Premium
Novel methods for integration and visualization of genomics and genetics data in Alzheimer's disease
Author(s) -
Bihlmeyer Nathan A.,
Merrill Emily,
Lambert Yann,
Srivastava Gyan P.,
Clark Timothy W.,
Hyman Bradley T.,
Das Sudeshna
Publication year - 2019
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2019.01.011
Subject(s) - genomics , computational biology , disease , biology , human genetics , omics , bioinformatics , gene , genome , genetics , medicine , pathology
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.