The Lipoprotein Profile Evaluated by 1H-NMR Improves the Performance of Genetic Testing in Familial Hypercholesterolemia

Abstract

Background: The familial hypercholesterolemia (FH) diagnosis is based on clinical and genetic criteria. A relevant proportion of FH patients fulfilling the criteria for definite FH have negative genetic testing. Increasing the identification of true genetic-based FH is a clinical challenge. Deepening the analysis of lipoprotein alterations could help increase the yield of genetic testing. We evaluated whether the number, size, and composition of lipoproteins assessed by 1H-NMR could increase the identification of FH patients with pathogenic gene variants.

Methods: We studied 294 clinically definite FH patients, 222 (75.5%) with positive genetic testing, as the discovery cohort. As an external validation cohort, we studied 88 children with FH, 72 (81%) with positive genetic testing. The advanced lipoprotein test based on 1H-NMR (Liposcale®) was performed at baseline after a lipid-lowering drug wash-out of at least 6 weeks. The association of variables with genetic variants was evaluated by random forest and logistic regression. Areas under the curve (AUCs) were calculated. A predictive formula was developed and applied to the validation cohort.

Results: A formula derived from NMR lipoprotein analyses improved the identification of genetically positive FH patients beyond LDL-C levels (AUC=0.87). The parameters contributing the most to the identification formula were LDL particle number, HDL size and remnant cholesterol. The formula also increases the classification of FH children with a pathogenic genetic variation.

Conclusions: NMR lipoprotein profile analysis identifies differences beyond standard lipid parameters that help identify FH with a positive pathogenic gene variant, increasing the yield of genetic testing in FH patients.

Keywords: cardiovascular risk; familiar hypercholesterolemia; genetic testing; machine learning; nuclear magnetic resonance.