In silico modeling of pathogenic point mutations in APP, PSEN1 and PSEN2 in Asia

Abstract

AbstractBackgroundAlzheimer’s disease (AD), the most common form of senile dementia, is a genetically complex disorder. In most Asian countries, the population and the number of AD patients are growing rapidly, and the genetics of AD has been extensively studied. Amyloid protein precursor (APP), presenilin‐1 (PSEN1), and presenilin‐2 (PSEN2) mutations cause autosomal dominant forms of early‐onset Alzheimer disease (EOAD). Although these genes were identified in the last several decades, variant classification remains a challenge, highlighting the need to elucidate their role in neuropathologic features of autosomal dominant ADAD.MethodWe tested the performance of four prediction tools (Align‐GVGD, SIFT, PolyPhen‐2, MutationTaster2) using a set of 50 missense variants that had previously been reported. Finally, 3‐D modeling was also performed for all mutations.ResultWe summarized substitution mutations in the APP, PSEN1 and PSEN2 genes in Asia and attempted to identify pathogenic mutations using Align‐GVGD, SIFT, PolyPhen‐2, MutationTaster2, and 3‐D structure analysis techniques. Most of the mutations were confirmed as pathogenic mutations by these algorithms.ConclusionOur results contribute to a better understanding of the behavior of the mutations and their pathogenic nature process, which is necessary to understand AD pathogenesis. Following this work, some potential mutations would be chosen and further checked out their pathogenicity of in AD through cellular studies.