TY - JOUR
T1 - Optimizing and Predicting Antidepressant Efficacy in Patients with Major Depressive Disorder Using Multi-Omics Analysis and the Opade AI Prediction Tools
AU - Corrivetti, Giulio
AU - Monaco, Francesco
AU - Vignapiano, Annarita
AU - Marenna, Alessandra
AU - Palm, Kaia
AU - Fernández-Arroyo, Salvador
AU - Frigola-Capell, Eva
AU - Leen, Volker
AU - Ibarrola, Oihane
AU - Amil, Burak
AU - Caruson, Mattia Marco
AU - Chiariotti, Lorenzo
AU - Palacios-Ariza, Maria Alejandra
AU - Hoekstra, Pieter J.
AU - Chiang, Hsin Yin
AU - Floareș, Alexandru
AU - Fagiolini, Andrea
AU - Fasano, Alessio
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/7
Y1 - 2024/7
N2 - According to the World Health Organization (WHO), major depressive disorder (MDD) is the fourth leading cause of disability worldwide and the second most common disease after cardiovascular events. Approximately 280 million people live with MDD, with incidence varying by age and gender (female to male ratio of approximately 2:1). Although a variety of antidepressants are available for the different forms of MDD, there is still a high degree of individual variability in response and tolerability. Given the complexity and clinical heterogeneity of these disorders, a shift from “canonical treatment” to personalized medicine with improved patient stratification is needed. OPADE is a non-profit study that researches biomarkers in MDD to tailor personalized drug treatments, integrating genetics, epigenetics, microbiome, immune response, and clinical data for analysis. A total of 350 patients between 14 and 50 years will be recruited in 6 Countries (Italy, Colombia, Spain, The Netherlands, Turkey) for 24 months. Real-time electroencephalogram (EEG) and patient cognitive assessment will be correlated with biological sample analysis. A patient empowerment tool will be deployed to ensure patient commitment and to translate patient stories into data. The resulting data will be used to train the artificial intelligence/machine learning (AI/ML) predictive tool.
AB - According to the World Health Organization (WHO), major depressive disorder (MDD) is the fourth leading cause of disability worldwide and the second most common disease after cardiovascular events. Approximately 280 million people live with MDD, with incidence varying by age and gender (female to male ratio of approximately 2:1). Although a variety of antidepressants are available for the different forms of MDD, there is still a high degree of individual variability in response and tolerability. Given the complexity and clinical heterogeneity of these disorders, a shift from “canonical treatment” to personalized medicine with improved patient stratification is needed. OPADE is a non-profit study that researches biomarkers in MDD to tailor personalized drug treatments, integrating genetics, epigenetics, microbiome, immune response, and clinical data for analysis. A total of 350 patients between 14 and 50 years will be recruited in 6 Countries (Italy, Colombia, Spain, The Netherlands, Turkey) for 24 months. Real-time electroencephalogram (EEG) and patient cognitive assessment will be correlated with biological sample analysis. A patient empowerment tool will be deployed to ensure patient commitment and to translate patient stories into data. The resulting data will be used to train the artificial intelligence/machine learning (AI/ML) predictive tool.
KW - artificial intelligence
KW - chatbot
KW - EEG
KW - genetics
KW - inflammation
KW - major depressive disorders
KW - metabolomic
KW - microbiome
KW - personalized medicine
KW - transcriptomics
UR - http://www.scopus.com/inward/record.url?scp=85199754927&partnerID=8YFLogxK
U2 - 10.3390/brainsci14070658
DO - 10.3390/brainsci14070658
M3 - Article
AN - SCOPUS:85199754927
SN - 2076-3425
VL - 14
JO - Brain Sciences
JF - Brain Sciences
IS - 7
M1 - 658
ER -