Clinical trial NCT06550037: Optimize and Predict Antidepressant Efficacy for Patient With MDD Using Multi-omics Analysis and AI-predictive Tool
Official title: Optimize and Predict Antidepressant Efficacy for Patient With Major Depressive Disorders Using Multi-omics Analysis and AI-predictive Tool
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Major Depressive Disorder
Keywords: Major Depressive Disorders
Microbiome
Metabolomic
Transcriptomics
Inflammation
Immune response profiling
Genetics
Artificial intelligence
Machine learning
Electroencephalography
Chatbot
Biomarkers
Personalized medicine
Lead sponsor: Massachusetts General Hospital
Sponsor class: OTHER
Collaborators: name: University of Siena
name: Fundació Eurecat
name: Perseus Biomics
name: ARTIFICIAL INTELLIGENCE EXPERT SRL
name: Mama Health Technologies GmbH
name: Protobios OU
name: Cephalgo
name: Biokeralty Research Institute
name: Sanitas University
name: Accare
name: Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
name: Istanbul Medipol University Hospital
name: CEINGE
name: Fondazione di ricerca biomedica EBRIS
First posted: 2024-08-12
Enrollment: 350
Sex: ALL
Minimum age (years): 14
Maximum age (years): 50
Standard ages: CHILD
ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients with Major Depressive Disorders

Brief summary: 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.

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.

Eligibility criteria: 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 outcomes:
measure: Identify neuroinflammatory indices
timeFrame: 2 years
measure: Microbiome analysis
timeFrame: 2 years
measure: Metabolomic analysis
timeFrame: 2 years
measure: Analysis of lipoprotein profile
timeFrame: 2 years
measure: Identify immune-profile linked and epigenomic signatures
timeFrame: 2 years
measure: AI-powered diagnostics predictive tool
timeFrame: 2 years
measure: Mood assessment through brain biomarker
timeFrame: 2 years
measure: Patient engagement digital tool
timeFrame: 2 years
measure: Discovery of a new set of biomarkers
timeFrame: 2 years
measure: Investigation of the gut-brain-axis and of the biomarkers of interest in the context of mental diseases starting with MDD
timeFrame: 2 years
Secondary outcomes:
Other outcomes:
Locations:
city: Siena
country: Italy
facility: Università Degli Studi Di Siena
Study officials:
References: