Key result
High-throughput functional characterization successfully reclassifies 20 LDLR variants of uncertain significance.
Why the study?
A substantial proportion of familial hypercholesterolaemia variants remain classified as variants of uncertain significance, creating a critical gap in genetic diagnosis and patient management.
Does a high-throughput functional classification pipeline enable the clinical re-interpretation of LDLR variants of uncertain significance in familial hypercholesterolaemia?
Does a high-throughput functional classification pipeline enable the clinical re-interpretation of LDLR variants of uncertain significance in familial hypercholesterolaemia?
High-throughput functional characterization of LDLR variants can successfully reclassify variants of uncertain significance, reducing diagnostic uncertainty in familial hypercholesterolaemia.
Answers are grounded in this paper and cite their sources.
May reduce diagnostic uncertainty in familial hypercholesterolaemia with LDLR VUS; extends high-throughput functional characterization for variant reclassification.
Background Familial hypercholesterolaemia (FH) is the most common autosomal disorder of lipid metabolism, affecting approximately 1 in 300 individuals. FH is characterised by markedly elevated plasma cholesterol levels from birth, predisposing to premature atherosclerotic cardiovascular disease. The identification of a pathogenic variant in a causative gene provides a definitive diagnosis and enables cascade screening of family members. However, a substantial proportion of FH variants remain classified as variants of uncertain significance (VUS), creating a critical gap in genetic diagnosis and patient management. Purpose This study is part of the PerMedFH projet and aims to implement a high-throughput pipeline for the functional classification of LDLR variants, thereby enabling their clinical re-interpretation and integration into diagnostic practice. Methods Selected LDLR variants were divided into two groups: a validation set and a test set. The validation group included 7 variants previously classified as benign/likely benign and 50 variants previously classified as pathogenic/likely pathogenic. The test group comprised 131 VUS with no prior functional assessment. Functional activity was evaluated using an automated analysis platform based on multiplexed high-content imaging to quantify LDL uptake, as described previously (1). Variant classification followed FH VCEP LDLR-specific guidelines (2). Results In total, 187 LDLR variants were analysed. In the validation group, 44 variants demonstrated completely concordant results with previous classifications, 8 fell within an intermediate "grey zone" (70–90% LDL uptake), and only 5 pathogenic variants were discordant. This yielded a sensitivity of 88.4%, specificity and precision of 100%, and overall accuracy of 78.9%.. Among the test group, 51 variants exhibited <70% of wild-type LDL uptake, 41 showed >90% of wild-type uptake, and 39 fell into the intermediate range, requiring additional functional studies. Integrating these findings with other ACMG/AMP evidence codes, 47 variants were considered “hot VUS”, amenable to reclassification. Of these, 9 were reclassified as likely benign and 11 as likely pathogenic. Conclusions This large-scale functional study of LDLR variants demonstrates the feasibility and clinical utility of integrating high-throughput functional evidence with high accuracy into variant interpretation. The ability to reclassify previously unresolved VUS represents a major step forward in reducing diagnostic uncertainty in FH. The PerMedFH project paves the way for a personalised medicine approach in FH, improving diagnostic precision, and ultimately enhancing patient care and cardiovascular outcomes.
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Islam et al. (2026) studied this question. High-throughput functional characterization of LDLR variants achieved 100% specificity and 88.4% sensitivity, successfully reclassifying 20 variants of uncertain significance.
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