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Open Access 10-05-2023 | Original Article

Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease

Authors: Sudharsana Sundarrajan, Arthi Venkatesan, Udhaya Kumar S, Mohanraj Gopikrishnan, Iftikhar Aslam Tayubi, M Aditya, Gowrishankar Bychapur Siddaiah, C. George Priya Doss, Hatem Zayed

Published in: Metabolic Brain Disease | Issue 6/2023

Abstract

Alzheimer disease (AD) is a leading cause of dementia in elderly patients who continue to live between 3 and 11 years of diagnosis. A steep rise in AD incidents is observed in the elderly population in East-Asian countries. The disease progresses through several changes, including memory loss, behavioural issues, and cognitive impairment. The etiology of AD is hard to determine because of its complex nature. The whole exome sequences of late-onset AD (LOAD) patients of Korean origin are investigated to identify rare genetic variants that may influence the complex disorder. Computational annotation was performed to assess the function of candidate variants in LOAD. The in silico pathogenicity prediction tools such as SIFT, Polyphen-2, Mutation Taster, CADD, LRT, PROVEAN, DANN, VEST3, fathmm-MKL, GERP + + , SiPhy, phastCons, and phyloP identified around 17 genes harbouring deleterious variants. The variants in the ALDH3A2 and RAD54B genes were pathogenic, while in 15 other genes were predicted to be variants of unknown significance. These variants can be potential risk candidates contributing to AD. In silico computational techniques such as molecular docking, molecular dynamic simulation and steered molecular dynamics were carried out to understand the structural insights of RAD54B with ATP. The simulation of mutant (T459N) RAD54B with ATP revealed reduced binding strength of ATP at its binding site. In addition, lower binding free energy was observed when compared to the wild-type RAD54B. Our study shows that the identified uncommon variants are linked to AD and could be probable predisposing genetic factors of LOAD.

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Title: Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease
Authors: Sudharsana Sundarrajan
Arthi Venkatesan
Udhaya Kumar S
Mohanraj Gopikrishnan
Iftikhar Aslam Tayubi
M Aditya
Gowrishankar Bychapur Siddaiah
C. George Priya Doss
Hatem Zayed
Publication date: 10-05-2023
Publisher: Springer US
Published in: Metabolic Brain Disease / Issue 6/2023
Print ISSN: 0885-7490
Electronic ISSN: 1573-7365
DOI: https://doi.org/10.1007/s11011-023-01221-7

Keynote webinar | Spotlight on medication adherence

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Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease

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Keynote webinar | Spotlight on medication adherence

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