The relationship between sex, personality traits, and the hypothalamic-pituitary-adrenocortical axis.

The aim of our study was to examine whether there are sex-based differences in the relationship between personality traits and hypothalamic-pituitary-adrenal (HPA) axis measures. A total of 106 healthy volunteers (56.6% women; age: 48.0 ± 15.8 years) were studied. The revised temperament and character inventory (TCI-R) and the Childhood Trauma Questionnaire (CTQ) were administered. HPA axis function was assessed using three dynamic measures: the cortisol awakening response (CAR), the diurnal cortisol slope, and the cortisol suppression ratio with 0.25 mg of dexamethasone (DSTR). Female sex was associated with an increased CAR and a more flattened diurnal cortisol slope, although a negative significant interaction between harm avoidance and female sex was found. Regarding the DSTR, perseverance was associated with increased cortisol suppression after dexamethasone; sex did not affect this association. Our study suggests that the relationship between specific personality traits (harm avoidance) and HPA axis measures (CAR, diurnal slope) differs according to sex.

Similar clinical improvement of depression using 0.5-ms and 1-ms pulse widths in bilateral electroconvulsive therapy.

There is a lack of research regarding 0.5-ms pulse width (PW) in bilateral electroconvulsive therapy (ECT). The aim of this study was to compare the efficacy and number of treatment sessions between groups receiving 0.5-ms and 1-ms PW ECT. Ninety-four patients with unipolar major depression treated with acute bilateral ECT were analysed retrospectively, grouped as consecutive patients treated with 0.5-ms PW ECT (n = 47), and age- and sex-matched patients treated with 1-ms PW ECT. Clinical and ECT data were extracted from clinical records. Symptom evaluations and global cognitive screening at baseline and post-ECT were administered by trained psychiatrists. The Hamilton Rating Scale for Depression (HDRS-21) was rated weekly. Efficacy and number of treatment sessions were compared between groups. PW was explored as a predictor of mean decrease in HDRS and number of treatment sessions by regression models. Group characteristics did not differ at baseline. The mean decrease in HDRS in the 0.5- and 1-ms PW [25.85 (7.79) vs. 24.33 (6.99), respectively], response (95.7% vs. 97.9%), remission (87.2% vs. 80.9%) and mean number of treatment sessions [11.28 (3.85) vs. 11.34 (3.36)] were not significantly different. Episode duration and severity, and previous ECT predicted HDRS decrease. Severity at baseline and the 6th session, the dosing method and the last ECT treatment dose predicted the number of treatment sessions needed. PW was not significant in the regressions models. The results suggest that both PWs perform similarly in bilateral ECT for depression, resulting in equivalent antidepressant efficacy and number of treatment sessions needed.

Sleep disturbances in obsessive-compulsive disorder: influence of depression symptoms and trait anxiety.

BACKGROUND: Sleep disturbances have been reported in obsessive-compulsive disorder (OCD) patients, with heterogeneous results. The aim of our study was to assess sleep function in OCD and to investigate the relationship between sleep and the severity of obsessive-compulsive (OC) symptoms, depressive symptoms and trait anxiety. METHODS: Sleep quality was measured in 61 OCD patients and 100 healthy controls (HCs) using the Pittsburgh Sleep Quality Index (PSQI). Multiple linear regression was conducted to explore the association between sleep and psychopathological measures; a mediation analysis was also performed. RESULTS: OCD patients showed poor sleep quality and more sleep disturbances compared to HCs. The severity of depression, trait anxiety and OC symptomatology were correlated with poor sleep quality. Multiple linear regression analyses controlling for potential confounders revealed that the severity of depression and trait anxiety were independently related to poor sleep quality in OCD. A mediation analysis showed that both the severity of trait anxiety and depression mediate the relationship between the severity of OC symptoms and poor sleep quality among patients with OCD. CONCLUSIONS: Our findings support the existence of sleep disturbances in OCD. Trait anxiety and depression play a key role in sleep quality among OCD patients.

