GWAS Applied to Heart Failure

Abstract

> “It would be so nice if something made sense for a change.” > > “Alice in Wonderland”, produced by Walt Disney (1951), based on the book by Lewis Carroll, Alice's Adventures in Wonderland, Macmillan and Co, London, 1865. Over the last decade, the application of genetics to cardiac risk has transitioned from single gene assessment in rare mendelian disorders to more common complex phenotypes such as ischemic heart disease, atrial fibrillation, and heart failure. This transition has been accelerated by the advances in genomic technology that have made Genome Wide Association Studies (GWAS) both practical and productive. In any clinical research, study number is power, and nowhere is that more important than GWAS, in which the cost of millions of simultaneous single nucleotide polymorphism (SNP) assessments is the need to set the statistical level of significance sufficiently low to avoid false-positives. This need for larger GWAS cohorts has led investigators to develop “networks of networks” to identify novel loci that are ultimately reproducible and truly important to cardiovascular risk and/or outcomes. In this issue of Circulation: Cardiovascular Genetics, the CHARGE investigators have used such a strategy and present meta-analyses of 4 community-based cohorts to evaluate genomic heart failure risk1 and heart failure mortality2 in nearly 24 000 subjects. Their findings demonstrate both the promise and the challenges of applying GWAS to heart failure. Articles see p 248 and 256 Patients with similar myocardial insults progress to the heart failure syndrome at markedly variable rates and degrees, and in the modern era it is clear that a significant portion of this clinical heterogeneity is genetically based. Indeed, analysis from multigenerational cohorts from the Framingham study has estimated that 28% of the risk of heart failure caused by systolic dysfunction can be attributed to genetic factors.3 Given the well-described pathways of …