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Estimates, or risk scores, of the likelihood of future cardiovascular disease (CVD) in healthy people are widely used to guide primary preventative medical therapy. Current risk scores rely mainly on phenotypic criteria, such as serum lipid levels, and predictive accuracy is suboptimal, particularly in patients with intermediate risk scores. Genome-wide studies now have identified numerous single nucleotide polymorphisms (SNPs) associated with CVD but the potential additive value of these common genetic variants for CVD prediction is not clear.
In this issue of Heart, Morris and colleagues (see page 1640) calculated a risk score that combined a standard phenotypic risk estimate with analysis of 53 common SNPs. This score was then evaluated using data from several prospective studies including a total of nearly 12 thousand people initially free of CVD who experienced 1444 incident CVD events during 10 years of follow-up. Overall, the addition of SNP data did not improve CVD risk prediction signficantly. However, in those at intermediate risk based on phenotypic criteria, the authors suggest that “genetic information would prevent one additional event for every 462 people screened” (figure 1).
The lack of a major improvement risk stratification using genetic markers certainly is disappointing at first glance. However, we should keep in mind, as Pereira discusses in the accompanying editorial (see page 1612), that …
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