Prevalence and profile of depressive mixed state in patients with autism spectrum disorder

Purpose: The present study aimed to clarify prevalence and profile of depressive mixed state (DMX) in depressed individuals with autism spectrum disorder (ASD). Patients and methods: The Quick Inventory of Depressive Symptomatology Self-Report Japanese version (QIDS-SR-J) and global assessment of functioning (GAF) were administered to 182 consecutive patients (36 ASD and 146 non-ASD subjects) with a major depressive episode (MDE). DMX was categorically diagnosed according to the criteria for mixed depression (MD) by Benazzi and mixed features (MF) specifier by DSM-5. Severity of DMX was assessed by the self-administered 12-item questionnaire for DMX (DMX-12). Clinical backgrounds and incidence/severity of DMX were compared between the ASD and non-ASD groups. Results: ASD patients showed higher prevalence of MD than non-ASD patients (36.1% versus 18.5%). Mood lability, distractibility, impulsivity, aggression, irritability, dysphoria and risk-taking behavior as mixed symptoms were more prevalent in ASD patients than those in non-ASD patients, together with higher scores of total DMX-12 and its disruptive emotion/behavior cluster. Multiple regression analysis revealed significant contribution of ASD to the disruptive emotion/behavior symptoms. Conclusion: Careful monitoring and management of potential DMX are warranted in depressed ASD individuals

Development of a 20-item questionnaire for drinking behavior pattern (DBP-20) toward personalized behavioral approaches for alcohol use disorder

Although screening tools are available for alcohol use disorders (AUD), such as the Alcohol Use Disorders Identification Test (AUDIT), these tools do not directly characterize individual drinking behavior for patients with AUD. Therefore, the aim of this study was to develop a new self-report questionnaire to identify the characteristics of drinking behavior patterns in patients with AUD. The study team developed a self-administered 20-item questionnaire for drinking behavior pattern (DBP-20) based on semistructured interviews of patients with AUD. The DBP-20 and AUDIT were administered to 232 patients with AUD and 222 normal drinkers (1 ≤ AUDIT <20) as controls. Exploratory factor analysis of the DBP-20 was conducted for patients with AUD, followed by comparisons of its item and subscale scores between patients with AUD and controls. Correlations of AUDIT with total and subscale scores of the DBP-20 were also analyzed. Receiver operating characteristic (ROC) analyses for the DBP-20 and its subscales were performed to distinguish patients with AUD from controls. Exploratory factor analysis revealed a multidimensional 4-factor model of the DBP-20: coping with negative affect, automaticity, enhancement, and social use. Significant differences in DBP-20 total and subscale scores were observed for patients with AUD versus controls for all factors, except the social use subscale. Both the coping with negative affect and automaticity subscale scores as well as total DBP-20 scores were highly correlated with AUDIT scores. Total DBP-20 scores showed the greatest sensitivity, negative predictive value, and area under the ROC curve to distinguish patients with AUD from normal drinkers. Drinking as a means of coping with negative affect and automaticity may be specific for patients with AUD. DBP-20 may help patients with AUD to be aware of their own targeted problematic drinking behaviors and to seek their personalized behavioral approaches in a collaborative relationship with therapists

Diagnosis & treatment of mixed depression

Although the definition of depressive mixed state, more commonly known as mixed depression, is still controversial, about one-third of major depressive episodes are held to contain mixed components. The most frequent manifestations of mixed depression are irritability, distractibility and psychomotor agitation, although these symptoms are not included in the mixed features during a major depressive episode according to the DSM-5 criteria, which is therefore unlikely to cover the full scope of mixed depression in real-world settings. Mixed depression often accompanies risky behavior including impulsive suicide attempts. The early detection and treatment of these unstable conditions is therefore necessary. Also, sufficiently sensitive and specific screening methods for depressive mixed state are needed to avoid both under- and over-diagnosis. Antidepressants should be avoided since these drugs often worsen irritability, agitation and impulsivity, and increase risky behavior. Instead, combination therapy with mood stabilizer(s) to prevent the relapse of the depressive mixed state and atypical antipsychotics for rapid stabilization in the acute phase should be considered. Because there is very little evidence for effective pharmacotherapy in mixed depression, the efficacy of various mood-stabilizing agents, either as monotherapy or in combination therapies, should be extensively examined in the future using quantitative assessments of the psychopathology of mixed depression in patients with confirmed diagnoses of mixed depression

Development of the 12-item questionnaire for quantitative assessment of depressive mixed state (DMX-12)

