895 resultados para Major depessive disorder


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BACKGROUND Psychomotor disturbances are a main clinical feature of major depressive disorder (MDD) but little is known about their EEG signature. One of the most replicated EEG findings in MDD is resting frontal asymmetry in the alpha band (FAA), which is thought to be a correlate of withdrawal behavior and reduced approach motivation. The purpose of this study was to assess psychomotor alterations, alpha band power, FAA and investigate the association between them. METHODS 20 MDD patients and 19 healthy subjects were enrolled. Alpha power and FAA scores were calculated from a resting state EEG. Wrist actigraphy was recorded from the non-dominant arm for 24 h and activity level scores (AL) were extrapolated from the wakeful periods. RESULTS MDD patients had a left-lateralized frontal alpha activity and lower AL scores when compared to healthy subjects. A significant correlation was found between mean FAA and AL scores. A negative covariance between power in the lower alpha range and AL scores over the motor cortex bilaterally was detected. LIMITATIONS Relatively small sample size. Patients were pharmacologically treated with antidepressants. CONCLUSIONS This study replicates the finding of left-lateralized FAA and lower AL scores in MDD patients, and establishes the first evidence of significant correlations between alpha power, FAA scores and measures of motor activity, which may be interpreted as an expression of impaired motivational drive in MDD.

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Frontal alpha band asymmetry (FAA) is a marker of altered reward processing in major depressive disorder (MDD), associated with reduced approach behavior and withdrawal. However, its association with brain metabolism remains unclear. The aim of this study is to investigate FAA and its correlation with resting – state cerebral blood flow (rCBF). We hypothesized an association of FAA with regional rCBF in brain regions relevant for reward processing and motivated behavior, such as the striatum. We enrolled 20 patients and 19 healthy subjects. FAA scores and rCBF were quantified with the use of EEG and arterial spin labeling. Correlations of the two were evaluated, as well as the association with FAA and psychometric assessments of motivated behavior and anhedonia. Patients showed a left – lateralized pattern of frontal alpha activity and a correlation of FAA lateralization with subscores of Hamilton Depression Rating Scale linked to motivated behavior. An association of rCBF and FAA scores was found in clusters in the dorsolateral prefrontal cortex bilaterally (patients) and in the left medial frontal gyrus, in the right caudate head and in the right inferior parietal lobule (whole group). No correlations were found in healthy controls. Higher inhibitory right – lateralized alpha power was associated with lower rCBF values in prefrontal and striatal regions, predominantly in the right hemisphere, which are involved in the processing of motivated behavior and reward. Inhibitory brain activity in the reward system may contribute to some of the motivational problems observed in MDD.

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Objective: Sertraline's efficacy and tolerability in treating generalized anxiety disorder were evaluated. Method: Adult outpatients with DSM-IV generalized anxiety disorder and a total score of 18 or higher on the Hamilton Anxiety Rating Scale were eligible. After a 1-week single-blind placebo lead-in, patients were randomly assigned to 12 weeks of double-blind treatment with placebo (N=188, mean baseline anxiety score=25) or flexible doses (50-150 mg/day) of sertraline (N=182, mean anxiety score=25). The primary outcome measure was baseline-to-endpoint change in the Hamilton anxiety scale total score. A secondary efficacy measure was the Clinical Global Impression (CGI) improvement score; response was defined as a score of 2 or less. Results: Sertraline patients had significantly greater improvement than placebo patients on all efficacy measures at week 4. Analysis of covariance of the intent-to-treat group at endpoint (with the last observation carried forward) showed a significant difference in the decrease from baseline of the least-square mean total score on the Hamilton anxiety scale between sertraline (mean=11.7) and placebo (mean=8.0). Significantly greater endpoint improvement with sertraline than placebo was obtained for mean scores on the Hamilton anxiety scale psychic factor (6.7 versus 4.1) and somatic factor (5.0 versus 3.9). The rate of responders, based on CGI improvement and last observation carried forward, was significantly higher for sertraline (63%) than placebo (37%). Sertraline was well tolerated; 8% of patients versus 10% for placebo dropped out because of adverse events. Conclusions: Sertraline appears to be efficacious and well tolerated in the treatment of generalized anxiety disorder.