International Consortium on the Genetics of Electroconvulsive Therapy and Severe Depressive Disorders (Gen-ECT-ic).

Recent genome-wide association studies have demonstrated that the genetic burden associated with depression correlates with depression severity. Therefore, conducting genetic studies of patients at the most severe end of the depressive disorder spectrum, those with treatment-resistant depression and who are prescribed electroconvulsive therapy (ECT), could lead to a better understanding of the genetic underpinnings of depression. Despite ECT being one of the most effective forms of treatment for severe depressive disorders, it is usually placed at the end of treatment algorithms of current guidelines. This is perhaps because ECT has controlled risk and logistical demands including use of general anaesthesia and muscle relaxants and side-effects such as short-term memory impairment. Better understanding of the genetics and biology of ECT response and of cognitive side-effects could lead to more personalized treatment decisions. To enhance the understanding of the genomics of severe depression and ECT response, researchers and ECT providers from around the world and from various depression or ECT networks, but not limited to, such as the Psychiatric Genomics Consortium, the Clinical Alliance and Research in ECT, and the National Network of Depression Centers have formed the Genetics of ECT International Consortium (Gen-ECT-ic). Gen-ECT-ic will organize the largest clinical and genetic collection to date to study the genomics of severe depressive disorders and response to ECT, aiming for 30,000 patients worldwide using a GWAS approach. At this stage it will be the largest genomic study on treatment response in depression. Retrospective data abstraction and prospective data collection will be facilitated by a uniform data collection approach that is flexible and will incorporate data from many clinical practices. Gen-ECT-ic invites all ECT providers and researchers to join its efforts.

Electroconvulsive Therapy Practice in Spain: A National Survey.

OBJECTIVES: The use of electroconvulsive therapy (ECT) in Spain has not been systematically evaluated since 2000 to 2001. The aim of this study is to assess the current use of ECT in Spain. METHODS: A cross-sectional survey was conducted covering every psychiatric unit in Spain as of December 31, 2012. RESULTS: About 93.2% of the centers answered the questionnaire. About 54.9% of the psychiatric units applied ECT at a rate of 0.66 patients per 10,000 inhabitants. Wide variations existed among the different autonomous communities and provinces. Written informed consent was obtained in all the facilities. About 38.2% of ECT-treated patients were 65 years or older. About 55.7% were women. Depressive episodes were the main indication for ECT (80.2%). All the facilities applied modified ECT. No sine wave current devices are currently used in Spain. Bifrontotemporal ECT was elective in 85% of the hospitals, bifrontal in 13.3%, and unilateral in 1.8%. Stimulus titration methods were elective in 8.6% of the centers. The decision to end ECT relied on the psychiatrist's clinical impression in 89.4% of the centers and on rating scales in 10.6%. The ECT training was mandatory in 56.5% of the centers. CONCLUSIONS: The ECT practice has significantly improved in Spain in recent years. Overall, Spanish facilities seem to comply with established clinical guidelines; however, specific concerns were identified, meaning there is still further scope for improvement.

Lymphocyte-derived and lipoprotein-derived inflammatory ratios as biomarkers in bipolar disorder type I: Characteristics, predictive values, and influence of current psychopharmacological treatments.

