DEEP-MIND (Deep Learning for Mental Health): Application of Deep Learning in the Brazilian High-Risk Cohort for the Integration of Genomic and Clinical Data

• Grant number: 25/02111-1
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: April 01, 2025
• End date: January 31, 2027
• Field of knowledge: Health Sciences - Medicine - Psychiatry
• Principal Investigator: Síntia Iole Nogueira Belangero
• Grantee: Victor Borin Centurion Biruel
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil
• Associated research grant: 21/05332-8 - Brazilian high-risk cohort for psychiatric disorders: 10 years follow-up, AP.TEM

Abstract

The DEEP-MIND project aims to apply deep-learning techniques to integrate genomic and clinical data within the Brazilian High-Risk Cohort (BHRC), with the goal of identifying genetic variants associated with major mental disorders and functional deviations. This initiative, resulting from a collaboration between the University of São Paulo (USP), Federal University of São Paulo (UNIFESP), and Federal University of Rio Grande do Sul (UFRGS), employs innovative approaches to analyze whole genome sequencing (WGS), genomic variants (SNVs and CNVs), and polygenic risk scores (PRS), correlating them with clinical and psychosocial data. The project has specific objectives, including the assembly and analysis of genomes, the development of pipelines for GWAS, and the creation of predictive models based on multimodal deep-learning, capable of integrating genomic, clinical, and geographic data. Additionally, it seeks to explore the predictive capacity of parental PRS in relation to their children's clinical outcomes, using statistical and mediation techniques. DEEP-MIND represents a significant advancement in understanding the genetic and clinical bases of mental disorders, with the potential to impact personalized medicine and clinical practice.