Digital droplet PCR versus quantitative PCR for lipoprotein (a) kringle IV type 2 repeat polymorphism genetic characterization

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 c...

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Veröffentlicht in:Journal of clinical laboratory analysis Jg. 38; H. 5; S. e24998 - n/a
Hauptverfasser: Barbieri, Giulia, Cassioli, Giulia, Kura, Ada, Orsi, Rebecca, Magi, Alberto, Berteotti, Martina, Scaturro, Giusi Maria, Lotti, Elena, Gori, Anna Maria, Marcucci, Rossella, Giusti, Betti, Sticchi, Elena
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States John Wiley & Sons, Inc 01.03.2024
Schlagworte:
Apolipoproteins
atherothrombotic risk
Cardiovascular diseases
Cholesterol
Copy number
Correlation analysis
digital droplet PCR
Enzymes
Gene polymorphism
High density lipoprotein
kringle IV type 2
Laboratories
lipoprotein (a)
Lipoproteins
Methods
Plasma
Plasma levels
Polymerase chain reaction
Polymorphism
Proteins
Quantitative analysis
quantitative real‐time PCR
Software
Statistical analysis
United States > US
Germany
quantitative real‐time PCR
kringle IV type 2
digital droplet PCR
atherothrombotic risk
lipoprotein (a)
ISSN:0887-8013, 1098-2825, 1098-2825
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Zusammenfassung: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. In this study, real‐time and digital droplet PCR were compared in the evaluation of KIV2 repeat copy number variation polymorphism, concerning LPA gene, which encode apolipoprotein (a), protein component of lipoprotein (a), which is a known genetic independent risk factor for atherothrombosis. Digital droplet PCR emerges as a promising method that can make improvements in the measurement of this kind of large repeat length CNV, which is used to assess the causality between Lp(a) and cardiovascular diseases.
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ISSN:0887-8013
1098-2825
1098-2825
DOI:10.1002/jcla.24998