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Circulating Extracellular Vesicles as Predictors of Antidepressant Response: Monitoring the Mechanism of Novel Therapeutic Approaches in Depression

Project type
Znanstveno-istraživački projekti
Slovenian-Croatian Bilateral Projects
Croatian Science Foundation
Start date
Dec 1st 2022
End date
Nov 30th 2025
Total cost
155285 EUR
More information

EVroPAR is a Slovenian-Croatian multidisciplinary research project which combines basic, preclinical and clinical research, including partners from Ruđer Bošković Institute (Croatia), Institute of Biochemistry (Faculty of Medicine in Ljubljana, Slovenia), University Foundation San Pablo CEU (Spain), University Hospital Centre Zagreb (Croatia), University Psychiatric Clinic Ljubljana (Slovenia) and Labena d.o.o. (Slovenia). Project incorporates cutting-edge metabolomics approach and miRNA profiling in order to identify novel biomarkers that could help clinicians to tailor treatment strategies in depression for individual patients. Currently available therapy for depression involves pharmacotherapy combined with psychotherapy, while dealing with poor response/nonresponse and a frequent discontinuation of treatment. The objective of the study is to give better insights into the efficacy and molecular mechanisms behind the effects of a widely used antidepressant (duloxetine), and compare this to the mechanism behind the effects of alternative methods of treatment in patients with treatment-resistant depression (transcranial magnetic stimulation (TMS), phototherapy (bright light therapy, BTL), esketamine treatment). The study will focus on circulating extracellular vesicles (EVs) as easily obtainable and non-invasive biomarkers. We aim to measure the dysregulation of epigenetic markers, the EV miRNA expression, and to determine metabolic alterations in four groups of patients (duloxetine vs. BLT vs. TMS vs. esketamine), by sampling 50 patients per group before and after the treatment. Another goal is to identify specific metabolic and miRNA signatures of depression by comparing patients with an appropriate control group (100 subjects). We expect that new biomarkers identified in this project will help determine treatment efficiency in depression and predict good/poor response to treatment, as a key step towards the inevitable personalized and effective medicine approach.

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