PURPOSE OF THIS RESEARCH: The purpose of this research was to investigate peripheral inflammation by analyzing lymphocyte and lipoprotein-derived inflammatory ratios in patients with bipolar disorder type I (BD-I) and healthy controls (HCs), considering mood stabilizer drug treatments, sex and clinical trajectories. METHODS: This was a cross-sectional case-control study of BD-I patients (n=252) and healthy controls (n=62). We investigated peripheral inflammation biomarkers through blood count values (CBCs), lipoproteins and a complex panel of inflammatory ratios, including the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-to-HDL ratio (NHR), monocyte-to-HDL ratio (MHR), platelet-to-HDL ratio (PHR) and lymphocyte-to-HDL ratio (LHR). Furthermore, we examined the effects of sex, drug treatment and clinical outcome on the inflammatory profile. RESULTS: We found that the monocyte-to-lymphocyte ratio (MLR) and lipoprotein-derived inflammatory ratio (NHR, MHR, PHR, and LHR) were significantly greater in BD-I patients than in control individuals. The monocyte-to-HDL ratio (MHR) showed acceptable accuracy as a disease predictor. Logistic regression analysis adjusted for sex, age and BMI indicated that the risk of having a BD-I diagnosis was greater for participants with MHR levels in quartiles 3 (OR= 5.2, p=0.001) and 4 (OR=13, p<0.001). There was a strong association between lithium treatment and increased inflammation represented by elevated lymphocyte-derived inflammatory ratios (NLR, MLR, PLR, SII, and SIRI) in lithium-treated BD-I patients compared to those in lithium-free or lithium treatment-naïve BD-I patients. The main limitations are the cross-sectional nature of the study and limited sample size of HCs. MAJOR CONCLUSIONS: Several CBCs, lipoproteins, and a complex panel of inflammatory ratios, including lymphocyte-derived inflammatory ratios (NLR, MLR, PLR, SII, and SIRI) and lipoprotein-derived inflammatory ratios (NHR, MHR, PHR, and LHR), are altered in individuals diagnosed with BD-I. The monocyte-to-HDL ratio (MHR) emerged as a disease predictor in our BD-I sample. A remarkable finding is the association of lithium and valproate treatment with the inflammatory state. Considering the study limitations, our results underscore the importance of pharmacological treatments when researching inflammation markers in mood disorders. Lymphocyte-derived and lipoprotein-derived inflammatory ratios are easy-to-implement and relevant biomarkers in BD-I patients.

Altered activation of the dorsal anterior cingulate cortex during oddball performance in individuals at risk for Alzheimer's disease.

INTRODUCTION: The neural mechanisms underlying neurodegenerative disorders in the elderly remain elusive, despite extensive neuroimaging research in recent decades. Amnestic type mild cognitive impairment (aMCI) and late-life major depressive disorder (MDD) are two such conditions characterized by intersecting cognitive and affective symptomatology, and they are at a higher risk for Alzheimer's disease. MATERIALS AND METHODS: This study analyzed the neural underpinnings of cognitive and depressive symptoms in a cohort comprising 12 aMCI subjects, 24 late-life MDD patients, and 26 healthy controls (HCs). Participants underwent a detailed neuropsychological assessment and completed a visual attentional oddball task during functional magnetic resonance imaging (fMRI), with evaluations at baseline and at 2-year follow-up. RESULTS: Initial findings showed that aMCI subjects had reduced dACC activation during oddball (target) stimulus detection, a pattern that persisted in longitudinal analyses and correlated with cognitive functioning measures. For HCs, subsequent dACC activation was linked to depression scores. Furthermore, in the affective-cognitive altered groups, later dACC activation correlated with oddball and memory performance. CONCLUSIONS: These findings enhance our comprehension of the neurobiological basis of cognitive and depressive disturbances in aging, indicating that dACC activation in response to a visual attentional oddball task could serve as a neural marker for assessing cognitive impairment and depression in conditions predisposing to Alzheimer's disease.

Effective connectivity of the locus coeruleus in patients with late-life Major Depressive Disorder or mild cognitive impairment.

