Abstract
Purpose :
The disease etiology of age-related macular degeneration (AMD) is largely unknown. We aimed to identify biological pathways, gene and protein interactions, protein families, and regulatory regions consistently enriched for genetic variations nominally associated with AMD.
Methods :
We performed pathway analysis using the Pathway Analysis by Randomization Incorporating Structure (PARIS, V2.4) software tool on 445,115 common and rare variants genotyped as a part of the International AMD Genomics Consortium (IAMDGC). The samples used to generate these data were from 16,144 advanced AMD cases and 17,832 controls. PARIS groups variants into features based on linkage disequilibrium and assigns significance to a pathway based on permutations of the genome. We performed 10,000 permutations. A feature was considered significant if it contained at least one variant with p-value<0.05. To acquire a more comprehensive understanding of which curated biological and genomic entities contribute to AMD risk, we performed PARIS using multiple biological function databases including KEGG, Reactome, GO, NetPath, BioGRID, MINT, Pfam, and ORegAnno. Entities with p-value<0.0001 were prioritized for further investigation.
Results :
Preliminary results confirmed several pathways previously implicated in AMD, including the complement cascade, Wnt signaling, and inflammation pathways. Genes previously implicated in the pathogenesis of AMD, such as SYN3, were consistently enriched for significant interactions and regulatory regions identified by PARIS. Preliminary results also showed that 2 genes, PLCG2 and CYP1A1, had significant signals across multiple immune, metabolic, and signaling pathways among the NetPath, KEGG, and Reactome databases. These anchor genes nominate multiple biological pathways and processes in the etiology of AMD.
Conclusions :
Variants potentially associated with AMD were enriched in multiple metabolic, signaling, and inflammatory pathways. Further examination is underway to identify the “driver” genes among these phenomena and determine how they may be contributing to AMD pathophysiology. This analysis highlights how the combination of genome-wide genotyping and statistical pathway analysis incorporating in silico functional data can be used to elucidate the genetic architecture of complex ocular diseases like AMD.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.