Extreme lipoprotein(a) levels and improved cardiovascular risk prediction

Abstract

Objectives: The study tested whether extreme lipoprotein(a) levels and/or corresponding LPA risk genotypes improve myocardial infarction (MI) and coronary heart disease (CHD) risk prediction beyond conventional risk factors. Background: Elevated lipoprotein(a) levels cause MI and CHD. Levels are primarily determined by variation in the LPA gene. Methods: We followed 8,720 Danish participants in a general population study from 1991 to 1994 through 2011 without losses to follow-up. During this period, 730 and 1,683 first-time MI and CHD events occurred. Using predefined cutpoints for extreme lipoprotein(a) levels and/or corresponding LPA risk genotypes (kringle IV type 2 [KIV-2]) repeat polymorphism, rs3798220, and rs10455872 single nucleotide polymorphisms), we calculated net reclassification indices from <10% to 10% to 19.9% to ≥20% absolute 10-year MI and CHD risk. Results: For individuals with lipoprotein(a) levels ≥80th percentile (≥47 mg/dl), 23% (p < 0.001) of MI events and 12% (p < 0.001) of CHD events were reclassified correctly, while no events were reclassified incorrectly for either endpoint. As some incorrect reclassification of individuals with no events occurred, addition of lipoprotein(a) levels ≥ 80th percentile overall yielded net reclassification indices of +16% (95% confidence interval: 8% to 24%) and +3% (-1% to 8%) for MI and CHD, respectively. Corresponding net reclassification indices for number of KIV-2 repeats ≤21st percentile were +12% (5% to 19%) and +4% (0% to 8%), for rs3798220 carrier status +15% (-14% to 44%) and +10% (-10% to 30%), and for rs10455872 carrier status +16% (6% to 26%) and +2% (-1% to 6%). Considering only individuals at 10% to 19.9% absolute 10-year MI and CHD risk, addition of extreme lipoprotein(a) levels or corresponding LPA risk genotypes improved risk prediction even further. Conclusions: Extreme lipoprotein(a) levels or corresponding LPA KIV-2/rs10455872 risk genotypes substantially improved MI and CHD risk prediction. © 2013 by the American College of Cardiology Foundation.