The Alzheimer's comorbidity phenome: mining from a large patient database and phenome-driven genetics prediction.

ABSTRACT:

Objective

Alzheimer's disease (AD) is a severe neurodegenerative disorder and has become a global public health problem. Intensive research has been conducted for AD. But the pathophysiology of AD is still not elucidated. Disease comorbidity often associates diseases with overlapping patterns of genetic markers. This may inform a common etiology and suggest essential protein targets. US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) collects large-scale postmarketing surveillance data that provide a unique opportunity to investigate disease co-occurrence pattern. We aim to construct a heterogeneous network that integrates disease comorbidity network (DCN) from FAERS with protein-protein interaction (PPI) to prioritize the AD risk genes using network-based

SUBMITTER: Zheng C 

PROVIDER: S-EPMC6434979 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature