Optimize and Predict Antidepressant Efficacy for Patient With MDD Using Multi-omics Analysis and AI-predictive Tool (OPADE)

Optimize and Predict Antidepressant Efficacy for Patient With Major Depressive Disorders Using Multi-omics Analysis and AI-predictive Tool

OPADE is a non-profit, observational, multicenter, open-label study aimed at defining personalized treatment for Major Depressive Disorder (MDD). In particular, we will combine genetics, epigenetics, microbiome, immune response data together with anamnesis, questionnaires, electroencephalography (EEG) collected from subjects suffering MDD. Eventually, an Artificial Intelligence (AI)/Machine Learning (ML) predictive tool will be created to guide clinicians in improving MDD treatment and patient's stratification.

Study Overview

• Status: Active, not recruiting
• Conditions: Major Depressive Disorder

Detailed Description

Three hundred and fifty patients diagnosed with MDD will be enrolled for 24 months and divided into 4 groups according to age: 14-17 years (70 pediatric patients), 18-30 years (100 adult patients), 31-39 years (90 adult patients), 40-50 years (90 adult patients).

The study protocol includes 6 follow-up visits: T0 (enrollment), T1, T2, T3, T4, and T5. At each medical visit, psychometric questionnaires will be administered to the patients and contextual biological samples including blood, stool and saliva will be collected. The study will use a multi-omics approach including: metagenomic sequencing to characterize the microbiome composition; metabolomics to detect circulating metabolites; transcriptomics to quantify microRNAs; epigenomics to assess methylation variability between and within groups and immune assays to analyze the antibody immune response and inflammatory profiles (cytokines, interleukins and growth factors). Cortisol and lipoproteins will also be quantified. In parallel, cognitive assessment and emotional status will be recorded remotely by each patient via chatbot and wearable EEG devices, respectively. Specifically, the chatbot will collect patient's conversations and monitoring her/his feelings; the chat conversation will be than transformed in a machine-readable data. The EEG device is a mobile app that will also allows to associate brainwaves with patients' feelings.

• Study Type: Observational
• Enrollment (Estimated): 350

Contacts and Locations

Study Locations

• Italy
  • Siena, Italy, 53100
    • Università degli Studi di Siena

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Patients with Major Depressive Disorders

Description

Inclusion Criteria:

• Patients diagnosed with Major Depressive Disorder as certified by a SCID 5 (Structured Clinical Interview for DSM-5) for DSM-S for adults and K-SADS-PL-DSM 5 (Kiddie Schedule for Affective Disorders and Schizophrenia - Present and Lifetime for DSM 5) for adolescents.
• Currently experiencing a major depressive episode with a HAM-D (Hamilton Depression) score of 18 or greater, or alternatively, a MADRS (Montgomery-Asberg Depression Rating Scale) score of 18 or greater.
• About to start a new antidepressant.
• Not concurrently starting a new psychotropic medication.
• Age 14-50 years.
• Able to use mobile devices (smart phone, tablet).
• Willingness to provide written informed consent to participate.

Exclusion Criteria:

• Intellectual disability.
• Neurological disease (multiple sclerosis, severe neurocognitive disorder, epilepsy).
• Current psychotic disorder or mood disorder with psychotic features.
• Primary diagnosis of alcohol or substance use disorder (DSM-5).
• Patients who started concomitant psychotropic medications less than one week ago.
• Active, ongoing inflammatory diseases (such as rheumatoid arthritis and rheumatic polymyalgia). or severe and unstable physical illness (such as recent myocardial infarction).
• A history of hepatitis B or C, human immunodeficiency virus, or evidence of active tuberculosis infection or any active systemic infection within 2 weeks prior to the start of the study.
• Use of antibiotics or other medications that may have affected the composition of the microbiota during the 30 days prior to baseline.
• Pregnancy and lactation.

Study Plan

How is the study designed?

