A new phenotypic classification system for dyslipidemias based on the standard lipid panel

• Published in: Lipids in health and disease Vol. 20; no. 1; p. 170
• Main Authors: Sampson, Maureen, Ballout, Rami A, Soffer, Daniel, Wolska, Anna, Wilson, Sierra, Meeusen, Jeff, Donato, Leslie J, Fatica, Erica, Otvos, James D, Brinton, Eliot A, Rosenson, Robert S, Wilson, Peter, Amar, Marcelo, Shamburek, Robert, Karathanasis, Sotirios K, Remaley, Alan T
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 27.11.2021; BioMed Central; BMC
• Subjects: Adult; Algorithms; Arteriosclerosis; Atherosclerosis; Cardiovascular disease; Cardiovascular diseases; Cholesterol; Classification; Diagnosis; Dyslipidemias; Dyslipidemias - blood; Dyslipidemias - classification; Female; Gel electrophoresis; Genetics; Genotype & phenotype; Heart Disease Risk Factors; High density lipoprotein; Humans; Identification and classification; LDL; Lipids; Lipids - blood; Lipoproteins; Lipoproteins - blood; Male; Medical laboratories; Metabolic disorders; Metabolism; Pancreatitis; Phenotype; Phenotypes; Phenotyping; Physiological aspects; Plasma; Risk assessment; Triglycerides; Triglycerides - blood; United States; United States > US; Cardiovascular disease; Genetics; Lipids; Lipoproteins; LDL; Cholesterol
• ISSN: 1476-511X; 1476-511X
• DOI: 10.1186/s12944-021-01585-8

Dyslipoproteinemias can be classified by their distinct lipoprotein patterns, which helps determine atherosclerotic cardiovascular disease (ASCVD) risk and directs lipid management but this has required advanced laboratory testing. To develop a new algorithm for classifying lipoprotein disorders that only relies on the standard lipid panel. Lipid thresholds for defining the different lipoprotein phenotypes were derived for Non-High-Density Lipoprotein-Cholesterol (NonHDL-C) and Triglycerides (TG) to be concordant when possible with the current US Multi-Society guidelines for blood cholesterol management. The new classification method categorizes patients into all the classical Fredrickson-like phenotypes except for Type III dysbetalipoproteinemia. In addition, a new hypolipidemic phenotype (Type VI) due to genetic mutations in apoB-metabolism is described. The validity of the new algorithm was confirmed by lipid analysis by NMR (N = 11,365) and by concordance with classification by agarose gel electrophoresis/beta-quantification (N = 5504). Furthermore, based on the Atherosclerosis Risk in Communities (ARIC) cohort (N = 14,742), the lipoprotein phenotypes differ in their association with ASCVD (TypeV>IIb > IVb > IIa > IVa > normolipidemic) and can be used prognostically as risk enhancer conditions in the management of patients. We describe a clinically useful lipoprotein phenotyping system that is only dependent upon the standard lipid panel. It, therefore, can be easily implemented for increasing compliance with current guidelines and for improving the care of patients at risk for ASCVD.