Asier Larrea-Sebal, Iñaki Sasiain, Shifa Jebari-Benslaiman, Unai Galicia-Garcia, Kepa B Uribe, Asier Benito-Vicente, Irene Gracia-Rubio, Harbil Bediaga-Bañeres, Sonia Arrasate, Ana Cenarro, Fernando Civeira, Humberto González-Díaz, Cesar Martín
Familial hypercholesterolemia (FH) is an inherited metabolic disease affecting cholesterol metabolism, with 90% of cases caused by mutations in the LDL receptor gene (LDLR), primarily missense mutations. This study aims to integrate six commonly used predictive software to create a new model for predicting LDLR mutation pathogenicity and mapping hot spot residues. Six predictive-software are selected: Polyphen-2, SIFT, MutationTaster, REVEL, VARITY, and MLb-LDLr. Software accuracy is tested with the characterized variants annotated in ClinVar and, by bioinformatic and machine learning techniques all models are integrated into a more accurate one...
January 23, 2024: Advanced Science (Weinheim, Baden-Wurttemberg, Germany)