Impact of Genetic Background as a Risk Factor for Atherosclerotic Cardiovascular Disease: A Protocol for a Nationwide Genetic Case-Control (CV-GENES) study in Brazil

Author:

Mattos Antônio José Cordeiro,de Menezes Neves Precil Diego Miranda,de Figueiredo Oliveira Gustavo BernardesORCID,Moreira Frederico Rafael,Pintão Maria Carolina,Rocha Viviane Zorzanelli,de Souza Rocha Cristiane,Katz Viviane Nakano,Ferreira Elisa Napolitano,Rojas-Málaga Diana,Viana Celso Ferraz,da Silva Fabiula FagundesORCID,Vidotti Juliete JorgeORCID,Felicio Natalia Mariana,de Araujo Vitor Leticia,Cesar Karina Gimenez,da Silva Camila Araújo,de Oliveira Alves Lucas Bassolli,de Oliveira Junior Haliton AlvesORCID,Avezum Álvaro

Abstract

ABSTRACTAtherosclerotic Cardiovascular Disease (ASCVD) represents the leading cause of death worldwide, and individual screening should be based on behavioral, metabolic, and genetic profile derived from data collected in large population-based studies. Due to a polygenic nature of ASCVD, we aimed to assess the association of genomics to ASCVD risk and its impact on the occurrence of acute myocardial infarction, stroke, or peripheral artery thrombotic-ischemic events on a population level. CV-GENES is a multicenter, Brazilian nationwide, 1:1 case-control study of 3,734 patients. Inclusion criteria for cases are the first occurrence of one of the cardiovascular events. Individuals without known ASCVD, and age- and sex-matched will be eligible for the control group. A genetics core lab analysis will be performed through the association of low-pass whole genome sequencing and whole exome sequencing. A polygenic risk score will be built in a multiethnic population to estimate the association between genetic polymorphisms and risk of ASCVD. In addition, the presence of pathogenic or likely pathogenic variants will be screened in 8 genes (ABCG5,ABCG8,APOB,APOE, LDLR,LDLRAP1,LIPA, PCSK9) associated with atherosclerosis. Multiple logistic regression will be applied to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs), and population attributable risks will be calculated. This study is registered inclinicaltrials.gov(NCT05515653.)

Publisher

Cold Spring Harbor Laboratory

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