View clinical trials related to Major Depressive Disorder.
Filter by:The overarching goal of the present study is to evaluate the effect of a subanesthetic dose of ketamine 24-hour post-injection on resting state functional connectivity, cognitive control, and reward learning.
The investigators are conducting this study to learn more about the cognitive and attentional processes among individuals with three types of repetitive negative thinking (RNT): mental rituals (as seen in obsessive compulsive disorder, OCD), worries (as seen in generalized anxiety disorder, GAD), and ruminations (as seen in major depressive disorder, MDD). Specifically, the investigators are studying whether psychological treatment can help people with RNT who have trouble stopping unwanted thoughts and shifting their attention.
The purpose of this study is to evaluate the efficacy and safety of Anyu Peibo Capsule comparing with placebo in the treatment of Chinese Patients with Depression.
The lifetime prevalence of major depressive disorder (MDD) is 10%~20%. Worldwide, nearly 340 million individuals have suffered the torture of depression. World Health Organization has reported that MDD would become the most serious global burden of disease and eventually turn into a public health problem in 2030. Varied clinical symptoms, inappropriate treatment, unclear pathogenesis, and lack of recurrent risk early-warning predictors cause a series of clinical problems, such as low diagnostic rate, low effective treatment rate, and high recurrent rate. Hence, this study aims to search multidimensional markers for early diagnosis of MDD, to establish optimized personalized therapy, and to explore sensitive recurrence predictors. Based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), MDD is subdivided into eight different clinical specifiers, one of which the incident rate of MDD with atypical features reaches 30%~38%. However, there is still a lack of meta-evidence for the clinical treatment strategy in MDD with atypical features. And 45.4 percentage of MDD with atypical features convert to bipolar disorder. Therefore, this study will focus on three issues about what's the objective endophenotype in MDD with atypical features, how to select appropriate personalized treatment for MDD with atypical features, what's the predictive biomarker of conversion to bipolar disorder. Based on the investigators' previous findings, this study will investigate adult depression at a cross-sectional study and a prospective cohort study. Multivariate informatics analysis was performed from three research dimensions (cognitive neuropsychology, metabonomics, and multimodal neuroimaging), including atypical features, "cold/hot" cognition assessment, KP (kynurenine pathway) metabolomics and inflammatory factors, multimodal MRI robust property. Referring guidelines for the diagnosis and treatment of depression and evidence-based medicine evidence, MDD with atypical features are divided into f groups (antidepressants, antidepressants+mood stabilizers, mood stabilizers, treat as usual). Then, the investigators perform follow-up to verify optimized treatment strategies and to explore risk factors of conversion from MDD with atypical features to bipolar disorder. Furthermore, this study performs correlation analysis to analyze cross-omics data, weight coefficient analysis to analyze multidimensional indexes, clustering analysis to analyze multivariate bio-information data, and artificial intelligence technologies (such as pattern recognition, and machine learning) to realize the transformation from medical data to practical transformation. Eventually, this study builds three specific models (the multidimensional early diagnosis models for MDD with atypical features, the optimized personalized therapy model, and the recurrence and conversion risk early-warning model), which form the integrated intelligent platform for multidimensional diagnosis, personalized treatment, recovery management of MDD with atypical features.
Major depressive disorder (MDD) is a chronic disease with high incidence rate, high recurrent rate and need whole course medical management. Varied clinical symptoms and unclear pathogenesis cause a series of clinical problem, such as low diagnostic rate and low effective treatment rate. Based on neuroimmune mechanisms of MDD, our previous study indicates that kynurenine pathway (KP) in serum may be the connections between central immune and peripheral immune, that key factors of KP may change the brain structure and function through affecting the central immune. The core research issue of this project are the inherent associations between metabonomics of inflammatory factors in KP, clinical phenotypes of MDD, and neuroimaging features. This project will focus on first-episode MDD, mass spectrometry analysis of KP factors will be conducted first, also multi-modal neuroimaging techniques will be applied to detect topological characteristics of brain structure and function in MDD and extract standard models, then correlation analyses will be performed between these molecular biological features and multi-dimensional clinical data in order to integrate KP metabonomics, core clinical characteristics (depressed mood, energy loss, interest loss and so on), neuroimaging biomarkers, and finally construct the deep learning based standard diagnostic technique of MDD. Additionally, this project will follow up MDD patients with different core clinical characteristics to certificate the aforementioned diagnostic technique as well as explore optimized treatment for different clinical subtypes.
