Periodic Reporting for period 1 - OPADE (Optimise and predict antidepressant efficacy for patient with major depressive disorders using multi-omics analysis and AI-predictive tool)
Berichtszeitraum: 2022-12-01 bis 2024-05-31
According to the WHO, Major Depressive Disorder (MDD) is the 4th leading cause of disability worldwide and the second most common disease after cardiovascular events. MDD is a multifactorial disease driven by a combined effect of genetic, epigenetic, psychological, biological, and environmental factors including compositional and functional changes in the gut microbiome. The microbiome exerts its effect on the nervous system, the so-called microbiome-gut-brain (MGB) axis, through the synthesis of metabolites that induce neurotransmitter production and immune system activation. In addition to influencing specific brain functions, there is a growing evidence that the gut microbiome may also affect epigenetic patterns and indirectly influence the efficacy of several drugs, including antidepressants. Both diagnosis and treatment of MDD patients remain challenging due to the lack of early biomarkers and personalized treatment options, especially for pediatric patients.
To address these issues, in this context, the OPADE project aims to identify early biomarkers in MDD to tailor personalized drug treatments. three hundred fifty patients between fourteen and fifty years will be recruited in 6 Countries (Italy, Colombia, Spain, Netherlands, Turkey) for twenty-four months. Real-time electroencephalogram (EEG) and patient cognitive assessment will be correlated with biological samples analysis. A patient empowerment tool (Chatbot) will be deployed to ensure patient commitment and to translate patient stories into data. 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. Resulting data will be used to train the Artificial Intelligence/Machine Learning (AI/ML) predictive tool. In summary, the OPADE project aims to analyze MDDs at different levels and with different approaches, leading to the constitution of a ML algorithm for improving diagnosis and treatment, preventing relapse by combining genetics, epigenetics, microbiome, immune response data, and the non-molecular biomarkers such as medical history, electroencephalography (EEG), from subjects with MDD.
To address these issues, in this context, the OPADE project aims to identify early biomarkers in MDD to tailor personalized drug treatments. three hundred fifty patients between fourteen and fifty years will be recruited in 6 Countries (Italy, Colombia, Spain, Netherlands, Turkey) for twenty-four months. Real-time electroencephalogram (EEG) and patient cognitive assessment will be correlated with biological samples analysis. A patient empowerment tool (Chatbot) will be deployed to ensure patient commitment and to translate patient stories into data. 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. Resulting data will be used to train the Artificial Intelligence/Machine Learning (AI/ML) predictive tool. In summary, the OPADE project aims to analyze MDDs at different levels and with different approaches, leading to the constitution of a ML algorithm for improving diagnosis and treatment, preventing relapse by combining genetics, epigenetics, microbiome, immune response data, and the non-molecular biomarkers such as medical history, electroencephalography (EEG), from subjects with MDD.
During the first eighteen months, under the coordination of EBRIS, the OPADE consortium has finalized all the procedures for the start up of the trial including the submission of the study protocol to the local Ethics Committees, the editing of a vademecum for biological samples collection, storage and trafficking and the implementation of a electronic platform for data collection and validation (RedCap). A dedicated study team (certified for GCP) is actively involved in the daily monitoring of entered data.
Regular updating of the progress/issues related to the project, including the recruitment status, sample trafficking, data analysis and use of devices involved in the study protocol, is achieved through the delivery of a monthly Newsletter.
Biological samples processing has started and the version V.1 of the AI model has been already developed. EBRIS has implemented an engineered planning and organization of data so that they are fair and secure. The trial has been registered on the international registry clinicaltrials.gov and is currently under revision. All the deliveries related to M18 were submitted and approved.
Regular updating of the progress/issues related to the project, including the recruitment status, sample trafficking, data analysis and use of devices involved in the study protocol, is achieved through the delivery of a monthly Newsletter.
Biological samples processing has started and the version V.1 of the AI model has been already developed. EBRIS has implemented an engineered planning and organization of data so that they are fair and secure. The trial has been registered on the international registry clinicaltrials.gov and is currently under revision. All the deliveries related to M18 were submitted and approved.
Within the first eighteen months of OPADE Project, 139 patients were enrolled and according to the study protocol around 13,900 biological samples were collected (blood, saliva, stool). The Consortium partners registered 139,000 metadata and have validated 98.3% of them. Biological sample trafficking and processing was started and the first version of the AI model was developed. The study protocols were submitted to the international journal Brain Sciences and other two publications were already delivered.
The protocols were also registered on the international registry clinicaltrials.gov (under revision).
The protocols were also registered on the international registry clinicaltrials.gov (under revision).