Active clinical trials for "Mental Disorders"

BBB dysfunction has been indicated in some groups of schizophrenia patients by measuring increased albumin and immunoglobulin (IgG) cerebrospinal fluid (CSF) levels. Most of the authors described a raised protein level in 5-20% of the schizophrenic patients (Muller & Ackenheil, 1995). Increased S100B levels were demonstrated in the serum of patients suffering from schizophrenia as well as depression, and this may reflect increased BBB permeability. Furthermore, this increase remains in those patients who develop a residual state with relevant negative symptoms, whereas S100B levels normalize in recovering patients (Shalev, Serlin & Friedman, 2009). CSF albumin and CSF IgG values correlate significantly with some of the SANS (Scale for the Assessment of Negative Symptoms) subscales and the SANS total score, this shows the correlation between BBB permeability and behavioral changes. It is important to say that although negative symptoms are often signs of chronicity of the disease, the abnormal CSF findings in Muller's experiment (1995) are not related to the duration of the disease, because the patients were quite young and the duration of the disease was less than 3 years. The investigators hypothesize that a primary vascular pathology, which leads to BBB breakdown, will result a leakage of serum-derived vascular components in to the brain tissue and may cause brain dysfunction such as disturbed thinking processes, mood and behavior, as we can see in psychiatric patients.

Psychiatric patients under the mental impaired influences, their living function were disabled, and their social lives were handicapped consequently. Idea psychiatric treatment is to control the psychiatric symptoms in a better way, to develop efficient psychiatric adjustment, to manage living stress into a lower level, to gradually develop the meaning and value of the patients' lives, and to obtain the satisfaction and happiness in life for them. In order to investigate the satisfaction for psychiatric patients under the current treatment and to evaluate their psychiatric health, it is necessary to measure the mental health status for the psychiatric patients, and to ensure the ideological status of psychiatric treatment. If there is a mental health measurement for the psychiatric patients, we may precisely identify the mental health levels of the patients and their mental disturbances degrees. Accordingly, we may develop efficient procedure to manage the mental health for the psychiatric patients, and to achieve the goal for the idea psychiatric treatment. In this study, we established the mental health assessment data sheet according to the clinical experiences. It includes mental health index data sheet, mental-and-physical stress response data sheet, mental sustentation data sheet, and supplemented with a general living satisfaction assessment data sheet. We will evaluate the reliability and validity of this study to ensure the usability of these data sheet in clinics. We will also recruit the continuous treated and mentally stabilized patients as subjects. After obtaining their written informed consents, we will go through these mental health assessments to discover the mental health status of these psychiatric patients, and use it as a reference to develop idea psychiatric treatment. We will use ICC test for the repeated measurement validity, Pearson r correlation coefficient within our data analyses to evaluate the validity of the same measurement, and independent t-test to assess the differences between the patient group and the society group (from previously established data files). This study result may evaluate the possible deficits existing in the traditional psychiatric treatment and may be used as a reference for the development of idea psychiatric medicine.

The project will focus on the major technical difficulty of "lack of effective nutritional intervention measures for early risk of common mental diseases in China", and rely on the platform of psychiatric risk identification and treatment specialty of Shanghai Mental Health Center, an authoritative institution in the field of mental health, and focus on the effective application of the domestic independent research and development of the artificial intelligence nicotinic acid skin flushing reaction quantification instrument.

This study is a prospective study with a mean of 7-year follow-up interval, aims to monitor the progression of α-synucleinopathy neurodegeneration by the evolution of prodromal markers and development of clinical disorders in patients with idiopathic REM Sleep Behavior Disorder (iRBD) and healthy controls.

To contribute to improving the level of functioning and quality of life and mental health outcomes for people with severe and enduring mental ill health (SMI) (schizophrenia, bipolar disorder, depression) by adapting and up scaling the implementation of a community-based service delivery model in Croatia.

Schizophrenia is a chronic brain disease that is still understood as a condition that limits the development of a normal life for the patient who suffers it and their families. The idea that only one third of patients have a good outcome is still in force, despite the lack of clinical and epidemiological longitudinal studies that have addressed this issue rigorously. Most studies that have established the poor prognosis of the disease have followed a cross-sectional design and are based on samples of patients undergoing treatment in healthcare devices and therefore represents an important bias. Based on clinical, cognitive, functional outcome and biomarkers studies (brain imaging) to medium term (3 years) we can establish that the particular idea of poor prognosis should be reconsidered. The development of longitudinal studies of first-episode patients in representative samples of a population and long-term it is of high value to shed light on the clinical course of the disease. The belief that there are factors determining the disease progression beyond the initial three years brings us to publish this study. Given this background, our project's main objective is to know the evolution at 10 years of patients followed in the First Episode Psychosis Clinical Program (PAFIP). Our hypothesis is that a higher percentage of expected patients have a favorable outcome of the disease. Factors such as enhancing treatment completion, abstinence from drug use, return to work, the reduction of expressed emotion in families during the early years of the disease (at least 3 years of intensive intervention PAFIP) will have a positive impact on the evolution of patients on long-term (10 years). Our hypothesis defends the existence of certain factors as independent risk factors for poor clinical and functional outcome of patients who should be known for establishing intervention strategies that attempt to mitigate their impact on the quality of life of patients and their families.