Background: Recent studies have suggested that gut-brain axis may be one of the mechanisms of major depression disorder. In animal studies, alteration of gut microbiota can affect animal's depression or anxiety-like behavior, brain neurochemistry and inflammation. In human studies, the composition of gut microbiota is different between patients with MDD and healthy controls. In addition, supplementation of probiotics can improve mood status in community and clinical participants. In preliminary open trial, the investigators found PS-128 can significantly reduce depression severity in patients with MDD. Therefore, the investigators would like to conduct an 8-week randomized, double-blind, placebo controlled trial of PS-128 in patients with MDD. Aims: This study will be an 8-week randomized, double-blind, placebo-controlled trial to investigate the effects of Lactobacillus plantarum PS128 on psychophysiology in patients with MDD. Method: This is a two-phase study. In the first phase, the investigators will recruited patients fulfilling the following inclusion criteria: Age 20-65; fulfill Diagnostic and Statistical Manual of Mental Disorders fifth version (DSM-V) criteria of major depressive episode in recent 2 years; Psychotropics including antidepressants, antipsychotics and hypnotics have been kept unchanged for at least 1 months. The exclusion criteria are: comorbid with schizophrenia, bipolar disorder, or other substance use (except tobacco) disorder; having active suicidal or homicidal ideation; known allergy to probiotics; comorbid with diabetes mellitus, irritable bowel syndrome, inflammatory bowl disease, liver cirrhosis, or autoimmune diseases; known active bacterial, fungal, or viral infections in one month; use of antibiotics, steroid, immunosuppressants, probiotics, or synbiotics in the month before collecting blood and fecal samples; pregnant or lactating women; who state to have dietary pattern changed or in diet within previous two months. Those with HAMD-17 >=14 in the first screen will be randomized to PS-128 or placebo, with the ratio of 1:1, in the second phase intervention. In the second phase intervention, the investigators will give eligible patients Lactobacillus plantarum PS128 or placebo for 8 weeks, and compare depression symptoms, gut microbiota, gut permeability, and serum inflammation level before and after intervention.
This is a research study to examine the effectiveness of a brief screening method that may predict which people with posttraumatic stress disorder (PTSD) or depression are most likely to show a positive response to selective serotonin reuptake inhibitor (SSRI) medications. Participants will be recruited over approximately 5.25 years, until at least 94 participants complete the 17 week study.
The diagnosis of major depression relies on patient reports, and two patients with the same diagnosis might share only one symptom. Thus, a single mechanism is unlikely to underlie a broad descriptive diagnosis such as major depression. Our approach is anchored by a neural circuit taxonomy that proposes distinct biotypes of depression derived from functional magnetic resonance imaging (fMRI) (Williams et al., 2016). In this study, we aim to target a putative type of major depression that arises from dysfunction in cognitive control neural circuitry with a drug called guanfacine.
Suicide accounts for at least 1 million deaths globally each year. This is likely a significant underestimate, because suicide is under-reported in many countries. In the US, over 42,000 people die from suicide annually. Despite increased focus on identification and treatment, the rate of suicide has increased steadily over the past 15 years. Our project aims both to improve our understanding of factors that increase the risk for suicide by comparing blood biomarkers associated with inflammation in patients with depression without suicidal behavior and patients with depression and suicidal behavior. The 160 individuals in this study will be followed with psychiatric assessments and blood samples at repeated time points over one year.
Targeted and individualized treatments for mental health disorders are critically needed. Repetitive transcranial magnetic stimulation (rTMS) represents the front-line of new and innovative approaches to normalizing dysfunctional brain networks in those with mental illness. rTMS is FDA-approved for depression and obsessive-compulsive disorder with clinical trials underway for PTSD and addiction, among others. However, remission rates are suboptimal and ideal stimulation parameters are unknown. We recently completed a randomized, double blind clinical trial and a depression severity biomarker that predicts clinical outcome. The overarching goal of this study is to develop the first broadly generalizable platform for real-time biomarker monitoring and personalized rTMS treatment. We plan to recruit patients with medication-resistant depression and in perform a four-phase, cross-over, double-blind, placebo-controlled trial to 1) identify how standard and optimized rTMS patterns engage the depression severity biomarker, and 2) determine the dose-response of these rTMS patterns. Findings from this study will provide the basis for a double-blind, randomized clinical trial comparing rTMS optimized to the individual against standard rTMS.