Abstract

BackgroundFrom genome wide association studies on Alzheimer’s disease (AD), it has been shown that many single nucleotide polymorphisms (SNPs) of genes of different pathways affect the disease risk. One of the pathways is endocytosis, and variants in these genes may affect their functions in amyloid precursor protein (APP) trafficking, amyloid-beta (Aβ) production as well as its clearance in the brain. This study uses computational methods to predict the effect of novel SNPs, including untranslated region (UTR) variants, splice site variants, synonymous SNPs (sSNPs) and non-synonymous SNPs (nsSNPs) in three endocytosis genes associated with AD, namely PICALM, SYNJ1 and SH3KBP1.Materials and MethodsAll the variants’ information was retrieved from the Ensembl genome database, and then different variation prediction analyses were performed. UTRScan was used to predict UTR variants while MaxEntScan was used to predict splice site variants. Meta-analysis by PredictSNP2 was used to predict sSNPs. Parallel prediction analyses by five different software packages including SIFT, PolyPhen-2, Mutation Assessor, I-Mutant2.0 and SNPs&GO were used to predict the effects of nsSNPs. The level of evolutionary conservation of deleterious nsSNPs was further analyzed using ConSurf server. Mutant protein structures of deleterious nsSNPs were modelled and refined using SPARKS-X and ModRefiner for structural comparison.ResultsA total of 56 deleterious variants were identified in this study, including 12 UTR variants, 18 splice site variants, eight sSNPs and 18 nsSNPs. Among these 56 deleterious variants, seven variants were also identified in the Alzheimer’s Disease Sequencing Project (ADSP), Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Mount Sinai Brain Bank (MSBB) studies.DiscussionThe 56 deleterious variants were predicted to affect the regulation of gene expression, or have functional impacts on these three endocytosis genes and their gene products. The deleterious variants in these genes are expected to affect their cellular function in endocytosis and may be implicated in the pathogenesis of AD as well. The biological consequences of these deleterious variants and their potential impacts on the disease risks could be further validated experimentally and may be useful for gene-disease association study.

Highlights

  • Alzheimer’s disease (AD) is the most common type of dementia

  • The single nucleotide polymorphisms (SNPs) datasets of PICALM, SYNJ1 and SH3KBP1 genes were retrieved from the Ensembl genome database

  • Out of the 399 synonymous SNPs (sSNPs) we studied, eight sSNPs were predicted as deleterious sSNPs in PredictSNP2, including five from PICALM gene and three from SYNJ1 gene

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Summary

Introduction

Alzheimer’s disease (AD) is the most common type of dementia. According to the amyloid hypothesis, amyloid-beta (Aβ) is the primary factor to initiate a pathogenic cascade of AD in the brain (see review in Du, Wang & Geng (2018)). Endocytosis is one of the biological pathways affecting APP trafficking and many endocytosis genes, including BIN1, CD2AP, PICALM, EPHA1 and SORL1 were identified as AD-associated in genome wide association study (GWAS) and other genetic studies (see review in Giri, Zhang & Lü (2016)). From genome wide association studies on Alzheimer’s disease (AD), it has been shown that many single nucleotide polymorphisms (SNPs) of genes of different pathways affect the disease risk. One of the pathways is endocytosis, and variants in these genes may affect their functions in amyloid precursor protein (APP) trafficking, amyloid-beta (Aβ) production as well as its clearance in the brain. This study uses computational methods to predict the effect of novel SNPs, including untranslated region (UTR) variants, splice site variants, synonymous SNPs (sSNPs) and non-synonymous SNPs (nsSNPs) in three endocytosis genes associated with AD, namely PICALM, SYNJ1 and SH3KBP1. The biological consequences of these deleterious variants and their potential impacts on the disease risks could be further validated experimentally and may be useful for genedisease association study

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