Background: Conventional categorical criteria have limitations in assessing the prevalence and severity of depressive mixed state (DMX). Thus, we have developed a new scale for screening and quantification of DMX and examined the symptomatological structure and severity of DMX in individuals with major depressive episode (MDE). Methods: Subjects were 154 patients with MDE (57 males and 97 females; age 13–83 years). Our original Japanese version of the self-administered 12-item questionnaire to assess DMX (DMX-12), together with the Quick Inventory of Depressive Symptomatology Self- Report Japanese version (QIDS-SR-J) and global assessment of functioning, were administered to each participant. The symptomatological structure of the DMX-12 was examined by exploratory factor analysis. Multiple regression analyses were used to analyze factors contributing to the DMX-12 scale. The relationships of this scale with categorical diagnoses (mixed depression by Benazzi and mixed features by DSM-5) were also investigated. Results: A three-factor model of the DMX-12 was extracted from exploratory factor analysis, namely, “spontaneous instability”, “vulnerable responsiveness”, and “disruptive emotion/behavior”. Multiple regression analyses revealed that age was negatively correlated with total DMX-12 score, while bipolarity and the QIDS-SR-J score were positively correlated. A higher score on the disruptive emotion/behavior subscale was observed in patients with mixed depression and mixed features. Conclusion: The DMX-12 seems to be useful for screening DMX in conjunction with conventional categorical diagnoses. Severely depressed younger subjects with potential bipolarity are more likely to develop DMX. The disruptive emotion/behavior subscale of the DMX-12 may be the most helpful in distinguishing patients with DMX from non-mixed patients.博士(医学)琉球大

Development of the 12-item questionnaire for quantitative assessment of depressive mixed state (DMX-12)

Background: Conventional categorical criteria have limitations in assessing the prevalence and severity of depressive mixed state (DMX). Thus, we have developed a new scale for screening and quantification of DMX and examined the symptomatological structure and severity of DMX in individuals with major depressive episode (MDE). Methods: Subjects were 154 patients with MDE (57 males and 97 females; age 13-83 years). Our original Japanese version of the self-administered 12-item questionnaire to assess DMX (DMX-12), together with the Quick Inventory of Depressive Symptomatology Self-Report Japanese version (QIDS-SR-J) and global assessment of functioning, were administered to each participant. The symptomatological structure of the DMX-12 was examined by exploratory factor analysis. Multiple regression analyses were used to analyze factors contributing to the DMX-12 scale. The relationships of this scale with categorical diagnoses (mixed depression by Benazzi and mixed features by DSM-5) were also investigated. Results: A three-factor model of the DMX-12 was extracted from exploratory factor analysis, namely, "spontaneous instability", "vulnerable responsiveness", and "disruptive emotion/behavior". Multiple regression analyses revealed that age was negatively correlated with total DMX-12 score, while bipolarity and the QIDS-SR-J score were positively correlated. A higher score on the disruptive emotion/behavior subscale was observed in patients with mixed depression and mixed features. Conclusion: The DMX-12 seems to be useful for screening DMX in conjunction with conventional categorical diagnoses. Severely depressed younger subjects with potential bipolarity are more likely to develop DMX. The disruptive emotion/behavior subscale of the DMX-12 may be the most helpful in distinguishing patients with DMX from non-mixed patients

A large-scale ENIGMA multisite replication study of brain age in depression

International audienceBackgroundSeveral studies have evaluated whether depressed persons have older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived “brain age gap” has varied from study to study, likely driven by differences in training and testing sample (size), age range, and used modality/features. To validate our previously developed ENIGMA brain age model and the identified brain age gap, we aim to replicate the presence and effect size estimate previously found in the largest study in depression to date (N = 2126 controls & N = 2675 cases; +1.08 years [SE 0.22], Cohen's d = 0.14, 95% CI: 0.08–0.20), in independent cohorts that were not part of the original study.MethodsA previously trained brain age model (www.photon-ai.com/enigma_brainage) based on 77 FreeSurfer brain regions of interest was used to obtain unbiased brain age predictions in 751 controls and 766 persons with depression (18–75 years) from 13 new cohorts collected from 20 different scanners. Meta-regressions were used to examine potential moderating effects of basic cohort characteristics (e.g., clinical and scan technical) on the brain age gap.ResultsOur ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R2 = 0.47, MAE = 7.50 years), although the performance varied from cohort to cohort. In these new cohorts, on average, depressed persons showed a significantly higher brain age gap of +1 year (SE 0.35) (Cohen's d = 0.15, 95% CI: 0.05–0.25) compared with controls, highly similar to our previous finding. Significant moderating effects of FreeSurfer version 6.0 (d = 0.41, p = 0.007) and Philips scanner vendor (d = 0.50, p 3400 patients and >2800 controls worldwide show reliable but subtle effects of brain aging in adult depression. Future studies are needed to identify factors that may further explain the brain age gap variance between cohorts