期刊
CIRCULATION-CARDIOVASCULAR GENETICS
卷 5, 期 5, 页码 547-554出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIRCGENETICS.112.963165
关键词
myocardial infarction; polymorphism myocardial infarction; population; single nucleotide; polymorphisms; coronary artery disease
资金
- Center of Excellence in Personalized Medicine (CEPMED)
- Canada Research Chair program
- Fonds de recherche du Quebec en Sante (FRQS)
- Montreal Heart Institute Foundation
- Genome Canada
Background-Familial history is a strong risk factor for coronary artery disease (CAD), especially for early-onset myocardial infarction (MI). Several genes and chromosomal regions have been implicated in the genetic cause of coronary artery disease/MI, mostly through the discovery of familial mutations implicated in hyper-/hypocholesterolemia by linkage studies and single nucleotide polymorphisms by genome-wide association studies. Except for a few examples (eg, PCSK9), the role of low-frequency genetic variation (minor allele frequency [ MAF]) approximate to 0.1%-5% on MI/coronary artery disease predisposition has not been extensively investigated. Methods and Results-We selected 68 candidate genes and sequenced their exons (394 kb) in 500 early-onset MI cases and 500 matched controls, all of French-Canadian ancestry, using solution-based capture in pools of nonindexed DNA samples. In these regions, we identified 1852 single nucleotide variants (695 novel) and captured 85% of the variants with MAF >= 1% found by the 1000 Genomes Project in Europe-ancestry individuals. Using gene-based association testing, we prioritized for follow-up 29 low-frequency variants in 8 genes and attempted to genotype them for replication in 1594 MI cases and 2988 controls from 2 French-Canadian panels. Our pilot association analysis of low-frequency variants in 68 candidate genes did not identify genes with large effect on MI risk in French Canadians. Conclusions-We have optimized a strategy, applicable to all complex diseases and traits, to discover efficiently and cost-effectively DNA sequence variants in large populations. Resequencing endeavors to find low-frequency variants implicated in common human diseases are likely to require very large sample size. (Circ Cardiovasc Genet. 2012;5:547-554.)
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