Profiles and the impact of affective temperaments on alcohol use disorder: a cross-sectional study.

AIMS: This study aimed to explore the profiles and impact of affective temperaments, together with social and clinical backgrounds, including affective symptoms, in patients with alcohol use disorder (AUD). METHODS: This study included 314 low-risk drinkers and 257 patients with AUD. To assess affective temperament, we used the short version of the temperament evaluation of Memphis, Pisa, Paris, and San Diego. To evaluate depressive and mixed symptoms, the quick inventory of depressive symptomatology self-report Japanese version and 12-item questionnaire for the quantitative assessment of the depressive mixed state were used. We compared the profiles of affective temperaments as well as social and clinical backgrounds, including affective symptoms, between the two groups and further performed logistic regression analyses to explore the factors contributing to AUD. RESULTS: Our analysis showed higher cyclothymic, hyperthymic, and irritable temperament scores and lower depressive temperament scores in patients with AUD than that in nonclinical drinkers. Regarding other social and clinical backgrounds, patients with AUD were less educated and employed and more experienced depressive and mixed symptoms. Logistic regression analysis identified hyperthymic temperament as a positive contributor and depressive temperament as a negative contributor to AUD. CONCLUSIONS: Our findings indicated potential bipolarity in patients with AUD, as manifested by a more hyperthymic temperament in contrast to less depressive temperament. Despite their self-perceived adaptive temperament profiles, patients showed poorer social outcomes and more affective symptoms. This gap may be partly explained by a lack of insight unique to AUD psychology, which potentially disturbs problem recognition.

Elevated Brain-Derived Neurotrophic Factor Levels During Depressive Mixed States.

OBJECTIVE: Neurotrophin-like brain-derived neurotrophic factor (BDNF) and pro-inflammatory cytokines may modulate the pathophysiology of mood disorders. Although several studies show alterations in these biomarkers during the depressive, manic, and euthymic states of mood disorders, evidence is lacking for those in a mixed state. Therefore, this study aimed to investigate the relationship between the depressive mixed state (DMX) and peripheral neurobiological factors. METHODS: We enrolled 136 patients with major depressive episodes. Depressive symptoms were assessed using the Quick Inventory of Depressive Symptomatology Self-Report Japanese version (QIDS-SR-J). The severity of DMX was assessed using the self-administered 12-item questionnaire (DMX-12). Categorical screening as DMX-positive (n=54) was determined by a cutoff score of 13 or more in the specific eight symptoms from the DMX-12; the remaining were DMX-negative (n=82). Serum BDNF, tumor necrosis factor-α, highsensitivity C-reactive protein, and interleukin-6 levels were measured. RESULTS: When comparing biomarkers between the DMX-positive and DMX-negative groups, higher serum BDNF concentration in the DMX-positive group than in the DMX-negative group was the only significant finding (p=0.009). A positive correlation existed between the total score of the eight specific symptoms of DMX-12 and the BDNF concentration (r=0.190, p=0.027). After adjustment for confounders, logistic regression analysis revealed that BDNF (odds ratio [OR]=1.07, 95% confidence interval [CI]=1.00-1.14, p=0.045), bipolar diagnosis (OR=3.43, 95% CI=1.36-8.66, p=0.009), and total QIDS-SR-J score (OR=1.29, 95% CI=1.15-1.43, p<0.001) were significantly associated with DMX positivity. CONCLUSION: BDNF was positively associated with DMX severity, suggesting that higher BDNF concentrations may be involved in the pathophysiology of DMX.

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.

The 12-Item Self-Rating Questionnaire for Depressive Mixed State (DMX-12) for Screening of Mixed Depression and Mixed Features.

For simultaneous screening of mixed features (MF) by DSM-5 and mixed depression (MD) by Benazzi, useful symptoms were extracted from our 12-item dimensional scale for depressive mixed state (DMX-12). Subjects were 190 consecutive cases with major depressive episode (MDE) who visited our clinic. Associations between symptomatological combinations of the DMX-12 and MF or MD were analyzed using receiver operating characteristic (ROC). The rate of MF was 4.2% while that of MD was 22.6%. Eight symptoms (overreactivity, inner tension, racing/crowded thought, impulsivity, irritability, aggression, risk-taking behavior, and dysphoria) with their AUC > 0.6 for ROC curves were specially focused on distinguishing patients with MF or MD from non-mixed patients. By using these 8 symptoms, 40.5% of the overall patients were screened as positive at the same cut-off value (≥13) for both MD and MF. The AUC of ROC curve and sensitivity/specificity were well balanced together with sufficient negative predictive values. The abovementioned 8 symptoms seem to be helpful for primary screening and negative check of DMX with considerable severity during MDE.