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Background - Bipolar disorder is frequently misdiagnosed as major depressive disorder, delaying appropriate treatment and worsening outcome for many bipolar individuals. Emotion dysregulation is a core feature of bipolar disorder. Measures of dysfunction in neural systems supporting emotion regulation might therefore help discriminate bipolar from major depressive disorder. Methods - Thirty-one depressed individuals—15 bipolar depressed (BD) and 16 major depressed (MDD), DSM-IV diagnostic criteria, ages 18–55 years, matched for age, age of illness onset, illness duration, and depression severity—and 16 age- and gender-matched healthy control subjects performed two event-related paradigms: labeling the emotional intensity of happy and sad faces, respectively. We employed dynamic causal modeling to examine significant among-group alterations in effective connectivity (EC) between right- and left-sided neural regions supporting emotion regulation: amygdala and orbitomedial prefrontal cortex (OMPFC). Results - During classification of happy faces, we found profound and asymmetrical differences in EC between the OMPFC and amygdala. Left-sided differences involved top-down connections and discriminated between depressed and control subjects. Furthermore, greater medication load was associated with an amelioration of this abnormal top-down EC. Conversely, on the right side the abnormality was in bottom-up EC that was specific to bipolar disorder. These effects replicated when we considered only female subjects. Conclusions - Abnormal, left-sided, top-down OMPFC–amygdala and right-sided, bottom-up, amygdala–OMPFC EC during happy labeling distinguish BD and MDD, suggesting different pathophysiological mechanisms associated with the two types of depression.

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Patients with Bipolar Disorder (BD) perform poorly on tasks of selective attention and inhibitory control. Although similar behavioural deficits have been noted in their relatives, it is yet unclear whether they reflect dysfunction in the same neural circuits. We used functional magnetic resonance imaging and the Stroop Colour Word Task to compare task related neural activity between 39 euthymic BD patients, 39 of their first-degree relatives (25 with no Axis I disorders and 14 with Major Depressive Disorder) and 48 healthy controls. Compared to controls, all individuals with familial predisposition to BD, irrespective of diagnosis, showed similar reductions in neural responsiveness in regions involved in selective attention within the posterior and inferior parietal lobules. In contrast, hypoactivation within fronto-striatal regions, implicated in inhibitory control, was observed only in BD patients and MDD relatives. Although striatal deficits were comparable between BD patients and their MDD relatives, right ventrolateral prefrontal dysfunction was uniquely associated with BD. Our findings suggest that while reduced parietal engagement relates to genetic risk, fronto-striatal dysfunction reflects processes underpinning disease expression for mood disorders. © 2011 Elsevier Inc.

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Genetic factors are important in the etiology of bipolar disorder (BD). However, first-degree relatives of BD patients are at risk for a number of psychiatric conditions, most commonly major depressive disorder (MDD), although the majority remain well. The purpose of the present study was to identify potential brain structural correlates for risk and resilience to mood disorders in patients with BD, type I (BD-I) and their relatives. Structural magnetic resonance imaging scans were acquired from 30 patients with BD-I, 50 of their firstdegree relatives (28 had no Axis I disorder, while 14 had MDD) and 52 controls. We used voxel-based morphometry, implemented in SPM5 to identify group differences in regional gray matter volume. From the identified clusters, potential differences were further examined based on diagnostic status (BD-I patients, MDD relatives, healthy relatives, controls). Whole-brain voxel-based analysis identified group differences in the left hemisphere in the insula, cerebellum, and substantia nigra. Increased left insula volume was associated with genetic preposition to BD-I independent of clinical phenotype. In contrast, increased left substantia nigra volume was observed in those with the clinical phenotype of BD-I. Changes uniquely associated with the absence of a clinical diagnosis in BD relatives were observed in the left cerebellum. Our data suggest that in BD, genetic and phenotype-related influences on brain structure are dissociable; if replicated, these findings may help with early identification of high-risk individuals who are more likely to transition to syndromal states. Copyright © 2009 Society for Neuroscience.

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Background - The Met allele of the catechol-O-methyltransferase (COMT) valine-to-methionine (Val158Met) polymorphism is known to affect dopamine-dependent affective regulation within amygdala-prefrontal cortical (PFC) networks. It is also thought to increase the risk of a number of disorders characterized by affective morbidity including bipolar disorder (BD), major depressive disorder (MDD) and anxiety disorders. The disease risk conferred is small, suggesting that this polymorphism represents a modifier locus. Therefore our aim was to investigate how the COMT Val158Met may contribute to phenotypic variation in clinical diagnosis using sad facial affect processing as a probe for its neural action. Method - We employed functional magnetic resonance imaging to measure activation in the amygdala, ventromedial PFC (vmPFC) and ventrolateral PFC (vlPFC) during sad facial affect processing in family members with BD (n=40), MDD and anxiety disorders (n=22) or no psychiatric diagnosis (n=25) and 50 healthy controls. Results - Irrespective of clinical phenotype, the Val158 allele was associated with greater amygdala activation and the Met allele with greater signal change in the vmPFC and vlPFC. Signal changes in the amygdala and vmPFC were not associated with disease expression. However, in the right vlPFC the Met158 allele was associated with greater activation in all family members with affective morbidity compared with relatives without a psychiatric diagnosis and healthy controls. Conclusions - Our results suggest that the COMT Val158Met polymorphism has a pleiotropic effect within the neural networks subserving emotional processing. Furthermore the Met158 allele further reduces cortical efficiency in the vlPFC in individuals with affective morbidity. © 2010 Cambridge University Press.

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Background: Hypothalamic-pituitary-adrenal (HPA) axis dysregulation has been reported in bipolar disorder (BD), but previous magnetic resonance imaging (MRI) studies of pituitary gland volume in BD have yielded inconsistent findings. In addition, the contribution of genetic factors to the pituitary changes in BD remains largely unknown. Method: We used MRI to investigate the pituitary volume in 29 remitted patients with BD, 49 of their first-degree relatives (of whom 15 had a diagnosis of Major Depressive Disorder), and 52 age- and gender-matched healthy controls. Results: BD patients had a significantly larger pituitary volume compared with their relatives and healthy controls. Pituitary volume did not differ between controls and healthy relatives or relatives diagnosed with major depression. Limitations: Direct measures of HPA function (i.e., hormonal levels) were not available. Conclusions: These findings suggest that enlarged pituitary volume is associated with disease expression but not genetic susceptibility to BD. © 2009 Elsevier B.V. All rights reserved.

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Over the last few years, zonisamide has been proposed as a potentially useful medication for patients with focal seizures, with or without secondary generalization. Since psychiatric adverse effects, including mania, psychosis, and suicidal ideation, have been associated with its use, it was suggested that the presence of antecedent psychiatric disorders is an important factor associated with the discontinuation of zonisamide therapy in patients with epilepsy. We, therefore, set out to assess the tolerability profile of zonisamide in a retrospective chart review of 23 patients with epilepsy and comorbid mental disorders, recruited from two specialist pediatric (n=11) and adult (n=12) neuropsychiatry clinics. All patients had a clinical diagnosis of treatment-refractory epilepsy after extensive neurophysiological and neuroimaging investigations. The vast majority of patients (n=22/23, 95.7%) had tried previous antiepileptic medications, and most adult patients (n=9/11, 81.8%) were on concomitant medication for epilepsy. In the majority of cases, the psychiatric adverse effects of zonisamide were not severe. Four patients (17.4%) discontinued zonisamide because of lack of efficacy, whereas only one patient (4.3%) discontinued it because of the severity of psychiatric adverse effects (major depressive disorder). The low discontinuation rate of zonisamide in a selected population of patients with epilepsy and neuropsychiatric comorbidity suggests that this medication is safe and reasonably well-tolerated for use in patients with treatment-refractory epilepsy. Given the limitations of the present study, including the relatively small sample size, further research is warranted to confirm this finding. © 2013 Elsevier Inc.

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Impaired facial expression recognition has been associated with features of major depression, which could underlie some of the difficulties in social interactions in these patients. Patients with major depressive disorder and age- and gender-matched healthy volunteers judged the emotion of 100 facial stimuli displaying different intensities of sadness and happiness and neutral expressions presented for short (100 ms) and long (2,000 ms) durations. Compared with healthy volunteers, depressed patients demonstrated subtle impairments in discrimination accuracy and a predominant bias away from the identification as happy of mildly happy expressions. The authors suggest that, in depressed patients, the inability to accurately identify subtle changes in facial expression displayed by others in social situations may underlie the impaired interpersonal functioning.

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A.F. is supported by Research Capability Funding from the Northumberland-Tyne-and-Wear NHS Foundation Trust awarded to R.H.M.-W.