INTRODUCTION: We compared effective connectivity from the locus coeruleus (LC) during the resting-state in patients with late-life Major Depressive Disorder (MDD), individuals with amnestic Mild Cognitive Impairment (aMCI), and Healthy Controls (HCs). PARTICIPANTS: 23 patients with late-life MDD, 22 patients with aMCI, and 28 HCs. MATERIAL AND METHODS: Participants were assessed in two time-points, 2 years apart. They underwent a resting-state functional magnetic resonance imaging and a high-resolution anatomical acquisition, as well as clinical assessments. Functional imaging data were analyzed with dynamic causal modeling, and parametric empirical Bayes model was used to map effective connectivity between 7 distinct nodes: 4 from the locus coeruleus and 3 regions displaying gray matter decreases during the two-year follow-up period. RESULTS: Longitudinal analysis of structural data identified three clusters of larger over-time gray matter volume reduction in patients (MDD+aMCI vs. HCs): the right precuneus, and the visual association and parahippocampal cortices. aMCI patients showed decreased effective connectivity from the left rostral to caudal portions of the LC, while connectivity from the left rostral LC to the parahippocampal cortex increased. In MDD, there was a decline in effective connectivity across LC caudal seeds, and increased connectivity from the left rostral to the left caudal LC seed over time. Connectivity alterations with cortical regions involved cross-hemisphere increases and same-hemisphere decreases. CONCLUSIONS: Our discoveries provide insight into the dynamic changes in effective connectivity in individuals with late-life MDD and aMCI, also shedding light on the mechanisms potentially contributing to the onset of neurodegenerative disorders.

Val66Met BDNF genotypes in melancholic depression: effects on brain structure and treatment outcome.

BACKGROUND: A brain-derived neurotrophic factor (BDNF) prodomain single-nucleotide polymorphism resulting in a valine to methionine substitution (Val66Met) has been associated with depression-related phenotypes and brain alterations involving regions consistently associated with major depressive disorder (MDD). The aim of our study was to evaluate the association of regional gray matter (GM) volume within the hippocampus and other unpredicted regions at the whole-brain level with the BDNF Val66Met polymorphism in MDD patients with melancholic features and their impact on treatment outcome. METHODS: A sample of 37 MDD inpatients was assessed with three-dimensional magnetic resonance imaging (1.5-T scanner). GM volume was analyzed with voxel-based morphometry (VBM) using Statistical Parametric Mapping (SPM5). The BDNF Val66Met variant was genotyped using SNPlex technology. MDD patients were classified according to genotype distribution under a dominant model of inheritance and thus comparing Val66 homozygotes (n = 22) versus Met66 carriers (n = 15). RESULTS: A significant GM volume reduction in the left hippocampus was observed in Met66 carriers. Conversely, in the same group, a volume increase in the right orbitofrontal cortex was detected. Moreover, a significant negative correlation between left hippocampal volume and days to remission was found in Val66 homozygotes, whereas right orbitofrontal volume was inversely correlated to days to remission in Met66 carriers. CONCLUSIONS: Our results suggest that the Val66Met BDNF variant may have a differential impact on the brain structure of melancholic patients with possible treatment outcome implications.

Importance of immunometabolic markers for the classification of patients with major depressive disorder using machine learning.

