The multimodal Munich Clinical Deep Phenotyping study to bridge the translational gap in severe mental illness treatment research

Abstract

IntroductionTreatment of severe mental illness (SMI) symptoms, especially negative symptoms and cognitive dysfunction in schizophrenia, remains a major unmet need. There is good evidence that SMIs have a strong genetic background and are characterized by multiple biological alterations, including disturbed brain circuits and connectivity, dysregulated neuronal excitation-inhibition, disturbed dopaminergic and glutamatergic pathways, and partially dysregulated inflammatory processes. The ways in which the dysregulated signaling pathways are interconnected remains largely unknown, in part because well-characterized clinical studies on comprehensive biomaterial are lacking. Furthermore, the development of drugs to treat SMIs such as schizophrenia is limited by the use of operationalized symptom-based clusters for diagnosis.MethodsIn line with the Research Domain Criteria initiative, the Clinical Deep Phenotyping (CDP) study is using a multimodal approach to reveal the neurobiological underpinnings of clinically relevant schizophrenia subgroups by performing broad transdiagnostic clinical characterization with standardized neurocognitive assessments, multimodal neuroimaging, electrophysiological assessments, retinal investigations, and omics-based analyzes of blood and cerebrospinal fluid. Moreover, to bridge the translational gap in biological psychiatry the study includes in vitro investigations on human-induced pluripotent stem cells, which are available from a subset of participants.ResultsHere, we report on the feasibility of this multimodal approach, which has been successfully initiated in the first participants in the CDP cohort; to date, the cohort comprises over 194 individuals with SMI and 187 age and gender matched healthy controls. In addition, we describe the applied research modalities and study objectives.DiscussionThe identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive dysfunction, and treatment-resistant symptoms in general are still difficult to treat.

How to measure functional connectivity using resting-state fMRI? A comprehensive empirical exploration of different connectivity metrics

“…The current study was based on four independent datasets acquired at different sites. We analyzed behavioral and neuroimaging data from the Mind-Brain-Body dataset from the Max-Planck-Institute Leipzig in Germany (MBB, DOI:10.18112/openneuro.ds000221.v1.0.0) 32 , the Clinical Deep Phenotyping cohort from the Department of Psychiatry and Psychotherapy of the Ludwig-Maximilians-University Hospital Munich in Germany (CDP) 33 , the aging cohort of the Human Connectome Project (HCP-Aging) 34 , and from four patients with malignant tumors from the Brain Tumor Connectomics data from the Ghent University Hospital in Belgium (BTC, DOI:10.18112/openneuro.ds001226.v4.0.0) 35,36 . The CDP and MBB datasets were used to address the first aim of this study, namely to examine the impact of different FC metrics on several common FC-based outcomes in rs-fMRI research.…”

“…The imaging protocol of the CDP study was based on the HCP protoco 34 . It contained a T1-weighted magnetization-prepared rapid acquisition gradient echo (MP-RAGE) sequence, a T2-weighted sampling perfection with application-optimized contrasts using different flip angle evolution (T2-SPACE), a resting-state EPI sequence and a DWI sequence conducted at a Siemens 3T Magnetom Prisma scanner with a 32-channel head coil (for details see Krčmář et al 33 ). The HCP-Aging protocol comprised a T1-weighted MP-RAGE sequence, T2-weighted SPACE sequence, a restingstate EPI sequence, a DWI sequence, and a pseudo continuous Arterial Spin Labeling (PCASL) sequence acquired at a Siemens 3T Magnetom Prisma scanner with a 32-channel head coil.…”

Investigation of choroid plexus variability in schizophrenia-spectrum disorders – insights from a multimodal study

“…This project was carried out in the context of the Clinical Deep Phenotyping (CDP) study 31 , an ongoing add-on study to the Munich Mental Health Biobank (project number 18-716) 32 (German Clinical Trials Register, DRKS, ID: DRKS00024177) and approved by the ethics committee of the Faculty of Medicine, LMU University Hospital Munich (project numbers 20-0528 and 22-0035).…”

Elucidating salient site-specific functional connectivity features and site-invariant biomarkers in schizophrenia via deep neural networks

“…Schizophrenia is a chronic and debilitating mental illness affecting more than 27 million individuals worldwide 1 . The diagnosis and management of this condition has to take into account the significant heterogeneity in neurobiology 2 and clinical presentations 3 which are actively being investigated across sites and clinical settings 4 , 5 . The examination and discovery of biological factors including neuroimaging biomarkers that are generalisable across sites would promote a better understanding of this disorder and potentially allow for better predictive models, novel treatment targets and prognostication of this condition 6 – 8 .…”