The functional landscape of coding variation in the familial hypercholesterolemia gene LDLR.


Journal article


Daniel R Tabet, (....), M. Bourbon, S. Pfisterer, (...), Frederick P. Roth
Science, 2025

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APA   Click to copy
Tabet, D. R., (....), Bourbon, M., Pfisterer, S., (...), & Roth, F. P. (2025). The functional landscape of coding variation in the familial hypercholesterolemia gene LDLR. Science.


Chicago/Turabian   Click to copy
Tabet, Daniel R, (....), M. Bourbon, S. Pfisterer, (...), and Frederick P. Roth. “The Functional Landscape of Coding Variation in the Familial Hypercholesterolemia Gene LDLR.” Science (2025).


MLA   Click to copy
Tabet, Daniel R., et al. “The Functional Landscape of Coding Variation in the Familial Hypercholesterolemia Gene LDLR.” Science, 2025.


BibTeX   Click to copy

@article{daniel2025a,
  title = {The functional landscape of coding variation in the familial hypercholesterolemia gene LDLR.},
  year = {2025},
  journal = {Science},
  author = {Tabet, Daniel R and (....) and Bourbon, M. and Pfisterer, S. and (...) and Roth, Frederick P.}
}

Abstract

Variants in the familial hypercholesterolemia gene LDLR-the most important genetic driver of cardiovascular disease-can raise circulating low-density lipoprotein (LDL) cholesterol concentrations and increase the risk of premature atherosclerosis. Definitive classifications are lacking for nearly half of clinically encountered LDLR missense variants, limiting interventions that reduce disease burden. Here, we tested the impact of ~17,000 (nearly all possible) LDLR missense coding variants on both LDLR cell-surface abundance and LDL uptake, yielding sequence-function maps that recapitulate known biochemistry, offer functional insights, and provide evidence for interpreting clinical variants. Functional scores correlated with hyperlipidemia phenotypes in prospective human cohorts and augmented polygenic scores to improve risk inference, highlighting the potential of this resource to accelerate familial hypercholesterolemia diagnosis and improve patient outcomes.