Clinical Deep Phenotyping Study

Clinical Deep Phenotyping Study - CDP

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00024177

Enrollment

220

Registered

2021-01-27

Start date

2020-10-09

Completion date

Unknown

Last updated

2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

F20 F31 F32 F33 F10.5 F11.5 F12.5 F13.5 F14.5 F15.5 F16.5 F17.5 F18.5 F19.5 F21 F22 F23 F24 F25 F28

Interventions

Group 1: Patients that are affected with psychotic spectrum disorders (ICD-10: F2X.X) including drug induced psychosis (ICD-10: F1X.5), bipolar disorder (ICD-10: F31.X) and major depression (ICD-10: F

Eligibility

Sex/Gender

All

Age

18 Years to 65 Years

Inclusion criteria

Inclusion criteria: o Psychotic spectrum disorders (ICD-10: F2X.X) o Drug induced psychosis (ICD-10: F1X.5) o Bipolar disorder (ICD-10: F31.X) o Major depression (ICD-10: F32.X + F33.X) o Healthy controls as a control group o Age: =18 years and = 65 years

Exclusion criteria

Exclusion criteria: o Patients with a primary psychiatric diagnosis other than defined above o Age: 65 years o patients who are not suitable for the study in the opinion of the investigator o acutely suicidal patients o patients that are not able to provide informed consent

Design outcomes

Primary

Measure	Time frame
This study is a naturalistic cross-sectional study. Patients and controls will be characterized at one timepoint (inclusion to the CDP study) CDP aims to investigate wheter multivariate deep clinical characterization based on multimodal MRI, EEG, TMS, OCT, ERG and clinical and cognitive characteritics could be used to identifiy the distinct patient groups or subgroups of patients. Machine learning-based methods will be applied for this multivariate analyses.	—

Measure

Time frame

This study is a naturalistic cross-sectional study. Patients and controls will be characterized at one timepoint (inclusion to the CDP study) CDP aims to investigate wheter multivariate deep clinical characterization based on multimodal MRI, EEG, TMS, OCT, ERG and clinical and cognitive characteritics could be used to identifiy the distinct patient groups or subgroups of patients. Machine learning-based methods will be applied for this multivariate analyses.

—

Secondary

Measure	Time frame
- are the anatomical brain-based parmeters (multimodal MRI) associated with the retinal anatomy (OCT) in patients - are is the brain-based electrophysiology (EEG, TMS) associated with retinal electrophysiology (ERG) - are brain-based parameters associated with cogniton in patients / controls - are retina-based parameters associated with cognition (BACS) in patients / controls - can in vivo assed anatomical and functional features translated in hiPSC-derived test systems	—

Measure

Time frame

- are the anatomical brain-based parmeters (multimodal MRI) associated with the retinal anatomy (OCT) in patients - are is the brain-based electrophysiology (EEG, TMS) associated with retinal electrophysiology (ERG) - are brain-based parameters associated with cogniton in patients / controls - are retina-based parameters associated with cognition (BACS) in patients / controls - can in vivo assed anatomical and functional features translated in hiPSC-derived test systems

—

Countries

Germany

Contacts

Public ContactLenka Slapakova

Klinik für Psychiatrie und Psychotherapie, Klinikum der Universität München, LMU München

lenka.slapakova(at)med.uni-muenchen.de089440055505

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026