Genetics
Digital droplet PCR outperforms quantitative PCR for measuring the LPA KIV2 repeat that drives Lp(a) variability (J Clin Lab Anal 2024)
Original title: Digital droplet PCR versus quantitative PCR for lipoprotein (a) kringle IV type 2 repeat polymorphism genetic characterization
In 100 subjects tested for cardiovascular risk with Lp(a) plasma levels assessed, this study compared quantitative real-time PCR (qPCR) against digital droplet PCR (ddPCR) for measuring copy number variation in the LPA kringle IV type 2 (KIV2) repeat, the primary genetic driver of Lp(a) variability. Correlation between the two methods' copy number values was only weakly significant (R = 0.413, p = 0.00002), reflecting wider data dispersion with qPCR, and ddPCR showed superior stability with lower intra- and inter-assay variation on internal controls. Both methods confirmed a significant inverse correlation between Lp(a) and KIV2 copy number, but it was stronger with ddPCR (R = -0.393) than qPCR (R = -0.220), and the KIV2 repeat difference between high- and low-Lp(a) groups was far more significant with ddPCR (p = 0.000013) than qPCR (p = 0.001). Digital droplet PCR offers meaningfully better performance for characterising this key genetic determinant of Lp(a) concentration.
Original abstract
Background: Lipoprotein(a) [Lp(a)] level variability, related to atherothrombotic risk increase, is mainly attributed to LPA gene, encoding apolipoprotein(a), with kringle IV type 2 (KIV2) copy number variation (CNV) acting as the primary genetic determinant. Genetic characterization of Lp(a) is in continuous growth; nevertheless, the peculiar structural characteristics of this variant constitute a significant challenge to the development of effective detection methods. The aim of the study was to compare quantitative real-time PCR (qPCR) and digital droplet PCR (ddPCR) in the evaluation of KIV2 repeat polymorphism.
Methods: We analysed 100 subjects tested for cardiovascular risk in which Lp(a) plasma levels were assessed.
Results: Correlation analysis between CNV values obtained with the two methods was slightly significant (R = 0.413, p = 0.00002), because of the wider data dispersion in qPCR compared with ddPCR. Internal controls C1, C2 and C3 measurements throughout different experimental sessions revealed the superior stability of ddPCR, which was supported by a reduced intra/inter-assay coefficient of variation determined in this method compared to qPCR. A significant inverse correlation between Lp(a) levels and CNV values was confirmed for both techniques, but it was higher when evaluated by ddPCR than qPCR (R = -0.393, p = 0.000053 vs R = -0.220, p = 0.028, respectively). When dividing subjects into two groups according to 500 mg/L Lp(a) cut-off value, a significantly lower number of KIV2 repeats emerged among subjects with greater Lp(a) levels, with stronger evidence in ddPCR than in qPCR (p = 0.000013 and p = 0.001, respectively).
Conclusions: Data obtained support a better performance of ddPCR in the evaluation of KIV2 repeat polymorphism.
Summary written by lp-a.org from the published abstract; figures as published. Page updated 18 August 2026. Methods.