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Optimise and predict antidepressant efficacy for patient with major depressive disorders using multi-omics analysis and AI-predictive tool

Project description

DEENESFRITPL

Novel predictive tool to ensure antidepressant effectiveness

Major depressive disorders (MDD) affect 280 million people worldwide. Several antidepressants exist. However, very few patients (less than 6 %) benefit from therapeutic methods. The EU-funded OPADE project will identify critical biomarkers that support the decision-making process of healthcare providers by focusing on the microbiota–brain axis, which plays a central role in mental health and MDD. By studying genetics, epigenetics, microbiomes and inflammatory networks to establish patient profiles, the project will predict and optimise antidepressant efficacy. It will also investigate the possible correlation between neuroinflammatory indices, target indicators of the microbiome, metabolomics, immune profiling as well as epigenomic and enzymatic algorithms. The project will use the results and analysis to train the artificial intelligence and machine learning predictive tool.

Objective

280M of people worldwide suffers from major depressive disorders (MDD). Although a well-populated therapeutic landscape of anti-depre280M of people worldwide suffers from major depressive disorders (MDD). Although a well-populated therapeutic landscape of anti-depressants, the number of patients in remission is particularly low with not more than 6% of the patients who benefit from the current therapeutic journey.
OPADE objective is to identify key biomarkers that support the decision-making process of the healthcare providers.
The project focuses on the microbiota – brain -axis which plays a major role in mental health and in particular MDD. Through clinical investigations, the consortium partners will study the combination between genetics, epigenetics, microbiome and inflammatory networks to:
- Establish patient profiles to predict and optimise the efficacy of the antidepressants prescribed with an increase in the remission rate and reduction of impairment of real-life functioning,
- Establish the possible correlation between neuroinflammatory indices, target indicators of the microbiome, metabolomics, immune-profile linked, epigenomic, enzymatic algorithms,
- Evaluate molecular and non-molecular biomarkers that may represent predictive indices of recurrence
- Discover new molecular targets for a personalised approach,
- Improve the diagnostic accuracy for primary prevention,
- Evaluate retrospectively, using accurate anamnesis, the onset of depressive symptoms in adolescence.
- Establish how much and to what extent do blood biomarkers correlate with other specific biomarkers
350 patients between 14 and 50 years will be recruited in 6 EU and international countries for 24 months. Real-time EEG and patient cognitive assessment will be collected with blood, stool and saliva samples. Results and analysis will be used to train the AI / ML predictive tool, the main outcome of the project. A patient empowerment tool will be deployed over the project duration.

Fields of science

Programme(s)

Topic(s)

Call for proposal

HORIZON-HLTH-2022-TOOL-11

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Funding Scheme

RIA - Research and Innovation action

Coordinator

FONDAZIONE EBRIS
Net EU contribution
€ 1 615 625,00
Address
Via de renzi 1
84125 Salerno
Italy

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Region
Sud Campania Salerno
Activity type
Research Organisations
Links
Other funding
€ 0,00

Participants (13)

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Last update: 4 May 2023

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Permalink: https://cordis.europa.eu/project/id/101095436

European Union, 2023