823 research outputs found

    Citalopram plus low-dose pipamperone versus citalopram plus placebo in patients with major depressive disorder: an 8-week, double-blind, randomized study on magnitude and timing of clinical response

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    Background: Selective serotonin reuptake inhibitors take several weeks to achieve their full antidepressant effects. Post-synaptic 5-HT<sub>2A</sub> receptor activation is thought to be involved in this delayed therapeutic effect. Pipamperone acts as a highly selective 5-HT<sub>2A</sub>/D<sub>4</sub> antagonist when administered in low doses. The purpose of this study was to compare citalopram 40 mg once daily plus pipamperone 5 mg twice daily (PipCit) versus citalopram plus placebo twice daily for magnitude and onset of therapeutic effect. Method: An 8-week, randomized, double-blind study in patients with major depressive disorder was carried out. Results: The study population comprised 165 patients (citalopram and placebo, n=82; PipCit, n=83) with a mean baseline Montgomery–Asberg Depression Rating Scale (MADRS) score of 32.6 (S.D.=5.5). In the first 4 weeks, more citalopram and placebo than PipCit patients discontinued treatment (18% v. 4%, respectively, p=0.003). PipCit patients had significantly greater improvement in MADRS score at week 1 [observed cases (OC), p=0.021; last observation carried forward (LOCF), p=0.007] and week 4 (LOCF, p=0.025) but not at week 8 compared with citalopram and placebo patients. Significant differences in MADRS scores favoured PipCit in reduced sleep, reduced appetite, concentration difficulties and pessimistic thoughts. Mean Clinical Global Impression–Improvement scores were significantly improved after 1 week of PipCit compared with citalopram and placebo (OC and LOCF, p=0.002). Conclusions: Although the MADRS score from baseline to 8 weeks did not differ between groups, PipCit provided superior antidepressant effects and fewer discontinuations compared with citalopram and placebo during the first 4 weeks of treatment, especially in the first week

    Longitudinal structural brain changes in bipolar disorder: A multicenter neuroimaging study of 1232 individuals by the ENIGMA Bipolar Disorder Working Group

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    Background Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD. Methods Longitudinal structural MRI and clinical data from the ENIGMA-BD Working Group, including 307 BD patients and 925 healthy controls (HC), were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at two time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between BD and HC. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables. Results Compared with HC, BD patients showed faster enlargement of ventricular volumes and slower thinning of fusiform and parahippocampal cortex (0.18<d<0.22). More (hypo)manic episodes were associated with faster cortical thinning, primarily in the prefrontal cortex. Conclusion In the hitherto largest longitudinal MRI study on BD, we did not detect accelerated cortical thinning but noted faster ventricular enlargements in BD. Abnormal fronto-cortical thinning was however observed in association with frequent manic episodes. Our study yields insights into disease progression in BD, and highlights the importance of mania prevention in BD treatment

    Kids Run the World SHP

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    The Boys & Girls Club services children ages 6 to 18 with programs and activities that emphasize development strategies (BGCA, n.d.). It provides role models, a safe environment, and constructive activities that focus on overall health. The club depends heavily on community engagement in the form of donors, partnerships, and volunteers (BGCA, n.d.). Our local club provided programs focusing on financial responsibility, leadership, and mental health, but lacked development of physical health practices. Kids Run the World comprised various activities to promote physical health in adolescents. This program is led by college level volunteers that worked with elementary and middle school-aged children to show them fun and safe ways to exercise. Before implementation of the program, research was completed to understand the dynamics of the local Boys & Girls Club. This research included how to be an effective role model and successes of similar programs. This is when “Kid Run the World� was established and put into action. After volunteering at the Boys & Girls Club throughout the duration of our project, we have observed increased physical activity levels and overall morale when group members and athletes are there leading activities. This was successful because of consistent attendance and positive interactions with the children. We learned we needed to have a youthful perspective and engage the kids with exercises they found familiar. Despite COVID-19, our group continues to make efforts to engage youth through our organization on campus, Kids Run the World. The Boys & Girls Club has many underserved children, and this has provided our group with a unique platform that has benefited both us and the children through increased physical activity levels and community involvement

    Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder

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    Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk

    Markers of neuroinflammation and neuronal injury in bipolar disorder: Relation to prospective clinical outcomes

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    Neuroimmune mechanisms have been linked to the pathophysiology of bipolar disorder based on studies of biomarkers in plasma, cerebrospinal fluid (CSF), and postmortem brain tissue. There are, however, no longitudinal studies investigating if CSF markers of neuroinflammation and neuronal injury predict clinical outcomes in patients with bipolar disorder. We have in previous studies found higher CSF concentrations of interleukin-8 (IL-8), monocyte chemoattractant protein 1 (MCP-1/CCL-2), chitinase-3-like protein 1 (CHI3L1/YKL-40), and neurofilament light chain (NF-L) in euthymic patients with bipolar disorder compared with controls. Here, we investigated the relationship of these CSF markers of neuroinflammation and neuronal injury with clinical outcomes in a prospective study. 77 patients with CSF analyzed at baseline were followed for 6–7 years. Associations of baseline biomarkers with clinical outcomes (manic/hypomanic and depressive episodes, suicide attempts, psychotic symptoms, inpatient care, GAF score change) were investigated. Baseline MCP-1 concentrations were positively associated with manic/hypomanic episodes and inpatient care during follow-up. YKL-40 concentrations were negatively associated with manic/hypomanic episodes and with occurrence of psychotic symptoms. The prospective negative association between YKL-40 and manic/hypomanic episodes survived multiple testing correction. Concentrations of IL-8 and NF-L were not associated with clinical outcomes. High concentrations of these selected CSF markers of neuroinflammation and neuronal injury at baseline were not consistently associated with poor clinical outcomes in this prospective study. The assessed proteins may be involved in adaptive immune processes or reflect a state of vulnerability for bipolar disorder rather than being of predictive value for disease progression
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