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Application of polygenic risk score methods in admixed population

Grant number: 22/16317-2
Support Opportunities:Scholarships in Brazil - Doctorate (Direct)
Effective date (Start): May 01, 2023
Effective date (End): April 30, 2026
Field of knowledge:Health Sciences - Medicine - Psychiatry
Principal Investigator:Marcos Leite Santoro
Grantee:Rafaella Ormond Sampaio
Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil
Associated scholarship(s):23/16709-0 - Improving prediction of schizophrenia by integrating genomic and epigenomic data, BE.EP.DD

Abstract

Schizophrenia is a severe mental disease with a prevalence of up to 1% in the world population and one of the main causes of disability in developed countries. Schizophrenia is a multifactorial disease and heritability is around 0,8. This suggests that the genome contains a large amount of information that has the potential to be used as genetic markers for diagnosing these disease. However, the polygenic nature of this disease, added to the influence of environmental factors, makes it difficult to explore this information. In the last years, the expansion of consortia in psychiatric genetics has allowed the creation of a polygenic risk score (PRS) for schizophrenia based on the results of genome-wide association studies (GWAS). With the increase of available GWAS, new PRS methods have emerged, each method has advantages and disadvantages with varying accuracies and computational burdens. One of the limitations of the PRS is that it has better prediction and greater validity for the population of European ancestry, making it difficult to apply in admixed samples, such as the Brazilian population. This is mainly due to the low number of GWAS with non-European ancestry.The overall objective of this proposal is: To improve the PRS prediction of schizophrenia in admixed population. The specific objectives are: 1) To verify the impact of admixture on the PRS using 6 tools already available in the literature; 2) Reformulate a PRS application methodology based on the PC+T method after decomposing the PRS into three subpopulations (European, African and Native American) for each individual; 3) Check which of the applied methodologies obtained a better prediction of PRS in admixed population. For the PRS analysis, we will use the already genotyped cohorts of the group (N=3379) with the Global Screening Array. The analysis will be done entirely by UNIX operating systems using the command line language as well as the statistical program R, PLINK and PRSice. The student will calculate the PRS for the height and schizophrenia phenotypes, using 8 different PRS tools, in order to verify the prediction of these tools in admixed population. (AU)

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