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J. Lipid Res.
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A more recent version of this article appeared on April 1, 2009

Papers In Press, published online ahead of print December 5, 2008
J. Lipid Res., doi:10.1194/jlr.D800050-JLR200
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Submitted on November 18, 2008
Revised on December 5, 2008
Accepted on December 5, 2008

Determination of lipoprotein(a) Kringle repeat number from genomic DNA: Copy number variation genotyping using quantitative real-time PCR

Matthew Lanktree, Chandheeb Rajakumar, J. Howard Brunt, Marlys L. Koschinsky, Philip W. Connelly, and Robert A. Hegele

Robarts Research Institute, University of Western Ontario, London, Ontario N6A5K8

Corresponding Author: hegele{at}robarts.ca

Plasma lipoprotein(a) (Lp[a]) concentration is related to risk of cardiovascular disease (CVD). The defining protein component of Lp(a) particles, apolipoprotein(a) (apo[a]), is encoded by the LPA gene. Apo(a) is extremely heterogeneous in size due to a common copy number variation, leading to a variable number of kringle-IV type 2 (KIV2)-like domains. Alleles with fewer KIV2 repeats, encoding smaller apo(a) isoforms, are associated with higher plasma Lp(a) concentrations. Two principal methods to detect variation in KIV2 repeat number are electrophoresis with immunoblotting to detect apo(a) protein isoforms or pulse-field electrophoresis of unamplified genomic DNA to detect the variation of the LPA gene. Both methods are technically challenging, laborious and time consuming. Here, we report a rapid method to determine the number of KIV2 repeats in LPA from genomic DNA using quantitative real-time polymerase chain reaction (qPCR). With qPCR, we found KIV2 repeat number was correlated with both apo(a) isoform size as determined by immunoblotting (rs=0.50, P<1x10-6) and with plasma Lp(a) concentration (rs=0.30, P<1x10-6). The qPCR technique permits rapid evaluation of apo(a) size from genomic DNA, and thus would provide an adjunctive genomic variable, in addition to LPA single nucleotide polymorphisms, for evaluating the genetic determinants of plasma Lp(a) concentration in genetic epidemiology studies of CVD outcomes.


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