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The Lipoprotein Profile Evaluated by 1H-NMR Improves the Performance of Genetic Testing in Familial Hypercholesterolemia.
Ibarretxe, Daiana; Llop, Dídac; Rodríguez-Borjabad, Cèlia; Andreychuk, Natalia; Plana, Núria; Scicali, Roberto; González-Lleó, Ana; Amigó, Núria; Girona, Josefa; Masana, Lluís.
Afiliação
  • Ibarretxe D; Unitat Medicina Vascular I Metabolisme. Unitat de Recerca en Lípids i Arteriosclerosi. Hospital Universitari Sant Joan. Universitat Rovira i Virgili. IISPV. Reus. Spain.
  • Llop D; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
  • Rodríguez-Borjabad C; Unitat Medicina Vascular I Metabolisme. Unitat de Recerca en Lípids i Arteriosclerosi. Hospital Universitari Sant Joan. Universitat Rovira i Virgili. IISPV. Reus. Spain.
  • Andreychuk N; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
  • Plana N; Unitat Medicina Vascular I Metabolisme. Unitat de Recerca en Lípids i Arteriosclerosi. Hospital Universitari Sant Joan. Universitat Rovira i Virgili. IISPV. Reus. Spain.
  • Scicali R; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
  • González-Lleó A; Unitat Medicina Vascular I Metabolisme. Unitat de Recerca en Lípids i Arteriosclerosi. Hospital Universitari Sant Joan. Universitat Rovira i Virgili. IISPV. Reus. Spain.
  • Amigó N; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
  • Girona J; Unitat Medicina Vascular I Metabolisme. Unitat de Recerca en Lípids i Arteriosclerosi. Hospital Universitari Sant Joan. Universitat Rovira i Virgili. IISPV. Reus. Spain.
  • Masana L; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain.
Article em En | MEDLINE | ID: mdl-38262691
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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article