Deep phenotyping as a contribution to personalized depression therapy: the GEParD and DaCFail protocols

Area of Science:

• Psychiatry and Clinical Psychology
• Cardiovascular Medicine
• Genetics and Epigenetics

Background:

• Depression presents with diverse symptoms and complex etiologies, leading to recurrent episodes in many patients.
• A significant portion (20-30%) of depressed individuals develop treatment-resistant depression.
• Understanding the interplay of genetic, epigenetic, and cardiovascular factors is crucial for personalized treatment.

Purpose of the Study:

• To describe the design of the GEParD and DaCFail protocols for investigating multimodal biomarkers in depression.
• To explore the utility of cardiovascular, genetic, and epigenetic markers in predicting antidepressant therapy response.
• To examine heart-brain interactions and stress systems in older adults with depression and/or heart failure.

Main Methods:

• Prospective, observational GEParD cohort recruited 346 depressed patients (2012-2020).
• Case-control DaCFail protocol (2016-2020) integrated four subgroups focusing on heart-brain interactions.
• Utilized comprehensive psychometry, cardiovascular and (epi-)genetic markers, and functional brain/heart imaging.

Main Results:

• Recruited 346 patients for GEParD and 120 depressed patients and 95 controls for DaCFail.
• DaCFail integrated subgroups focusing on depression with heart failure, and controls.
• Study design provides a roadmap for standardized, reproducible investigations in inpatient settings.

Conclusions:

• The GEParD and DaCFail protocols offer a framework for personalized antidepressant therapy research.
• Multimodal biomarkers, including cardiovascular and (epi-)genetic markers, are key to evaluating treatment response.
• Future multicenter studies can build upon this design, focusing on heart comorbidities in depression.