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The major depressive disorder is one of the most common mental illnesses worldwide. Current treatment standards recommend a combined therapy with medication and psychotherapy. As an additive component and to further improvements in treatment, physical activity such as yoga may be integrated into conventional treatment. This study investigates the impact of a 3-month body-oriented yoga in patients with major depressive disorder (MDD). In total, n = 83 patients were included. An intervention group received a vigorous Ashtanga-Yoga three times a week. The waiting-list control group obtained a treatment as usual (TAU). As a primary outcome depression scores (Beck Depression Inventory-II (BDI-II), Montgomery Asberg Depression Rating Scale (MADRS)) were tested at three time points. Secondary outcome was the positive and negative affect [Positive and Negative Affect Scale (PANAS)] and remission rates. To analyze the data, multilevel models and effect sizes were conducted. The results showed an improvement in BDI-II scores for both groups over time [γ = − 3.46, t(165) = − 7.99, p < 0.001] but not between groups [γ = 0.98, t(164) = 1.12, p = 0.263]. An interaction effect (time x group) occurred for MADRS [γ = 2.10, t(164) = 2.10, p < 0.038]. Positive affects improved over time for both groups [γ = 1.65, t(165) = 4.03, p < 0.001]. Negative affects decreased for all over time [γ = − 1.00, t(165) = − 2.51, p = 0.013]. There were no significant group differences in PANAS. Post hoc tests revealed a greater symptom reduction within the first 6 weeks for all measurements. The effect sizes for depression scores showed a positive trend. Remission rates indicated a significant improvement in the yoga group (BDI-II: 46.81%, MADRS: 17.02%) compared to the control group (BDI: 33.33%, MADRS: 8.33%). The findings suggest that there is a trendsetting additive effect of Ashtanga-Yoga after 3 months on psychopathology and mood with a greater improvement at the beginning of the intervention. Further research in this field can help to achieve more differentiated results.
Physical inactivity is discussed as one of the most detrimental influences for lifestyle-related medical complications such as obesity, heart disease, hypertension, diabetes and premature mortality in in- and outpatients with major depressive disorder (MDD). In contrast, intervention studies indicate that moderate-to-vigorous-intensity physical activity (MVPA) might reduce complications and depression symptoms itself. Self-reported data on depression [Beck-Depression-Inventory-II (BDI-II)], general habitual well-being (FAHW), self-esteem and physical self-perception (FAHW, MSWS) were administrated in a cross-sectional study with 76 in- and outpatients with MDD. MVPA was documented using ActiGraph wGT3X + ® accelerometers and fitness was measured using cardiopulmonary exercise testing (CPET). Subgroups were built according to activity level (low PA defined as MVPA < 30 min/day, moderate PA defined as MVPA 30–45 min/day, high PA defined as MVPA > 45 min/day). Statistical analysis was performed using a Mann–Whitney U and Kruskal–Wallis test, Spearman correlation and mediation analysis. BDI-II scores and MVPA values of in- and outpatients were comparable, but fitness differed between the two groups. Analysis of the outpatient group showed a negative correlation between BDI-II and MVPA. No association of inpatient MVPA and psychopathology was found. General habitual well-being and self-esteem mediated the relationship between outpatient MVPA and BDI-II. The level of depression determined by the BDI-II score was significantly higher in the outpatient low- and moderate PA subgroups compared to outpatients with high PA. Fitness showed no association to depression symptoms or well-being. To ameliorate depressive symptoms of MDD outpatients, intervention strategies should promote habitual MVPA and exercise exceeding the duration recommended for general health (≥ 30 min/day). Further studies need to investigate sufficient MVPA strategies to impact MDD symptoms in inpatient settings. Exercise effects seem to be driven by changes of well-being rather than increased physical fitness.
Based on accumulating evidence of a role of lipid signaling in many physiological and pathophysiological processes including psychiatric diseases, the present data driven analysis was designed to gather information needed to develop a prospective biomarker, using a targeted lipidomics approach covering different lipid mediators. Using unsupervised methods of data structure detection, implemented as hierarchal clustering, emergent self-organizing maps of neuronal networks, and principal component analysis, a cluster structure was found in the input data space comprising plasma concentrations of d = 35 different lipid-markers of various classes acquired in n = 94 subjects with the clinical diagnoses depression, bipolar disorder, ADHD, dementia, or in healthy controls. The structure separated patients with dementia from the other clinical groups, indicating that dementia is associated with a distinct lipid mediator plasma concentrations pattern possibly providing a basis for a future biomarker. This hypothesis was subsequently assessed using supervised machine-learning methods, implemented as random forests or principal component analysis followed by computed ABC analysis used for feature selection, and as random forests, k-nearest neighbors, support vector machines, multilayer perceptron, and naïve Bayesian classifiers to estimate whether the selected lipid mediators provide sufficient information that the diagnosis of dementia can be established at a higher accuracy than by guessing. This succeeded using a set of d = 7 markers comprising GluCerC16:0, Cer24:0, Cer20:0, Cer16:0, Cer24:1, C16 sphinganine, and LacCerC16:0, at an accuracy of 77%. By contrast, using random lipid markers reduced the diagnostic accuracy to values of 65% or less, whereas training the algorithms with randomly permuted data was followed by complete failure to diagnose dementia, emphasizing that the selected lipid mediators were display a particular pattern in this disease possibly qualifying as biomarkers.