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Miller PE, Martin SS, Toth PP, Santos RD, Blaha MJ, Nasir K, Virani SS, Post WS, Blumenthal RS, Jones SR. Screening and advanced lipid phenotyping in familial hypercholesterolemia: The Very Large Database of Lipids Study-17 (VLDL-17). Journal of clinical lipidology. 2015 Sep 1; 9(5):676-83.
BACKGROUND: Familial hypercholesterolemia (FH) is an autosomal dominant dyslipidemia characterized by defective low-density lipoprotein (LDL) clearance. The aim of this study was to compare Friedewald-estimated LDL cholesterol (LDL-C) to biologic LDL-C in individuals screening positive for FH and then further characterize FH phenotypes. METHODS: We studied 1,320,581 individuals from the Very Large Database of Lipids, referred from 2009 to 2011 for Vertical Auto Profile ultracentrifugation testing. Friedewald LDL-C was defined as the cholesterol content of LDL-C, intermediate-density lipoprotein cholesterol, and lipoprotein(a) cholesterol (Lp(a)-C), with LDL-C representing biologic LDL-C. Using Friedewald LDL-C, we phenotypically categorized patients by the National Lipid Association guideline age-based screening thresholds for FH. In those meeting criteria, we categorized patients using population percentile-equivalent biologic LDL-C cutpoints and explored Lp(a)-C and remnant lipoprotein cholesterol (RLP-C) levels. RESULTS: Overall, 3829 patients met phenotypic criteria for FH by Friedewald LDL-C screening (FH+). Of those screening FH+, 78.8% were above and 21.2% were below the population percentile-equivalent biologic LDL-C. The mean difference in Friedewald biologic LDL-C percentiles was -0.01 (standard deviation, 0.17) for those above, and 1.92 (standard deviation, 9.16) for those below, respectively. Over 1 of 3 were found to have an elevated Lp(a)-C and over 50% had RLP-C greater than 95th percentile of the entire VLDL population. CONCLUSIONS: Of those who screened FH+, Friedewald and biologic LDL-C levels were closely correlated. Large proportions of the FH+ group had excess levels of Lp(a)-C and RLP-C. Future studies are warranted to study these mixed phenotypic groups and determine the role for further risk stratification and treatment algorithms.