medRxivGenetic & Genomic MedicinePreprint
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
Antônio José Cordeiro MattosiD, Precil Diego Miranda de Menezes NevesiD, Gustavo Bernardes de Figueiredo OliveiraiD, Frederico Rafael MoreiraiD, Maria Carolina Pintão, Viviane Zorzanelli RochaiD, Cristiane S. RochaiD, Viviane Nakano Katz, Elisa Napolitano FerreiraiD, Diana Rojas MálagaiD, Celso Ferraz Viana, Fabiula Fagundes da SilvaiD, Juliete Jorge VidottiiD, Natália Mariana Felício, Leticia de Araújo Vitor, Karina Gimenez Cesar, Camila Araújo da Silva, Lucas Bassolli de Oliveira AlvesiD, Haliton Alves de OliveiraiD, Álvaro AvezumiD
Abstract
Atherosclerotic 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 in clinicaltrials.gov (NCT05515653.)
- organism: human
- assay: whole-exome sequencing
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 1
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