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Clinical deep phenotyping of treatment response in schizophrenia (CDP-STAR): design and methodology of a prospective multimodal observational study

  • Schizophrenia spectrum disorders (SSDs) exhibit a marked heterogeneity in clinical course and treatment outcomes. Some individuals achieve remission and recovery, whereas others experience repeated relapses and progressive deterioration in psychosocial functioning. This variability underscores the unmet clinical need for prognostic biomarkers to predict treatment outcomes and guide personalized care. Deep phenotyping with multimodal data integration holds promise for understanding this complexity and delivering clinically relevant predictive models of treatment response in SSDs. To address this need, we initiated the Clinical Deep Phenotyping of Treatment Response in Schizophrenia (CDP-STAR) study, a prospective, naturalistic, longitudinal observational study integrating comprehensive multimodal assessments. These include clinical phenotyping, magnetic resonance imaging (MRI), electroencephalography (EEG), retinal imaging, and extensive sampling of blood and cerebrospinal fluid (CSF)Schizophrenia spectrum disorders (SSDs) exhibit a marked heterogeneity in clinical course and treatment outcomes. Some individuals achieve remission and recovery, whereas others experience repeated relapses and progressive deterioration in psychosocial functioning. This variability underscores the unmet clinical need for prognostic biomarkers to predict treatment outcomes and guide personalized care. Deep phenotyping with multimodal data integration holds promise for understanding this complexity and delivering clinically relevant predictive models of treatment response in SSDs. To address this need, we initiated the Clinical Deep Phenotyping of Treatment Response in Schizophrenia (CDP-STAR) study, a prospective, naturalistic, longitudinal observational study integrating comprehensive multimodal assessments. These include clinical phenotyping, magnetic resonance imaging (MRI), electroencephalography (EEG), retinal imaging, and extensive sampling of blood and cerebrospinal fluid (CSF) for multi-omics profiling. The study aims to externally validate promising biomarker candidates and elucidate the pathophysiological mechanisms underlying treatment outcomes. This innovative deep phenotyping framework integrates data across multiple critical domains, enabling external validation of potential biomarkers and the discovery of novel ones. Ultimately, the CDP-STAR study aims to yield mechanistic insights that advance precision psychiatry and inform clinical decision-making in SSDs.show moreshow less

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Metadaten
Author:Vladislav Yakimov, Lara Neuwinger, Madeleine M. Weber, Maximilian Brantl, Isabel Maurus, Jana Sautner, Miriam John, Berkhan Karslı, Genc Hasanaj, Anne Bungard, Alkomiet HasanORCiDGND, Elias WagnerORCiDGND, Laura Fischer, Paula Steiner, Benedikt Schworm, Siegfried Priglinger, Sergi Papiol, Peter Falkai, Andrea Schmitt, Florian J. Raabe, Daniel Keeser, Lukas Roell, Joanna Moussiopoulou, Emanuel Boudriot
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/125446
ISSN:0940-1334OPAC
ISSN:1433-8491OPAC
Parent Title (English):European Archives of Psychiatry and Clinical Neuroscience
Publisher:Springer Science and Business Media LLC
Place of publication:Berlin
Type:Article
Language:English
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2025/09/23
Note:
Full author list includes the CDP-Working Group. Please see publisher's website for further details.
DOI:https://doi.org/10.1007/s00406-025-02100-1
Institutes:Medizinische Fakultät
Medizinische Fakultät / Lehrstuhl für Psychiatrie und Psychotherapie
Medizinische Fakultät / Bezirkskrankenhaus (BKH)
Medizinische Fakultät / Professur für Evidenzbasierte Psychiatrie und Psychotherapie
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Latest Publications (not yet published in print):Aktuelle Publikationen (noch nicht gedruckt erschienen)
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)