Development of a novel prediction model based on protein structure for identifying RPE65-associated inherited retinal disease (IRDs) of missense variants

Abstract

Purpose This study aimed to develop a prediction model to classify RPE65-mediated inherited retinal disease (IRDs) based on protein secondary structure and to analyze phenotype-protein structure correlations of RPE65 missense variants in a Chinese cohort. Methods Pathogenic or likely pathogenic missense variants of RPE65 were obtained from UniProt, ClinVar, and HGMD databases. The three-dimensional structure of RPE65 was retrieved from the Protein Data Bank (PDB) and modified with Pymol software. A novel prediction model was developed using LASSO regression and multivariate logistic regression to identify RPE65-associated IRDs. A total of 21 Chinese probands with RPE65 variants were collected to analyze phenotype-protein structure correlations of RPE65 missense variants. Results The study found that both pathogenic and population missense variants were associated with structural features of RPE65. Pathogenic variants were linked to sheet, β-sheet, strands, β-hairpins, Fe2+ (iron center), and active site cavity, while population variants were related to helix, loop, helices, and helix–helix interactions. The novel prediction model showed accuracy and confidence in predicting the disease type of RPE65 variants (AUC = 0.7531). The study identified 25 missense variants in Chinese patients, accounting for 72.4% of total mutations. A significant correlation was observed between clinical characteristics of RPE65-associated IRDs and changes in amino acid type, specifically for missense variants of F8 (H68Y, P419S). Conclusion The study developed a novel prediction model based on the protein structure of RPE65 and investigated phenotype-protein structure correlations of RPE65 missense variants in a Chinese cohort. The findings provide insights into the precise diagnosis of RPE65-mutated IRDs.