28 research outputs found

    Abnormalities in one-carbon metabolism in young patients with psychosis

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    International audienceIntroduction: Folates, the main actors in one-carbon (C1) metabolism, are involved in synthesising monoamines and maintaining genomic stability. Previous studies support the association between C1 metabolism and schizophrenia. The main purpose of this study was to assess the prevalence of plasma folate, and/or vitamin B12 deficiencies and hyperhomocysteinemia in young patients with psychotic disorders. Methods: We included young inpatients (15–30 years old) with psychosis between 2014 and 2017 from Sainte-Anne Hospital in Paris. Plasma folate, vitamin B12 deficiency and homocysteinemia dosages were done at admission. Clinical data were extracted retrospectively, and patients diagnosed with a first-episode psychosis (FEP), schizophrenia, schizoaffective disorder, or persistent delusional disorder were retained for the analysis. Results: Among the 334 inpatients, 188 (56%) had C1 dosages available (135 males; 53 females). From the 188 patients, 32% had a C1 abnormality. This abnormality reached 38% of FEP patients. The most frequent abnormality was folate deficiency: 21% of all patients and 27% of FEP. Lower levels of folates were found in males compared to females (p = 0.02) and were correlated with more severe disorder, as assessed by Clinical Global Impression – Severity (CGI-S; p = 0.009). Antipsychotic dosage was positively associated with B12 levels (p = 0.013) and negatively with homocysteinemia (p = 0.034). Conclusion: One-carbon metabolism anomalies in young patients with psychotic disorders are highly prevalent, reaching almost half of the patients with FEP. Potential protective effects from females and antipsychotics have emerged. These results spotlight the need for new therapeutic prospects, such as folate supplementation, to achieve personalised medical approaches to the early stages of psychotic disorders. Copyrigh

    Persistent Depersonalization/Derealization Disorder Induced by Synthetic Cannabinoids

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    Toi Même, a Mobile Health Platform for Measuring Bipolar Illness Activity: Protocol for a Feasibility Study

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    International audienceBackground The diagnosis and management of bipolar disorder are limited by the absence of available biomarkers. Patients with bipolar disorder frequently present with mood instability even during remission, which is likely associated with the risk of relapse, impaired functioning, and suicidal behavior, indicating that the illness is active. Objective This research protocol aimed to investigate the correlations between clinically rated mood symptoms and mood/behavioral data automatically collected using the Toi Même app in patients with bipolar disorder presenting with different mood episodes. This study also aimed to assess the feasibility of this app for self-monitoring subjective and objective mood/behavior parameters in those patients. Methods This open-label, nonrandomized trial will enroll 93 (31 depressive, 31 euthymic, and 31 hypomanic) adults diagnosed with bipolar disorder type I/II (Diagnostic and Statistical Manual of Mental Disorders, 5th edition criteria) and owning an iPhone. Clinical evaluations will be performed by psychiatrists at the baseline and after 2 weeks, 1 month, 2 months, and 3 months during the follow-up. Rather than only accessing the daily mood symptoms, the Toi Même app also integrates ecological momentary assessments through 2 gamified tests to assess cognition speed (QUiCKBRAIN) and affective responses (PLAYiMOTIONS) in real-life contexts, continuously measures daily motor activities (eg, number of steps, distance) using the smartphone’s motion sensors, and performs a comprehensive weekly assessment. Results Recruitment began in April 2018 and the completion of the study is estimated to be in December 2021. As of April 2019, 25 participants were enrolled in the study. The first results are expected to be submitted for publication in 2020. This project has been funded by the Perception and Memory Unit of the Pasteur Institute (Paris) and it has received the final ethical/research approvals in April 2018 (ID-RCB: 2017-A02450-53). Conclusions Our results will add to the evidence of exploring other alternatives toward a more integrated approach in the management of bipolar disorder, including digital phenotyping, to develop an ethical and clinically meaningful framework for investigating, diagnosing, and treating individuals at risk of developing bipolar disorder or currently experiencing bipolar disorder. Further prospective studies on the validity of automatically generated smartphone data are needed for better understanding the longitudinal pattern of mood instability in bipolar disorder as well as to establish the reliability, efficacy, and cost-effectiveness of such an app intervention for patients with bipolar disorder. Trial Registration ClinicalTrials.gov NCT03508427; https://clinicaltrials.gov/ct2/show/NCT03508427 International Registered Report Identifier (IRRID) DERR1-10.2196/1881

    Discriminative Network Models of Schizophrenia

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    International audienceSchizophrenia is a complex psychiatric disorder that has eluded a characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, "emergent" working of the brain. We propose a novel data-driven approach to capture emergent features using functional brain networks [4] extracted from fMRI data, and demonstrate its advantage over traditional region-of-interest (ROI) and local, task-specific linear activation analyzes. Our results suggest that schizophrenia is indeed associated with disruption of global brain properties related to its functioning as a network, which cannot be explained by alteration of local activation patterns. Moreover, further exploitation of interactions by sparse Markov Random Field classifiers shows clear gain over linear methods, such as Gaussian Naive Bayes and SVM, allowing to reach 86% accuracy (over 50% baseline- random guess), which is quite remarkable given that it is based on a single fMRI experiment using a simple auditory task

    Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations

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    <div><p>Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, “emergent” working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophrenic brain display disrupted topological properties. However, is it possible to explain such abnormalities just by alteration of local activation patterns? This work suggests a negative answer to this question, demonstrating that significant disruption of the topological and spatial structure of functional MRI networks in schizophrenia (a) cannot be explained by a disruption to area-based task-dependent responses, i.e. indeed relates to the emergent properties, (b) is global in nature, affecting most dramatically long-distance correlations, and (c) can be leveraged to achieve high classification accuracy (93%) when discriminating between schizophrenic vs control subjects based just on a single fMRI experiment using a simple auditory task. While the prior work on schizophrenia networks has been primarily focused on discovering statistically significant differences in network properties, this work extends the prior art by exploring the generalization (prediction) ability of network models for schizophrenia, which is not necessarily captured by such significance tests.</p></div

    Examining transcranial random noise stimulation as an add-on treatment for persistent symptoms in schizophrenia (STIM’Zo): a study protocol for a multicentre, double-blind, randomized sham-controlled clinical trial

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    International audienceBackground: One out of three patients with schizophrenia failed to respond adequately to antipsychotics and continue to experience debilitating symptoms such as auditory hallucinations and negative symptoms. The development of additional therapeutic approaches for these persistent symptoms constitutes a major goal for patients. Here, we develop a randomized-controlled trial testing the efficacy of high-frequency transcranial random noise stimulation (hf-tRNS) for the treatment of resistant/persistent symptoms of schizophrenia in patients with various profiles of symptoms, cognitive deficits and illness duration. We also aim to investigate the biological and cognitive effects of hf-tRNS and to identify the predictors of clinical response. Methods: In a randomized, double-blind, 2-arm parallel-group, controlled, multicentre study, 144 patients with schizophrenia and persistent symptoms despite the prescription of at least one antipsychotic treatment will be randomly allocated to receive either active (n = 72) or sham (n = 72) hf-tRNS. hf-tRNS (100-500 Hz) will be delivered for 20 min with a current intensity of 2 mA and a 1-mA offset twice a day on 5 consecutive weekdays. The anode will be placed over the left dorsolateral prefrontal cortex and the cathode over the left temporoparietal junction. Patients' symptoms will be assessed prior to hf-tRNS (baseline), after the 10 sessions, and at 1-, 3-and 6-month follow-up. The primary outcome will be the number of responders defined as a reduction of at least 25% from the baseline scores on the Positive and Negative Syndrome Scale (PANSS) after the 10 sessions. Secondary outcome
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