Journal of clinical lipidology · 2016
Predicting proprotein convertase subtilisin kexin type-9 loss of function mutations using plasma PCSK9 concentration.
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Wanneh Eric, Luna Grisel, Dufour Robert, Baass Alexis
Аннотация
BACKGROUND: Low plasma proprotein convertase subtilisin kexin type-9 (PCSK9) concentration has been associated with loss of function (LOF) PCSK9 mutations in several studies. However, the current standard for detection of these LOF mutations is through gene sequencing. Gene sequencing is labor intensive and expensive. Identifying a simple test to help predict PCSK9 LOF mutations would help to better target subjects requiring gene sequencing.
OBJECTIVES: Determine the diagnostic accuracy of plasma PCSK9 concentration in detecting PCSK9 LOF mutations using genotyping as the gold standard.
METHODS: We carried out a retrospective analysis of 1412 French-Canadian participants of the Quebec Child and Adolescent Health and Social Survey who had been screened for the PCSK9 R46L and Leucine insertion (InsLEU) LOF mutations by genotyping. Their plasma PCSK9 concentrations were measured using a well-described enzyme-linked immunosorbent assay. We used the Youden index to determine the optimal cutoff for PCSK9 concentration to predict mutation status. We further investigated the use of low-density lipoprotein cholesterol (LDL-C) concentration in combination with plasma PCSK9 concentration to refine the prediction of mutation status.
RESULTS: Plasma PCSK9 had a moderate accuracy (area under the curve, 0.71) in detecting the PCSK9 R46L mutation with a sensitivity of 71% and specificity of 70% at cutoff of 70 ng/mL. Combining PCSK9 and LDL-C increased the diagnostic accuracy for the detection of the R46L mutation (area under the curve, 0.75). However, plasma PCSK9 concentration was no better than chance at detecting PCSK9 InsLEU mutation.
CONCLUSION: This analysis suggests that plasma PCSK9 combined with LDL-C concentrations might be useful to predict certain PCSK9 LOF mutations such as the R46L mutation but may fail to predict others such as the InsLEU mutation.
OBJECTIVES: Determine the diagnostic accuracy of plasma PCSK9 concentration in detecting PCSK9 LOF mutations using genotyping as the gold standard.
METHODS: We carried out a retrospective analysis of 1412 French-Canadian participants of the Quebec Child and Adolescent Health and Social Survey who had been screened for the PCSK9 R46L and Leucine insertion (InsLEU) LOF mutations by genotyping. Their plasma PCSK9 concentrations were measured using a well-described enzyme-linked immunosorbent assay. We used the Youden index to determine the optimal cutoff for PCSK9 concentration to predict mutation status. We further investigated the use of low-density lipoprotein cholesterol (LDL-C) concentration in combination with plasma PCSK9 concentration to refine the prediction of mutation status.
RESULTS: Plasma PCSK9 had a moderate accuracy (area under the curve, 0.71) in detecting the PCSK9 R46L mutation with a sensitivity of 71% and specificity of 70% at cutoff of 70 ng/mL. Combining PCSK9 and LDL-C increased the diagnostic accuracy for the detection of the R46L mutation (area under the curve, 0.75). However, plasma PCSK9 concentration was no better than chance at detecting PCSK9 InsLEU mutation.
CONCLUSION: This analysis suggests that plasma PCSK9 combined with LDL-C concentrations might be useful to predict certain PCSK9 LOF mutations such as the R46L mutation but may fail to predict others such as the InsLEU mutation.