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The use of polygenic score as a tool to determine the risk of schizophrenia

Grant number: 17/20059-0
Support type:Scholarships in Brazil - Master
Effective date (Start): March 01, 2018
Effective date (End): September 30, 2018
Field of knowledge:Health Sciences - Medicine
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal Investigator:Síntia Iole Nogueira Belangero
Grantee:Fernanda Talarico
Home Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil

Abstract

Schizophrenia (SCZ) is a serious mental illness, which comprehend positive symptoms, negativesymptoms and cognitive deficits, resulting in consequences for both individual and a society. Thedisease has an average incidence of 1.5 new cases per year per 10 000 inhabitants and is considered multifactorial, with environmental and genetic factors needed to develop it. The heritability for the SCZ is estimated at 60-80%, and the recurrent rate of having first-degree relative is 10%. Among the environmental factors associated with SCZ are urbanity, cannabis abuse and other drugs. Genome Wide Association Studies (GWAS) helped understanding the genetic components in disease, identifying single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) related to SCZ. Recently, the International Psychiatric Genetics Consortium (PGC) developed a tool to calculate the risk of each individual from a large sample of more than 35,000 SCZ patients and more than 100,000 controls. In this tool, called Polygenic Risk Score(PRS), variants associated with the disease are summed, resulting in an individual risk score. PRShas been widely used as a genetic risk variable and correlated with several clinical, neuropsychological, neuroimaging and other variables. It also have explained up to 30% of thedifference between cases and controls. Therefore, the aim of this project is to apply PRS in aBrazilian sample of patients with SCZ and controls, in order to observe genetic and environmentalrisk and protection factors for the disease. To do so, we will use the PGC reference GWAS, Michigan Imputation Server platform for genotyping imputation, PRSice and Plink programs to generate the score, and RStudio to identify whether there is relationship between SCZ and environmental factors or genetic variants. We will compare the controls with high scores and patients with low scores, in order to find mechanisms associated with healthy control resilience and patient propensity. Thus, we intend to identify environmental and genetic risk and protection factors, helping to understand the pathophysiology of SCZ, and trying to prevent, in the future, new cases of the disease. (AU)