Impact of Lipoprotein(a)-Cholesterol on Accurate Classification of Familial Hypercholesterolemia
Authors: Fatica Erica , Meeusen Jeffrey W , Donato Leslie J 
Published: October 2020

Lipoprotein(a) [Lp(a)] is a pro-atherogenic and pro-thrombotic LDL-like particle recognized as an independent risk factor for cardiovascular disease (CVD) that is resistant to typical lipid-lowering treatments. The cholesterol within Lp(a) (Lp(a)-C) contributes to the reported LDL-cholesterol (LDL-C) concentration by nearly all available methods including beta-quantification, direct homogenous assays, and all estimating equations. Accurate LDL-C measurements are critical for identification of genetic hyperlipidemia conditions such as familial hypercholesterolemia (FH). FH risk estimators such as the Dutch Lipid Clinic Network (DLCN) criteria utilize LDL-C concentration cut-offs and other clinical inputs to assess the likelihood of FH. Therefore, failure to adjust for Lp(a)-C can impact accurate FH classification, appropriate follow-up testing and treatments, and interpretation of cholesterol-lowering treatment efficacy. Lp(a)-C can be estimated from Lp(a) mass as measured by immunoassay using an average cholesterol content per particle. However, Lp(a)-C size and composition varies significantly within individuals resulting in inaccurate Lp(a)-C estimates. In this study, we use direct Lp(a)-C measurements to assess the potential misclassification of FH risk due to the contribution of Lp(a)-C to LDL-C in patient samples submitted for advanced lipoprotein profiling. A total of 28,200 samples submitted for lipoprotein profiling were included. The profiling included lipid testing in a CDC-certified laboratory on Roche cobas 501 (cholesterol and triglycerides by enzymatic method, high-density lipoprotein cholesterol by MgCl2/dextran sulfate precipitation). LDL-C was measured by beta-quantification, and Lp(a)-C by quantitative lipoprotein electrophoresis (SPIFE Vis Cholesterol, Helena Laboratories). The DLCN LDL-C cut-offs (155, 190, 250, and 330mg/dL) were applied to LDL-C results before and after accounting for Lp(a)-C contribution. Lp(a)-C was detected in 3,728 (13.2%) samples. The median (range) concentrations of Lp(a)-C and LDL-C were 11mg/dL (5-108mg/dL) and 121mg/dL (27-678mg/dL), respectively. Overall, subtracting Lp(a)-C would reclassify 6.5% of all samples into a lower LDL-C category within the DLCN algorithm. Within the LDL-C scoring categories, 7.0% (n=222) of subjects with LDL-C 155-189mg/dL, 5.6% (n=66) of subjects with LDL-C 190-249mg/dL, 5.2% (n=10) of subjects with LDL-C 250-329mg/dL, and 3.4% (n=4) of subjects with LDL-C &gt;330mg/dL would be down-classified after adjusting for Lp(a)-C. Limiting to subjects with measurable Lp(a)-C, reclassification to a lower diagnostic threshold occurred in 47.4% of subjects with LDL-C 155-189mg/dL, 37.5% with LDL-C 190-249mg/dL, 41.6% with LDL-C 250-329mg/dL, and 33.3% with LDL-C &gt;330mg/dL after adjustment. Current guidelines recommend screening for elevated Lp(a) in patients with family history of CVD. Our data show that a high percentage of samples evaluated for advanced lipid testing contain measurable Lp(a)-C that could cause mis-classification in FH prediction algorithms. If labeled high probability of FH, these mis-classifications could trigger inappropriate work-up for suspected FH. As clinical follow-up and therapeutic strategies differ between FH and elevated Lp(a), proper distinction between LDL-C and Lp(a)-C is needed to guide appropriate patient management.