Association of genetic variants and biological pathways across different psychiatric disorders

• Grant number: 19/07163-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): July 01, 2019
• Effective date (End): December 31, 2019
• Field of knowledge: Health Sciences - Medicine - Psychiatry
• Principal Investigator: Síntia Iole Nogueira Belangero
• Grantee: Jessica Honorato Mauer
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil

Abstract

Psychiatric disorders are some of the main causes of functional impairment among complex diseases and lead to a major impact in the lives of patients and to society. Psychiatric disorders are highly heritable, and studies reveal that there is overlapping of genetic factors across different disorders. Therefore, to study psychiatric disorders in a joint way enables a better understanding of the shared genetic etiology between them. Therefore, the objectives of this study are: 1) To identify genetic variants common between psychiatric disorders in a highly admixture sample; 2) To perform functional annotation and pathway enrichment analysis of the associated SNPs/genes; 3) To estimate the SNP heritability for the presence of some psychiatric disorders in the sample, and 4) To compare our findings to the results of the Psychiatric Genomics Consortium (which uses a similar approach, although with a mainly European sample). To reach these objectives a Genome-Wide Association Study (GWAS) will be performed, evaluating 1,285 individuals with psychiatric disorders and 2,221 controls (undiagnosed with psychiatric disorders until the moment of recruitment) from four cohorts (including patients diagnosed with schizophrenia, post-traumatic stress disorder and attention deficit-hiperactivity disorder, patients in first-episode psychosis and children/adolescents in high risk for developing psychiatric disorders). The analyses will be performed in UNIX operational systems using the PLINK, R, GCTA and FUMA computational tools. With the results of the present study, we intend to improve knowledge about the common genetic underpinnings of psychiatric disorders, to verify if the variants associated in other studies apply to our population, and to point variants that may aid the identification of individuals at risk for these pathologies.