O uso do escore poligênico como uma ferramenta de determinação de risco de esquizofrenia

• Autor(a) principal: Talarico, Fernanda [UNIFESP]
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UNIFESP
• Texto Completo: https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=7025591; https://repositorio.unifesp.br/handle/11600/52333
• topic: Schizophrenia; Multifactorial inheritance; Environmental exposure; Esquizofrenia; Herança multifatorial; Exposição ambiental

Background: Schizophrenia (SCZ) is a severe and debilitating psychiatric disorder. Its main characteristics are the positive, negative and cognitive deficits symptoms. It is a multifactorial disease; thus, environmental (such as use of substances) and genetic factors (single nucleotide polymorphisms SNPs, with low effect size, as well as copy number variations CNVs, with lower effect size) interact together to its development. From genomewide association studies (GWAS), an instrument called polygenic risk score (PRS) is used to estimate the individual genetic risk to SCZ development (from low size effect variants). Objectives: To verify how an interracial admixture may interfere to PRS results. Additionally, to verify the effects of environmental and genetic factors on SCZ patients, in order to improve a tool for risk measurement. Methodology: We used the summary statistics from PGC (Psychiatric Genomics Consortium) SCZGWAS (36,989 patients and 113,075 controls) to calculate PRS in our sample (309 patients and 445 controls). Genotyping was performed with Human OmniExpress Beadchips and Infinium PsychArray BeadChips (Illumina, USA). Genomic imputation was performed on Sanger server and PRScise and PLINK were used to calculate PRS. The environmental factors evaluated were the use of substances, as drugs, alcohol, cigarette smoke and cannabis. The genetics factors were, besides the PRS, the amount of CNVs per individual and whether it was duplication or deletion of base pairs. Results: We explained 5% of variety between cases and controls when including all individual. Better results were obtained when selecting only Caucasians (11% of variability was explained). Moreover, we observed that the exposure to environmental factors were more present in patients with lower genetic risk to SCZ when compared to controls with higher genetic risk, as well as the amount of CNVs. Furthermore, the best SCZ predictor model was the one calculated for all environmental and genetic factors together. Conclusion: This study allowed us to confirm that different ancestries have a negative effect on PRS. Even more, we supported our initial hypothesis stablished at the beginning of the work: patients with lower genetic risk factors had been exposed to more environmental factors and/or CNVs. Lastly, we observed that combining environmental and genetic risk factors is the most accurate predictor do SCZ.