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Published on: September 15, 2018
The Spectrum of Genetic Causes of Familial Hypercholesterolemia Phenotype
M Bourbon1,2, A C Alves3,4, J R Chora3,4
1Unidade de Investigação e Desenvolvimento, Grupo de Investigação Cardiovascular, Departamento de Promoção da Saúde e Prevenção de Doenças Não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, Lisbon, Portugal. mafalda.bourbon@insa.min-saude.pt.
Purpose Of Review:
This paper reviews the genetic spectrum underlying the Familial Hypercholesterolemia (FH) phenotype, aiming to improve diagnosis, awareness and understanding of these inherited lipid disorders.
Recent Findings:
Although genetic testing for FH has traditionally targeted LDLR, APOB, and PCSK9, the adoption of an expanded eight-gene sequencing panel is now recommended. This broader approach improves diagnostic accuracy by identifying additional lipid disorders that mimic the FH phenotype. Among these, sitosterolemia and the APOE variant p.(Leu167del) appear to be more prevalent than previously recognized. LDLR variants remain the predominant cause of FH, yet the functional significance of approximately half of the reported variants remains undetermined. Recent research efforts are increasing and aimed at resolving these uncertainties through functional characterization studies. Penetrance varies markedly among FH genes, with LDLR variants showing highest penetrance (> 90%), APOB intermediate (~ 50-70%), and PCSK9 is gain-of-function dependent, influencing phenotype severity. Familial hypercholesterolemia (FH) remains widely underdiagnosed and undertreated, increasing preventable cardiovascular risk. Advances in genetic testing with expanded multi-gene panels have enhanced diagnostic precision, but accurate variant classification-using ACMG guidelines and functional assays-is crucial to reduce variants of uncertain significance. Expanded FH genetic testing not only differentiates true FH from phenocopies but also strengthens the individualized management of lipid disorders. By enabling therapy to target the specific affected pathway, it represents an important step toward precision medicine and improved patient outcomes. Data sharing initiatives like PerMedFH further improve variant interpretation and clinical utility.
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