Novel methods for integration and visualization of genomics and genetics data in Alzheimer's disease

Abstract

Introduction: Numerous omics studies have been conducted to understand the molecular networks involved in Alzheimer's disease (AD), but the pathophysiology is still not completely understood; new approaches that enable neuroscientists to better interpret the results of omics analysis are required.

Methods: We have developed advanced methods to analyze and visualize publicly-available genomics and genetics data. The tools include a composite clinical-neuropathological score for defining AD, gene expression maps in the brain, and networks integrating omics data to understand the impact of polymorphisms on AD pathways.

Results: We have analyzed over 50 public human gene expression data sets, spanning 19 different brain regions and encompassing three separate cohorts. We integrated genome-wide association studies with expression data to identify important genes in the pathophysiology of AD, which provides further insight into the calcium signaling and calcineurin pathways.

Discussion: Biologists can use these freely-available tools to obtain a comprehensive, information-rich view of the pathways in AD.

Keywords: Alzheimer's disease; Calcineurin; Calcium signaling pathway; Data visualization; Genomics; PTK2B; TOMM40.