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A 3-fold kernel approach for characterizing Late Onset Alzheimer’s Disease

The purpose of this study is to identify a global and robust signature characterizing Alzheimer’s Disease (AD). Two public GWAS datasets were analyzed considering a 3-fold kernel approach, based on SNPs, Genes and Pathways analysis, and two binary classifications tasks were addressed: cases@controls and APOE4 task. In the SNP signature of the ADNI-1 and ADNI-2 datasets, chromosome 19 and 20 reached high classification accuracy. In addition, the functional characterization of ADNI-1 and ADNI-2 SNP signatures found enriched the same pathway (i.e., Neuroactive ligand-receptor interaction), with GRM7 gene in common with both. TOMM40 was confirmed linked to AD pathology by SNP, gene and pathway-based analyses in ADNI-1. Using this 3-fold kernel approach, a peculiar signature of SNPs, genes and pathways has been highlighted in both datasets. Based on these significant results, we retain such approach a valuable tool to elucidate the heritable susceptibility to AD but also to other similar complex diseases.