Stratification of candidate genes for Parkinson's disease using weighted protein-protein interaction network analysis.

ABSTRACT:

Background

Genome wide association studies (GWAS) have helped identify large numbers of genetic loci that significantly associate with increased risk of developing diseases. However, translating genetic knowledge into understanding of the molecular mechanisms underpinning disease (i.e. disease-specific impacted biological processes) has to date proved to be a major challenge. This is primarily due to difficulties in confidently defining candidate genes at GWAS-risk loci. The goal of this study was to better characterize candidate genes within GWAS loci using a protein interactome based approach and with Parkinson's disease (PD) data as a test case.

Results

We applied a recently developed Weighted Protein-Protein Interaction Network Analysis (WPPINA) pipeline as a means to de

SUBMITTER: Ferrari R 

PROVIDER: S-EPMC6000968 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature