs healthy controls comparison retained seven variables (interleukin-6, Carbonyl, brain-derived neurotrophic factor, interleukin-10, interleukin-17A, interleukin-4 and tumor necrosis factor-α), with an AUC of 0.74, a sensitivity of 0.68 and 0.70 specificity. CONCLUSION: Our findings show the potential of machine learning models to aid in clinical practice, leading to more objective assessment. Future studies will examine the possibility of combining peripheral blood biomarker data with other biological data to develop more accurate signatures.

Depression, Anxiety, and Lifestyle Among Essential Workers: A Web Survey From Brazil and Spain During the COVID-19 Pandemic.

BACKGROUND: Essential workers have been shown to present a higher prevalence of positive screenings for anxiety and depression during the COVID-19 pandemic. Individuals from countries with socioeconomic inequalities may be at increased risk for mental health disorders. OBJECTIVE: We aimed to assess the prevalence and predictors of depression, anxiety, and their comorbidity among essential workers in Brazil and Spain during the COVID-19 pandemic. METHODS: A web survey was conducted between April and May 2020 in both countries. The main outcome was a positive screening for depression only, anxiety only, or both. Lifestyle was measured using a lifestyle multidimensional scale adapted for the COVID-19 pandemic (Short Multidimensional Inventory Lifestyle Evaluation-Confinement). A multinomial logistic regression model was performed to evaluate the factors associated with depression, anxiety, and the presence of both conditions. RESULTS: From the 22,786 individuals included in the web survey, 3745 self-reported to be essential workers. Overall, 8.3% (n=311), 11.6% (n=434), and 27.4% (n=1027) presented positive screenings for depression, anxiety, and both, respectively. After adjusting for confounding factors, the multinomial model showed that an unhealthy lifestyle increased the likelihood of depression (adjusted odds ratio [AOR] 4.00, 95% CI 2.72-5.87), anxiety (AOR 2.39, 95% CI 1.80-3.20), and both anxiety and depression (AOR 8.30, 95% CI 5.90-11.7). Living in Brazil was associated with increased odds of depression (AOR 2.89, 95% CI 2.07-4.06), anxiety (AOR 2.81, 95%CI 2.11-3.74), and both conditions (AOR 5.99, 95% CI 4.53-7.91). CONCLUSIONS: Interventions addressing lifestyle may be useful in dealing with symptoms of common mental disorders during the strain imposed among essential workers by the COVID-19 pandemic. Essential workers who live in middle-income countries with higher rates of inequality may face additional challenges. Ensuring equitable treatment and support may be an important challenge ahead, considering the possible syndemic effect of the social determinants of health.

Lifetime cocaine use is a potential predictor for conversion from major depressive disorder to bipolar disorder: A prospective study.

AIM: We aimed to identify whether lifetime cocaine use is a risk factor for conversion from major depressive disorder (MDD) to bipolar disorder (BD) in an outpatient sample of adults. METHODS: This prospective cohort study included 585 subjects aged 18 to 60 years who had been diagnosed with MDD as assessed by the Mini International Neuropsychiatric Interview (MINI-Plus) at baseline (2012-2015). Subjects were reassessed a mean of 3 years later (2017-2018) for potential conversion to BD as assessed by the MINI-Plus. Lifetime cocaine use was assessed using the Alcohol, Smoking, and Substance Involvement Screening Test. RESULTS: In the second wave, we had 117 (20%) losses, and 468 patients were reassessed. The rate of conversion from MDD to BD in 3 years was 12.4% (n = 58). A logistic regression analysis showed that the risk for conversion from MDD to BD was 3.41-fold higher (95% confidence interval, 1.11-10.43) in subjects who reported lifetime cocaine use at baseline as compared to individuals who did not report lifetime cocaine use at baseline, after adjusting for demographic and clinical confounders. CONCLUSION: These findings showed that lifetime cocaine use is a potential predictor of conversion to BD in an MDD cohort. Further studies are needed to assess the possible underlying mechanisms linking exposure to cocaine with BD conversion.