Network-based identification of genetic factors in Ageing, lifestyle and Type 2 Diabetes that Influence in the progression of Alzheimer’s disease

Abstract

MotivationAlzheimers disease (AD) is currently incurable and the causative risk factors are still poorly understood, which impedes development of effective prevention and treatment strategies. We propose a network-based quantitative framework to reveal details of the complex interaction between the various genetic contributors to AD susceptibility. We analyzed gene expression microarray data from tissues affected by AD, advanced ageing, high alcohol consumption, type II diabetes, high body fat, high dietary fat, obesity, high dietary red meat intake, sedentary lifestyle, smoking, and control datasets. We developed genetic associations and diseasome networks for these factors and AD using the neighborhood-based benchmarking and multilayer network topology approaches.\n\nResultsThe study identified 484 genes differentially expressed between AD and controls. Among these, 27 genes showed elevated expression both in individuals in AD and in smoker datasets; similarly 21 were observed in AD and type II diabetes datasets and 12 for AD and sedentary lifestyle datsets. However, AD shared less than ten such elevated expression genes with other factors examined. 3 genes, namely HLA-DRB4, IGH and IGHA2 showed increased expression among the AD, type II diabetes and alcohol consumption datasets; 2 genes, IGHD and IGHG1, were commonly up-regulated among the AD, type II diabetes, alcohol consumption and sedentary lifestyle datasets. Protein-protein interaction networks identified 10 hub genes: CREBBP, PRKCB, ITGB1, GAD1, GNB5, PPP3CA, CABP1, SMARCA4, SNAP25 and GRIA1. Ontological and pathway analyses genes, including Online Mendelian Inheritance in Man (OMIM) and dbGaP databases were used for gold benchmark gene-disease associations to validate the significance of these putative target genes of AD progression.\n\nConclusionOur network-based methodologies have uncovered molecular pathways that may influence AD development, suggesting novel mechanisms that contribute to AD risk and which may form the basis of new therapeutic and diagnostic approaches.\n\nContactmohammad.moni@sydney.edu.au