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Redefining schizophrenia treatment with muscarinic modulation-A perspective.
Eur Neuropsychopharmacol
December 2024
Department of Psychiatry, Student of Medicine, King Edward Medical University, Lahore, Pakistan. Electronic address:
DNA methylation and histone modifications associated with antipsychotic treatment: a systematic review.
Mol Psychiatry
January 2025
Department of Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Antipsychotic medications are essential when treating schizophrenia spectrum and other psychotic disorders, but the efficacy and tolerability of these medications vary from person to person. This interindividual variation is likely mediated, at least in part, by epigenomic processes that have yet to be fully elucidated. Herein, we systematically identified and evaluated 65 studies that examine the influence of antipsychotic drugs on epigenomic changes, including global methylation (9 studies), genome-wide methylation (22 studies), candidate gene methylation (16 studies), and histone modification (18 studies).
View Article and Find Full Text PDFThe status of MRI databases across the world focused on psychiatric and neurological disorders.
Psychiatry Clin Neurosci
October 2024
Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan.
Article Synopsis
- Neuroimaging databases for neuro-psychiatric disorders provide valuable data for researchers to explore diseases, develop machine learning models, and redefine understanding of these conditions.* ! -
- A review identified 42 global MRI datasets totaling 23,293 samples from patients with various disorders, including mood, developmental, schizophrenia, Parkinson's, and dementia.* ! -
- Improved governance and addressing technical issues of these databases are essential for sharing data across borders, aiding in understanding, diagnosing, and creating early interventions for neuro-psychiatric disorders.* !
Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm.
Nat Commun
July 2024
Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China.
Article Synopsis
- This study used machine learning to classify subtypes of schizophrenia by analyzing brain images from over 4,000 patients and healthy individuals through international collaboration.* -
- Researchers identified two neurostructural subgroups: one with predominant cortical loss and enlarged striatum, and another with significant subcortical loss in areas like the hippocampus and striatum.* -
- The findings suggest this new imaging-based classification could redefine schizophrenia based on biological similarities, enhancing our understanding and treatment of the disorder.*
Towards the DSM-6: Results of a Survey of Experts on the Reintroduction of First-Rank Symptoms as Core Criteria of Schizophrenia and on Redefining Hallucinations.
Schizophr Bull
August 2024
Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: Diagnostic criteria for mental disorders are subject to change. This is particularly true for schizophrenia, whose diagnostic criteria in the current DSM-5 bear little resemblance to what Kraepelin once named "dementia praecox" and Bleuler termed "the schizophrenias." The present study reports results from a survey of experts on two core topics of schizophrenia: (a) whether subsequent editions of the DSM should once again give the Schneiderian first-rank symptoms (FRS; eg, thought broadcasting) the prominent role they had in the DSM-IV and (b) whether the currently quite narrow definition of hallucinations in the DSM-5 requiring them to be vivid and clear and have the full force and impact of normal perceptions should be broadened to incorporate perceptual-like phenomena that the individual can differentiate from proper perceptions but still perceives as real and externally generated.
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