There is growing evidence of high rates of substance use disorders among individuals with psychotic disorders especially in young people with predisposition for psychosis. There is some genetic evidence that carriers of the valine158 allele of the catechol-O-methyltransferase (COMT) gene had increased risk to exhibit psychotic symptoms and to develop schizophrenia if they used cannabis by the age of 18. It was also shown that carriers of the COMT val/val genotype were most sensitive to THC-induced psychotic experiences but this was conditional on pre-existing susceptibility to psychosis. The investigators propose to use brain-imaging and molecular genetics to investigate whether genetic factors may contribute to the THC-induced dopamine release and possibly to cannabis- induced psychosis.

Bipolar disorder is a chronic and frequent mood pathology, that impacts on emotional and socio-professional life of sick subjects, and also increase mortality by suicide. Suicide is considered as a bipolar disorder result. The main goal of this study is the endophenotype characterization from a clinical and cognitive point of view, of a bipolar spectrum's disorder present in a family, and then highlight a mutation of one of the genes involved is this disorder.

This protocol aims to develop the use of behavioral and electroencephalographic measures during cognitive tasks in patients treated with deep brain stimulation during the stimulation parameters adjustments. The main clinical goal of this protocol is to find behavioral and or electroencephalographic markers to evaluates the right targeting of stimulation electrodes. On the more fundamental point of view, the study of those data can be used to understand better the action mechanisms of deep brain stimulation.

A burgeoning body of research has pointed to increased efficacy of clozapine (CLZ) over other antipsychotics in schizophrenia (SCZ). On the other hand, safety concerns likely cause underutilization across a range of European and other nations. The lack of data available to predict efficacy and adverse drug reactions (ADRs) of CLZ further contributes to underprescription rates in these countries. Here, we hypothesize that (epi)genetic and non-genetic factors aid to help predict treatment outcome (efficacy + ADRs) to CLZ. We furthermore posit that such prediction will result in enhanced quality of life of both patients and family members. Our primary objective is to predict CLZ treatment outcome based on phenotypic and genetic data obtained through the current design. The first secondary objective is to investigate which methylation levels/patterns are correlated with CLZ treatment outcome. The second secondary objective is to aid in the further elucidation of the genetic architecture of SCZ and any possible differences between 'regular' SCZ patients and those on CLZ, who are generally more severely ill. We thus intend to cover two currently unmet needs using a precision medicine approach: the lack of knowledge about determinants of treatment response to CLZ and the lack of insight into neurobiological differences between 'regular' SCZ and relatively treatment resistant subjects (CLZ users). The prime analysis will be a common variant hypothesis-generating genotyping endeavor investigating treatment response to CLZ. Additional analyses include whole-genome methylation and gene expression analyses and analyses of non-genetic determinants of response. We will include 2,500 CLZ treated patients for our discovery cohort, which is in line with previous whole-genome pharmacogenomics studies and our power calculations. We will replicate any genome-wide loci using our prospectively collected cohort of new users (N=59). Potential yields include a publicly available prediction tool to help identify patients responsive to CLZ in early disease stages and prevent harmful effects. In addition, common variant analyses compounded by pathway analyses may help elucidate the mechanisms of action of CLZ. We ask for broad informed consent from participants ensuring rich, longitudinal phenotypic and genotypic data resources for both currently planned and future analyses, allowing e.g. next-generation sequencing focused on both CLZ and SCZ disease genetics (e.g. in large consortia). We plan to also generate polygenic risk scores (PRS) of CLZ efficacy and use those to identify other diseases or patients for which CLZ may be helpful, e.g. schizoaffective disorder patients who are sometimes first treated with mood stabilizers. Last, evidence hints that disparaging genetic loci influence efficacy to different antipsychotics. Adding genetic data from our cohort to existing datasets of response to other antipsychotics may help identify such loci. Finally, comparison studies with non-CLZ using patients suffering from SCZ may deepen the understanding of biological mechanisms underlying treatment resistance (or: a relatively severe course of illness).The results of this genetic part of the study will be combined with the results from our other research protocol 'Phenomics and genomic of clozapine pharmacotherapy - New Users'.The overarching goal of both projects is to create a prediction model for clozapine outcome (response (and side effects). This model includes genetic, epigenetic and clinical data.