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.
Eligibility
Sex
ALL
Min age
14 Years
Max age
50 Years
Healthy volunteers
No
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.
Primary outcome measure(s)
Identify neuroinflammatory indices — 2 years 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.
Microbiome analysis — 2 years Identification of bacterial and fungal components.
Metabolomic analysis — 2 years 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.
Analysis of lipoprotein profile — 2 years 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.
Identify immune-profile linked and epigenomic signatures — 2 years Methylome analysis on genomic DNA will be performed.
AI-powered diagnostics predictive tool (companion diagnostic-like) — 2 years 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.
Mood assessment through brain biomarker — 2 years Validate a patient tracking tool for mood assessment using brain biomarker.
Patient engagement digital tool — 2 years Validate a patient engagement digital tool that can be deployed in any patient community to enhance clinical study outcomes.
Discovery of a new set of biomarkers — 2 years Propose new set of biomarkers that can guide the development of new antidepressants
Investigation of the gut-brain-axis and of the biomarkers of interest in the context of mental diseases starting with MDD — 2 years Identify indices in MDD to improve diagnostic accuracy for primary prevention and patients' stratification.
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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