Integration of single nucleotide variants, genetic ancestry and single nucleus RNA-seq data from prefrontal cortex of schizophrenia patients

• Grant number: 24/18987-0
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: January 01, 2025
• End date: May 31, 2025
• Field of knowledge: Biological Sciences - Genetics - Human and Medical Genetics
• Principal Investigator: Síntia Iole Nogueira Belangero
• Grantee: Gustavo Satoru Kajitani
• Supervisor: Konstantin Khodosevich
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil
• Institution abroad: University of Copenhagen, Denmark
• Associated to the scholarship: 22/14055-0 - Evaluation of the prognostic potential of MicroRNAs in the development of epilepsy after traumatic brain injury, BP.PD

Abstract

Schizophrenia, one the most well-characterized psychiatric disorders, presents symptoms such as psychosis, cognitive impairment, and social dysfunction. It has a very impactful genetic component, with heritability estimated at around 70%. Despite extensive genomic and transcriptomic research, only a few genes have been consistently linked with schizophrenia. Variability in results can be attributed to factors such as study design, symptom manifestations, tissue cell type composition, and both environmental and genetic variations, including differences in genetic ancestry. To address these issues, this project aims to conduct integrative analyses using single nucleus RNA-Seq (snRNA-seq) of postmortem prefrontal cortex neuronal nuclei from schizophrenia and control samples. These samples are being obtained from patients with diverse genetic backgrounds and ancestries. Using snRNA-seq, we intend to identify cell-type composition and gene expression alterations specific to schizophrenia. Additionally, we will identify genetic variants from the snRNA-seq data to obtain single nucleotide variants (SNVs) from each sample, enabling the reconstruction of genetic data, which will be used for identification of sample ancestry, and association of SNVs with schizophrenia-specific gene expression in neuronal subtypes and with patient-specific symptoms. This integrative, multidimensional analysis can elucidate the molecular etiology of functional brain impairments in schizophrenia, and thereby in specific symptoms in psychiatric disorders, potentially facilitating the advancement of personalized diagnostics and drug discovery.