Abstract
Genome–wide association studies (GWAS) have revealed a plethora of putative susceptibility genes for Alzheimer’s disease (AD), with the sole exception of APOE gene unequivocally validated in independent study. Considering that the etiology of complex diseases like AD could depend on functional multiple genes interaction network, here we proposed an alternative GWAS analysis strategy based on (i) multivariate methods and on a (ii) telescope approach, in order to guarantee the identification of correlated variables, and reveal their connections at three biological connected levels. Specifically as multivariate methods, we employed two machine learning algorithms and a genetic association test and we considered SNPs, Genes and Pathways features in the analysis of two public GWAS dataset (ADNI-1 and ADNI-2). For each dataset and for each feature we addressed two binary classifications tasks: cases vs. controls and the low vs. high risk of developing AD considering the allelic status of APOEe4. This complex strategy allowed the identification of SNPs, genes and pathways lists statistically robust and meaningful from the biological viewpoint. Among the results, we confirm the involvement of TOMM40 gene in AD and we propose GRM7 as a novel gene significantly associated with AD.
Highlights
Alzheimer’s disease (AD) is the predominant form of dementia (50–75%) in the elderly population
In the Results section we show the signatures of SNPs, genes and pathways identified considering both the binary classification tasks, cases@controls and APOEe4, while in the discussion we comment the obtained results considering the possible integration of the signatures across the SNPs, genes and pathways levels and across Alzheimer’s Disease Neuroimaging Initiative (ADNI)-1 and ADNI-2 dataset that we analyzed separately and considering only the genotype SNPs
Genome–wide association studies (GWAS) studies have revealed a plethora of putative susceptibility genes for AD, APOE gene is the sole exception unequivocally validated in independent studies
Summary
Alzheimer’s disease (AD) is the predominant form of dementia (50–75%) in the elderly population. The first well known gene associated to LOAD was APOE3 It encodes three known isoforms proteins (APOE2, APOE3 and APOE4), with APOE4 known to increase risk in familial and sporadic EOAD. Coexist: AD could be caused by the concerted action of independent genetic factors, each having a small effect size that require to adopt multivariate methods and to increase sample s ize[5]; or it could be caused by the concerted actions of multiple genes (again characterized by low effect size) that act inter-dependently in still undefined pathways, that would need a pathway-based approach, as done for other complex diseases[6]. In order to explore the first two possible scenarios, in this study we proposed an alternative GWAS analysis strategy based on (i) multivariate methods and on (ii) a SNPs-Genes-Pathways ensamble, in order to guarantee the identification of correlated variables, and reveal the possible connections existing among the identified relevant variables at different, but biologically connected levels
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