Multiomic Alterations Associated with Antidepressant Response in Brain Organoids

• Grant number: 24/21099-0
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: September 01, 2025
• End date: April 30, 2030
• Field of knowledge: Biological Sciences - Biochemistry - Chemistry of Macromolecules
• Principal Investigator: Daniel Martins-de-Souza
• Grantee: Vitor Ikeda Ito Silva
• Host Institution: Instituto de Biologia (IB). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 23/14968-9 - The quest for antidepressant treatment response biomarkers: identifying the potential candidates, AP.R

Abstract

Major Depressive Disorder (MDD) is a severe psychiatric disorder characterized by a depressed mood and lack of interest and pleasure, affecting 185 million people worldwide with a lifetime prevalence of approximately 12%. Despite the role of serotonin in MDD having been recently disputed, Selective Serotonin Reuptake Inhibitors (SSRIs) antidepressants, specifically sertraline and escitalopram, remain the first-line treatment for MDD. Even with promising efficacy rates, only 27% of the patients achieve remission within 12 weeks. Several studies have attempted to understand the molecular mechanisms involved in MDD and the relationship with antidepressant response; however, the majority of these studies analyzed isolated brain cells, animal models, or post-mortem brains and peripheral samples such as blood or cerebrospinal fluid. These studies lack in model complexity, low translatability between animal models and humans, or the inability to manipulate relevant variables. Therefore, the present work aims to investigate the molecular mechanisms associated with escitalopram treatment response in a 3D cell culture that models the interactions between different brain cell types. To this end, induced pluripotent stem cells (iPSCs) derived from refractory and remitted MDD patients will be differentiated into brain organoids and treated with escitalopram. Single-cell RNA sequencing will be performed to assess the most affected neural cell types and biological processes. Proteomic and metabolomic analyses will also be performed, and the obtained multi-omics data will be integrated using the Multi-Omics Factor Analysis (MOFA) framework. Our findings aim to contribute to a better understanding of the molecular mechanisms involved in antidepressant treatment outcomes, as well as provide new predictive treatment biomarkers.