Highlights
- •A total of 13,167 single amino acid missense substitutions in LDLR were modeled, in which 10,490 substitutions predicted FH pathogenicity with functional impact predictions.
- •52 out of all 54 reported experimentally-tested LDLR variants were consistent with our predictions.
- •Three newly-identified FH-causing LDLR variants in patients and two novel benign variants validated our model predictions experimentally.
- •This is the first to systematically predict pathogenic LDLR single amino acid missense substitutions with corresponding functional characteristics.
Abstract
Background and aims
Familial hypercholesterolemia (FH) is a an autosomal dominant disorder characterized
by very high levels of low-density lipoprotein cholesterol (LDL-C). It is estimated
that >85% of all FH-causing mutations involve genetic variants in the LDL receptor
(LDLR). To date, 795 single amino acid LDLR missense mutations have been reported in the Leiden Open Variation Database (LOVD).
However, the functional impact of these variants on the LDLR pathway has received
little attention and remains poorly understood. We aim to establish a systematic functional
prediction model for LDLR single missense mutations.
Methods
Using a combined structural modeling and bioinformatics algorithm, we developed an
in silico prediction model called “Structure-based Functional Impact Prediction for Mutation
Identification” (SFIP-MutID) for FH with LDLR single missense mutations. We compared the pathogenicity and functional impact predictions
of our model to those of other conventional tools with experimentally validated variants,
as well as in vitro functional test results for patients with LDLR variants.
Results
Our SFIP-MutID model systematically predicted 13,167 potential LDLR single amino acid missense substitutions with biological effects. The functional
impact of 52 out of 54 specific mutations with reported in vitro experimental data was predicted correctly. Further functional tests on LDLR variants
from patients were also consistent with the prediction of our model.
Conclusions
Our LDLR structure-based computational model predicted the pathogenicity of LDLR missense mutations by linking genotypes with LDLR functional phenotypes. Our model
complements other prediction tools for variant interpretation and facilitates the
precision diagnosis and treatment of FH and atherosclerotic cardiovascular diseases.
Graphical abstract
Graphical Abstract
Keywords
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Article Info
Publication History
Published online: December 15, 2018
Accepted:
December 4,
2018
Received in revised form:
November 26,
2018
Received:
May 18,
2018
Identification
Copyright
© 2018 Elsevier B.V. All rights reserved.