BACKGROUND: Although there is scientific evidence of the presence of immunometabolic alterations in major depression, not all patients present them. Recent studies point to the association between an inflammatory phenotype and certain clinical symptoms in patients with depression. The objective of our study was to classify major depression disorder patients using supervised learning algorithms or machine learning, based on immunometabolic and oxidative stress biomarkers and lifestyle habits. METHODS: Taking into account a series of inflammatory and oxidative stress biomarkers (C-reactive protein (CRP), tumor necrosis factor (TNF), 4-hydroxynonenal (HNE) and glutathione), metabolic risk markers (blood pressure, waist circumference and glucose, triglyceride and cholesterol levels) and lifestyle habits of the participants (physical activity, smoking and alcohol consumption), a study was carried out using machine learning in a sample of 171 participants, 91 patients with depression (71.42% women, mean age = 50.64) and 80 healthy subjects (67.50% women, mean age = 49.12). The algorithm used was the support vector machine, performing cross validation, by which the subdivision of the sample in training (70%) and test (30%) was carried out in order to estimate the precision of the model. The prediction of belonging to the patient group (MDD patients versus control subjects), melancholic type (melancholic versus non-melancholic patients) or resistant depression group (treatment-resistant versus non-treatment-resistant) was based on the importance of each of the immunometabolic and lifestyle variables. RESULTS: With the application of the algorithm, controls versus patients, such as patients with melancholic symptoms versus non-melancholic symptoms, and resistant versus non-resistant symptoms in the test phase were optimally classified. The variables that showed greater importance, according to the results of the area under the ROC curve, for the discrimination between healthy subjects and patients with depression were current alcohol consumption (AUC = 0.62), TNF-α levels (AUC = 0.61), glutathione redox status (AUC = 0.60) and the performance of both moderate (AUC = 0.59) and vigorous physical exercise (AUC = 0.58). On the other hand, the most important variables for classifying melancholic patients in relation to lifestyle habits were past (AUC = 0.65) and current (AUC = 0.60) tobacco habit, as well as walking routinely (AUC = 0.59) and in relation to immunometabolic markers were the levels of CRP (AUC = 0.62) and glucose (AUC = 0.58). In the analysis of the importance of the variables for the classification of treatment-resistant patients versus non-resistant patients, the systolic blood pressure (SBP) variable was shown to be the most relevant (AUC = 0.67). Other immunometabolic variables were also among the most important such as TNF-α (AUC = 0.65) and waist circumference (AUC = 0.64). In this case, sex (AUC = 0.59) was also relevant along with alcohol (AUC = 0.58) and tobacco (AUC = 0.56) consumption. CONCLUSIONS: The results obtained in our study show that it is possible to predict the diagnosis of depression and its clinical typology from immunometabolic markers and lifestyle habits, using machine learning techniques. The use of this type of methodology could facilitate the identification of patients at risk of presenting depression and could be very useful for managing clinical heterogeneity.

Genetic variants and abnormal processing of pre-miR-182, a circadian clock modulator, in major depression patients with late insomnia.

Previous studies in mice have reported five different microRNAs (miRNAs; miR-219-1/132/183/96/182) to be modulators of the endogenous circadian clock and have presented experimental evidence for some of the genes involved in the molecular clock machinery as target sites. Moreover, disruption of circadian rhythms has long been implicated in the pathophysiology of major depression (MD). We investigated these miRNAs and some of their target sites at the sequence and functional levels as possible predisposing factors for susceptibility to MD and related chronobiological subphenotypes. Mutational screening was performed in a sample of 359 MD patients and 341 control individuals. We found a significant association between the T allele of the rs76481776 polymorphism in the pre-miR-182 and late insomnia in MD patients. Previous studies have reported an association between insomnia and CLOCK gene, a predicted miR-182 target site. A significant overexpression of miR-182 was detected by quantitative real-time polymerase chain reaction in cells transfected with the mutated form of the pre-miR-182 when compared with wild-type form. Moreover, a significant reduction in luciferase activity of plasmids with 3' UTR of ADCY6, CLOCK and DSIP genes was shown when transfecting cells with the mutated form of pre-miR-182 compared with cells that did not express miR-182. These data indicate that abnormal processing of pre-miR-182 in patients carrying the T allele of the rs76481776 polymorphism may contribute to the dysregulation of circadian rhythms in MD patients with insomnia, which could influence expression levels of the mature form of miR-182 and might increase downregulation in some of its target genes.

Long-term treatment strategies in major depression: a 2-year prospective naturalistic follow-up after successful electroconvulsive therapy.

OBJECTIVE: To describe a 2-year follow-up in a cohort of patients with major depressive disorder treated with pharmacotherapy plus a short-term course of electroconvulsive therapy (ECT) over the index episode. METHODS: This naturalistic study included 127 patients. After remission, the same pharmacotherapy regimen was maintained in all patients, whereas 44 also received continuation/maintenance ECT (C/M-ECT). Demographic and clinical data were reported for patients with pharmacotherapy and patients with pharmacotherapy and C/M-ECT. The clinical course of the disorder was compared two years before and after index episode remission. RESULTS: Continuation/maintenance ECT was more prescribed in men and in those patients with more previous episodes and admissions and higher treatment resistance. Longer duration of index episode and greater number of episodes in the previous 2 years were identified as risk factors for relapse/recurrence. Furthermore, in our sample, a significant improvement of the illness course after remission was observed after successful ECT. CONCLUSION: Both treatments were effective as maintenance strategies for depressive patients who showed complete response to an acute ECT course. According to our observations, pharmacotherapy both alone and plus C/M-ECT may potentially be considered as long-term treatments after successful ECT in patients with severe major depressive disorder.

Hormone Targets for the Treatment of Sleep Disorders in Postmenopausal Women with Schizophrenia: A Narrative Review.

While the early identification of insomnia in patients with schizophrenia is of clinical relevance, the use of specific compounds to treat insomnia has been studied less in postmenopausal women with schizophrenia. We aimed to explore the effects of melatonin, sex hormones, and raloxifene for the treatment of insomnia in these populations. Although melatonin treatment improved the quality and efficiency of the sleep of patients with schizophrenia, few studies have explored its use in postmenopausal women with schizophrenia. The estrogen and progesterone pathways are dysregulated in major psychiatric disorders, such as in schizophrenia. While, in the context of menopause, a high testosterone-to-estradiol ratio is associated with higher frequencies of depressive symptoms, the effects of estradiol and other sex hormones on sleep disorders in postmenopausal women with schizophrenia has not been sufficiently investigated. Raloxifene, a selective estrogen receptor modulator, has shown positive effects on sleep disorders in postmenopausal women. Future studies should investigate the effectiveness of hormonal compounds on insomnia in postmenopausal women with schizophrenia.

A systematic review and meta-analysis of suicidality in psychotic disorders: Stratified analyses by psychotic subtypes, clinical setting and geographical region.

We studied the prevalence of suicide attempts and cumulative incidence of completed suicide in schizophrenia (SZ), schizoaffective disorder (SZAF), delusional disorder (DD) and first-episode psychosis (FEP). A systematic review was performed using Scopus and PubMed databases (1990- July 2020). A random effects meta-analysis was conducted. Stratified analyses were conducted by diagnosis, clinical setting and geographical region. The prevalence of attempted suicide was 20.3% for SZ, 46.8% for SZAF, 11.1% for DD and 12.5% for FEP. Suicide attempts rates were higher for outpatient samples than for inpatient samples in SZ, SZAF and DD (but not FEP) studies. Analyses by geographical region in SZ showed greater prevalence of suicide attempts in North America and Northern Europe. The cumulative incidence of completed suicide was 2.0% for SZ, 2.4% for SZAF; 2.2% for DD and 1.9% for FEP. In schizophrenia and FEP studies, Northern European studies reported higher rates of completed suicide when compared to Western European countries. In conclusion, suicidal behaviour rates in psychoses differ by diagnoses, clinical setting and geographical region.

Diagnosis of late-life depression using structural equation modeling and dynamic effective connectivity during resting fMRI.

BACKGROUND: Late-life depression (LLD) is characterized by cognitive and social impairments. Determining neurobiological alterations in connectivity in LLD by means of fMRI may lead to a better understanding of the neural basis underlying this disorder and more precise diagnostic markers. The primary objective of this paper is to identify a structural model that best explains the dynamic effective connectivity (EC) of the default mode network (DMN) in LLD patients compared to controls. METHODS: Twenty-seven patients and 29 healthy controls underwent resting-state fMRI during a period of eight minutes. In both groups, jackknife correlation matrices were generated with six ROIs of the DMN that constitute the posterior DMN (pDMN). The different correlation matrices were used as input to estimate each structural equation model (SEM) for each subject in both groups incorporating dynamic effects. RESULTS: The results show that the proposed LLD diagnosis algorithm achieves perfect accuracy in classifying LLD patients and controls. This differentiation is based on three aspects: the importance of ROIs 4 and 6, which seem to be the most distinctive among the subnetworks; the shape that the specific connections adopt in their networks, or in other words, the directed connections that are established among the ROIs in the pDMN for each group; and the number of dynamic effects that seem to be greater throughout the six ROIs studied [t = 54.346; df = 54; p < .001; 95 % CI difference = 5.486-5.906]. LIMITATIONS: The sample size was moderate, and the participants continued their current medications. CONCLUSIONS: The network models that we developed describe a pattern of dynamic activation in the pDMN that may be considered a possible biomarker for LLD, which may allow early diagnosis of this disorder.

