Published in
Public Library of Science, PLoS Genetics, 2(11), p. e1004855, 2015
DOI: 10.1371/journal.pgen.1004855
Links
- ORCID
- ORCID
- Public Library of Science
- [www.ncbi.nlm.nih.gov] | PDF
- [doaj.org] | PDF
- [dash.harvard.edu] | PDF
- [dspace.mit.edu] | PDF
- [europepmc.org] | PDF
- [www.researchgate.net] | PDF
- [www.ncbi.nlm.nih.gov] | PDF
- [www.ncbi.nlm.nih.gov] | PDF
Tools
Systematic Cell-Based Phenotyping of Missense Alleles Empowers Rare Variant Association Studies: A Case for LDLR and Myocardial Infarction
,
Pier Angelica Merlini,
Diego Ardissino,
Eric S. Lander,
Stacey Gabriel,
Daniel J. Rader,
Gina M. Peloso,
Rainer Pepperkok
and other authors.
Full text: Download
Abstract
A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants in vitro. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (LDLR) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare LDLR allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude.