Research into Biomarkers of Electroconvulsive Therapy for Severe Depression

Understand mechanisms of ECT better

The DetECT study (“Multiomics and blood-based biomarkers of electroconvulsive therapy in severe and treatment-resistant depression”), which is running since 2022, explores how biological signatures in the blood can help predict treatment outcomes in patients undergoing electroconvulsive therapy (ECT). ECT remains one of the most effective interventions for individuals with severe, treatment-resistant depression (TRD), yet its use is often limited by uncertainty regarding individual response. DetECT addresses this gap by investigating whether molecular biomarkers - measurable in peripheral blood - can forecast how a patient will respond to ECT, or help track treatment progress more objectively.

The study follows a longitudinal, observational design and includes patients diagnosed with severe withdepression who meet established criteria for treatment resistance. These individuals receive ECT as part of their clinical care, and biological samples are collected at several time points: before treatment, during the course, and after completion. The collected blood samples are analyzed using a comprehensive multiomics approach, including genomics, epigenomics, transcriptomics, and proteomics. In addition to biological data, patients are assessed using validated clinical self- and foreign-rating instruments such as the PHQ-9 for depressive symptoms, the PHQ-15 for somatic complaints, along with self-report tools for neurocognitive functioning as well as the MADRS, HAM-D21, HAM-A, and GAF.

The overarching goal is to identify patterns within this high-dimensional dataset that correlate with clinical improvement or non-response. By integrating molecular data with clinical phenotyping, DetECT aims to discover reliable, blood-based biomarkers that reflect the underlying mechanisms of ECT and provide predictive value for treatment planning.

This research is highly relevant in the context of a growing shift toward personalized medicine in psychiatry. As depression is a heterogeneous disorder, biomarker-based stratification could help clinicians tailor interventions more effectively. DetECT contributes to this vision by offering a model for how complex biological data can be linked to real-world treatment outcomes. If successful, the study could support more targeted use of ECT, reduce reliance on trial-and-error approaches, and ultimately improve care for patients with the most challenging forms of depression.