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. 2024 Oct 15;109(11):e2090-e2099.
doi: 10.1210/clinem/dgae037.

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

Ibarretxe Daiana  1   2 , Llop Dídac  1   2 , Rodríguez-Borjabad Cèlia  1   2 , Andreychuk Natalia  1   2 , Plana Núria  1   2 , Scicali Roberto  3 , González-Lleó Ana  1   2 , Amigó Núria  4   5   2 , Girona Josefa  1   2 , Masana Lluís  1   2
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The Lipoprotein Profile Evaluated by 1H-NMR Improves the Performance of Genetic Testing in Familial Hypercholesterolemia

Ibarretxe Daiana et al. J Clin Endocrinol Metab. .

Erratum in

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 washout 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 nuclear magnetic resonance (NMR) lipoprotein analyses improved the identification of genetically positive FH patients beyond low-density lipoprotein (LDL)-cholesterol levels (AUC = 0.87). The parameters contributing the most to the identification formula were LDL particle number, high-density lipoprotein size, and remnant cholesterol. The formula also increases the classification of FH children with a pathogenic genetic variation.

Conclusion: 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.

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