Brazilian Portuguese validation of Mood Disorder Questionnaire.

BACKGROUND: The Mood Disorder Questionnaire (MDQ) is a screening instrument for bipolar spectrum disorders already validated in many languages. METHODS: Patients from 2 psychiatric outpatient facilities were diagnosed with bipolar disorder (BD) type I and II and major depression according to the mood module of the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (SCID), Axis I Disorders--Clinician Version. In addition, a control group of healthy subjects was selected. The diagnostic interviews were used as the gold standard against which to investigate the performance of the MDQ. The MDQ was administered to 153 subjects, distributed among 4 groups. We analyzed the test reliability and discriminative capacity of the MDQ for the detection of patients with BD. RESULTS: Based on the SCID, Axis I Disorders--Clinician Version, 52 subjects (33.3%) presented a bipolar spectrum disorder (type I, II, or not otherwise specified), 48 (32.4%) were diagnosed as having unipolar depressive disorder, whereas 54 (35.3%) were unaffected by any type of psychiatric disorder (had no psychiatric disorder according to SCID results). The sensitivity for bipolar disorder was 0.72 (bipolar I disorder, 0.81; bipolar II disorder, 0.58; and bipolar disorder not otherwise specified, 0.69), with specificity of 0.95. The Brazilian Portuguese MDQ demonstrated adequate internal consistency (Cronbach α = .87). LIMITATIONS: Recruiting patients attending tertiary services may inflate the performance of the MDQ. CONCLUSIONS: The performance of the Brazilian Portuguese MDQ is comparable with other language validations. In a psychiatric outpatient sample, the Brazilian Portuguese MDQ proves to be a feasible and reliable screening instrument.

Bipolar disorder treatment according to illness trajectory: a systematic review of clinical trials.

The current bipolar disorder treatment guidelines focus mainly on the prevention of recurrence and stabilization of acute mood episodes while neglecting outcomes related to the longitudinal course of illness. We systematically reviewed studies that assess the impact of disease progression in the treatment of patients with bipolar disorder. We searched PubMed, Embase, and Web of Science for clinical trials that moderated treatment effects by number of previous episodes, disease length, or a clinical staging model. We retrieved 6,156 potential abstracts. After deduplication, 5,376 were screened and eight studies met inclusion criteria. Seven trials moderated results by number of prior episodes, and one of those also used a measure of disease length. One trial used a clinical staging model and yielded informing results. Only three studies evaluated pharmacological interventions, the other five assessing psychotherapeutic modalities. Most of the studies were post-hoc analysis of clinical trials not primarily aimed at studying variables associated with illness trajectory. Overall, a loss of efficacy was found according to clinical progression, which supports early intervention. Tailored recommendations according to disease stages cannot be made. Furthermore, we identified methodological weaknesses and strengths in this subfield of research, suggesting the use of clinical staging models for future studies.

Accelerated aging signatures in subjects with schizophrenia and their unaffected siblings.

Schizophrenia (SZ) is a chronic debilitating disease. Subjects with SZ have significant shorter life expectancy. Growing evidence suggests that a process of pathological accelerated aging occurs in SZ, leading to early development of severe clinical diseases and worse morbimortality. Furthermore, unaffected relatives can share certain endophenotypes with subjects with SZ. We aim to characterize accelerated aging as a possible endophenotype of schizophrenia by using a machine learning (ML) model of peripheral biomarkers to accurately differentiate subjects with SZ (n = 35), their unaffected siblings (SB, n = 36) and healthy controls (HC, n = 47). We used a random forest algorithm that included biomarkers related to aging: eotaxins CCL-11 and CCL-24; the oxidative stress markers thiobarbituric acid-reactive substances (TBARS), protein carbonyl content (PCC), glutathione peroxidase (GPx); and telomere length (TL). The ML algorithm of biomarkers was able to distinguish individuals with SZ from HC with prediction accuracy of 79.7%, SZ from SB with 62.5% accuracy and SB from HC with 75.5% accuracy. These results support the hypothesis that a pathological accelerated aging might occur in SZ, and this pathological aging could be an endophenotype of the disease, once this profile was also observed in SB, suggesting that SB might suffer from an accelerated aging in some level.