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort
Pediatric patients affected by MDD; 14-17 years (70 pediatric patients)
Group 1 of adult patients affected by MDD; 18-30 years (100 adult patients)
Group 2 of adult patients affected by MDD; 31-39 years (90 adult patients)
Group 3 of adult patients affected by MDD; 40-50 years (90 adult patients)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identify neuroinflammatory indices	Several inflammatory markers such as G-CSF, GM-CSF, IFN-γ IL-10, IL-12p40, IL-15, IL-1α, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8/CXCL8, MCP-1/CCL2, TNF-α, TNFβ will be analysed.	2 years
Microbiome analysis	Identification of bacterial and fungal components.	2 years
Metabolomic analysis	The metabolomic analysis will involve three different groups of metabolites: 1) Intermediate of tryptophan metabolism (tryptophan, serotonin, 5-HIAA, quinurenin, quinurenic acid and other hormones and derivatives involved in the pathway) and others related to purines (paraxanthin/xanthin ratio); 2) L-acylcarnitines (including short chain, medium long-lasting acylcarnitine), with particular emphasis on laurylcarnitine and acetylcarnitine; 3) Phenolic (and related), such as phenolic acid, mandelic acid or methoxy-hydroxyphenyl glycol.	2 years
Analysis of lipoprotein profile	Different forms of lipoproteins will be evaluated: Apolipoproteins A1 and A2, HDL-apolipoproteins A1 and A2,free cholesterol HDL3, HDL3-apolipoprotein A1, HDL2-apolipoprotein A2, apolipoprotein A2, IDL, HDL-apolipoprotein A2, VLDL and its subtypes, VLDL2-triglycerides, VLDL3-triglyceridestriglycerides, VLDL2- cholesterol, VLDL3 cholesterol, VLDL4 cholesterol free of VLDL4, phospholipids VLDL2, Phospholipids VLDL3, Cholesterol LDL5, Cholesterol free LDL5, Phospholipids LDL5, LDL5-apolipoprotein B, HDL3 cholesterol, HDL4 cholesterol HDL4, HDL3 cholesterol free, free cholesterol HDL4, HDL3-phospholipids, HDL4-phospholipids, HDL3-apolipoprotein A1, HDL4-apolipoprotein A1, HDL3-apolipoprotein A2 and HDL4-apolipoprotein A2.	2 years
Identify immune-profile linked and epigenomic signatures	Methylome analysis on genomic DNA will be performed.	2 years
Mood assessment through brain biomarker	Validate a patient tracking tool for mood assessment using brain biomarker.	2 years
Patient engagement digital tool	Validate a patient engagement digital tool that can be deployed in any patient community to enhance clinical study outcomes.	2 years
Discovery of a new set of biomarkers	Propose new set of biomarkers that can guide the development of new antidepressants	2 years
Investigation of the gut-brain-axis and of the biomarkers of interest in the context of mental diseases starting with MDD	Identify indices in MDD to improve diagnostic accuracy for primary prevention and patients' stratification.	2 years
AI-powered diagnostics predictive tool (companion diagnostic-like)	Deploy an AI-powered predictive tool (companion diagnostic-like) in clinical practice for the prescription of anti-depressants. OPADE AI-powered predictive tool will be a class C medical device under the In vitro diagnostic classification.	2 years

Collaborators and Investigators

• Sponsor: Alessio Fasano
• Collaborators: Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta; Istanbul Medipol University Hospital; University of Siena; Fundació Eurecat; Accare; Sanitas University; Perseus Biomics; ARTIFICIAL INTELLIGENCE EXPERT SRL; Mama Health Technologies GmbH; Protobios OU; Cephalgo; Biokeralty Research Institute; CEINGE; Fondazione di ricerca biomedica EBRIS

Publications and helpful links

Helpful Links

• OPADE Official Website

Study record dates

Study Major Dates

• Study Start (Actual): August 7, 2023
• Primary Completion (Estimated): April 1, 2027
• Study Completion (Estimated): May 31, 2027

Study Registration Dates

• First Submitted: July 24, 2024
• First Submitted That Met QC Criteria: August 9, 2024
• First Posted (Actual): August 12, 2024

Study Record Updates

• Last Update Posted (Actual): May 15, 2026
• Last Update Submitted That Met QC Criteria: May 13, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: Genetics; Inflammation; Microbiome; Biomarkers; Personalized medicine; Artificial intelligence; Electroencephalography; Metabolomic; Transcriptomics; Machine learning; Chatbot; Major Depressive Disorders; Immune response profiling
• Additional Relevant MeSH Terms: Mental Disorders; Pathologic Processes; Mood Disorders; Depressive Disorder; Pathological Conditions, Signs and Symptoms; Inflammation; Depressive Disorder, Major
• Other Study ID Numbers: Pro23479

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No