Relationship between immunometabolic status and cognitive performance among major depression disorder patients.

BACKGROUND: Alterations in cognitive performance have been described in patients with major depressive disorder (MDD). However, the specific risk factors of these changes are not yet known. This study aimed to explore whether inmunometabolic parameters are related to cognitive performance in MDD in comparison to healthy controls (HC) METHODS: Sample consisted of 84 MDD patients and 78 HC. Both groups were compared on the results of cognitive performance measured with the Cambridge Neuropsychological Test Automated Battery (CANTAB), the presence of metabolic syndrome (MetS) and an inflammatory/oxidative index calculated by a principal component analysis of peripheral biomarkers (tumor necrosis factor, C-reactive protein and 4-hydroxynonenal). A multiple linear regression was carried out, to study the relationship between inmunometabolic variables and the global cognitive performance, being the latter the dependent variable. RESULTS: Significant differences were obtained in the inflammatory/oxidative index between both groups (F(1157)= 12.93; p < .001), also in cognitive performance (F(1157)= 56.75; p < .001). The inmunometabolic covariate regression model (i.e., condition (HC/MDD), sex, age and medication loading, MetS, inflammatory/oxidative index and the interaction between MetS and inflammatory/oxidative index) was statistically significant (F(7157)= 11.24; p < .01) and explained 31% of variance. The condition, being either MDD or HD, (B=-0.97; p < .001), age (B=-0.28; p < .001) and the interaction between inflammatory/oxidative index and MetS (B=-0.38; p = .02) were factors associated to cognitive performance. LIMITATIONS: Sample size was relatively small. The cross-sectional design of the study limits the possibilities of analysis. CONCLUSIONS: Our results provide evidence on the conjoint influence of metabolic and inflammatory dysregulation on cognitive dysfunction in MDD patients. In this way, our study opens a line of research in immunometabolic agents to deal with cognitive decline associated with MDD.

First manic/hypomanic episode in obsessive-compulsive disorder patients treated with antidepressants: A systematic review.

High doses of antidepressants, particularly clomipramine and selective serotonin reuptake inhibitors (SSRIs), are the well-established treatment for obsessive-compulsive disorder (OCD), but manic/hypomanic episodes are potential adverse events associated with this treatment. A systematic literature review was performed on manic/hypomanic episodes in non-bipolar OCD patients. Clinical, sociodemographic and antidepressant characteristics during the manic/hypomanic switch were extracted using descriptive statistics. Data were obtained from 20 case reports and case series. Switching episodes mostly appeared in the first 12 weeks after antidepressant initiation and took place more frequently during SSRI use (mostly fluoxetine) in 64.3% of cases. Clomipramine and SSRI use differed non-significantly between the switching episodes that appeared during the first 12 weeks of antidepressant treatment and the episodes that appeared beyond 12 weeks. Switching episodes emerging before 12 weeks were associated with a lower defined daily dose of antidepressants than episodes emerging after 12 weeks. These findings suggest that there are two independent characteristics involved in manic/hypomanic switch in OCD: a) they appeared most frequently with SSRI use (fluoxetine) regardless of the time of it use, and b) episodes appeared in the first 12 weeks after SSRI or clomipramine initiation had a lower dose of antidepressant than episodes appeared after 12 weeks.