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Background and Aims Affective instability (AI), childhood trauma, and mental illness are linked, but evidence in affective disorders is limited, despite both AI and childhood trauma being associated with poorer outcomes. Aims were to compare AI levels in bipolar disorder I (BPI) and II (BPII), and major depressive disorder recurrent (MDDR), and to examine the association of AI and childhood trauma within each diagnostic group. Methods AI, measured using the Affective Lability Scale (ALS), was compared between people with DSM-IV BPI (n = 923), BPII (n = 363) and MDDR (n = 207) accounting for confounders and current mood. Regression modelling was used to examine the association between AI and childhood traumas in each diagnostic group. Results ALS scores in descending order were BPII, BPI, MDDR, and differences between groups were significant (p < 0.05). Within the BPI group any childhood abuse (p = 0.021), childhood physical abuse (p = 0.003) and the death of a close friend in childhood (p = 0.002) were significantly associated with higher ALS score but no association was found between childhood trauma and AI in BPII and MDDR. Conclusions AI is an important dimension in bipolar disorder independent of current mood state. There is a strong link between childhood traumatic events and AI levels in BPI and this may be one way in which exposure and disorder are linked. Clinical interventions targeting AI in people who have suffered significant childhood trauma could potentially change the clinical course of bipolar disorder.

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OBJECTIVE: To test common genetic variants for association with seasonality (seasonal changes in mood and behavior) and to investigate whether there are shared genetic risk factors between psychiatric disorders and seasonality. METHOD: Genome-wide association studies (GWASs) were conducted in Australian (between 1988 and 1990 and between 2010 and 2013) and Amish (between May 2010 and December 2011) samples in whom the Seasonal Pattern Assessment Questionnaire (SPAQ) had been administered, and the results were meta-analyzed in a total sample of 4,156 individuals. Genetic risk scores based on results from prior large GWAS studies of bipolar disorder, major depressive disorder (MDD), and schizophrenia were calculated to test for overlap in risk between psychiatric disorders and seasonality. RESULTS: The most significant association was with rs11825064 (P = 1.7 × 10⁻⁶, β = 0.64, standard error = 0.13), an intergenic single nucleotide polymorphism (SNP) found on chromosome 11. The evidence for overlap in risk factors was strongest for schizophrenia and seasonality, with the schizophrenia genetic profile scores explaining 3% of the variance in log-transformed global seasonality scores. Bipolar disorder genetic profile scores were also associated with seasonality, although at much weaker levels (minimum P value = 3.4 × 10⁻³), and no evidence for overlap in risk was detected between MDD and seasonality. CONCLUSIONS: Common SNPs of large effect most likely do not exist for seasonality in the populations examined. As expected, there were overlapping genetic risk factors for bipolar disorder (but not MDD) with seasonality. Unexpectedly, the risk for schizophrenia and seasonality had the largest overlap, an unprecedented finding that requires replication in other populations and has potential clinical implications considering overlapping cognitive deficits in seasonal affective disorders and schizophrenia.

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Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.

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OBJECTIVE: The aim of this study was to translate the Structured Clinical Interview for Mood Spectrum into Brazilian Portuguese, measuring its reliability, validity, and defining scores for bipolar disorders. METHOD: Questionnaire was translated (into Brazilian Portuguese) and back-translated into English. Sample consisted of 47 subjects with bipolar disorder, 47 with major depressive disorder, 18 with schizophrenia and 22 controls. Inter-rater reliability was tested in 20 subjects with bipolar disorder and MDD. Internal consistency was measured using the Kuder Richardson formula. Forward stepwise discriminant analysis was performed. Scores were compared between groups; manic (M), depressive (D) and total (T) threshold scores were calculated through receiver operating characteristic (ROC) curves. RESULTS: Kuder Richardson coefficients were between 0.86 and 0.94. Intraclass correlation coefficient was 0.96 (CI 95 % 0.93-0.97). Subjects with bipolar disorder had higher M and T, and similar D scores, when compared to major depressive disorder (ANOVA, p < 0.001). The sub-domains that best discriminated unipolar and bipolar subjects were manic energy and manic mood. M had the best area under the curve (0.909), and values of M equal to or greater than 30 yielded 91.5% sensitivity and 74.5% specificity. CONCLUSION: Structured Clinical Interview for Mood Spectrum has good reliability and validity. Cut-off of 30 best differentiates subjects with bipolar disorder vs. unipolar depression. A cutoff score of 30 or higher in the mania sub-domain is appropriate to help make a distinction between subjects with bipolar disorder and those with unipolar depression.