July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
Pathway analysis identifies PLCG2 as a candidate gene for age-related macular degeneration
Author Affiliations & Notes
  • Andrea R Waksmunski
    Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States
    Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States
  • Michelle Grunin
    Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States
  • Tyler Kinzy
    Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States
  • Robert P. Igo
    Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States
  • Jonathan L Haines
    Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States
    Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States
  • Jessica Cooke Bailey
    Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States
    Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States
  • Footnotes
    Commercial Relationships   Andrea Waksmunski, None; Michelle Grunin, None; Tyler Kinzy, None; Robert Igo, None; Jonathan Haines, None; Jessica Cooke Bailey, None
  • Footnotes
    Support  1X01HG006934-01 and R01 EY022310
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 2959. doi:
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      Andrea R Waksmunski, Michelle Grunin, Tyler Kinzy, Robert P. Igo, Jonathan L Haines, Jessica Cooke Bailey; Pathway analysis identifies PLCG2 as a candidate gene for age-related macular degeneration. Invest. Ophthalmol. Vis. Sci. 2019;60(9):2959.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Age-related macular degeneration (AMD) is the third-leading cause of blindness in the world. Although at least 52 independent genomic variants associated with advanced AMD have been detected by genome-wide association studies (GWAS), nearly one-third of its heritability is still unexplained. We hypothesize that pathway analysis integrating genetic and biological data may further elucidate the genetic etiology of AMD.

Methods : We performed a knowledge-driven pathway analysis using Pathway Analysis by Randomization Incorporating Structure (PARIS) on the association statistics from the 2016 advanced AMD GWAS performed by the International AMD Genomics Consortium. The knowledge sources for our analyses included the KEGG, Reactome, GO, and NetPath databases. We identified statistical driver genes that exhibited significant signals within significant pathways in these databases. Using MEME, we searched for DNA sequence motifs that were present for the majority of our statistical driver genes and have known transcription factor binding sites to elucidate if they are under the influence of a master regulator.

Results : We found evidence for known AMD-related pathways, such as the complement cascade and small molecule transport, and support for novel pathways, such as B cell receptor signaling and natural killer cell mediated cytotoxicity. Eight genes (C2, C3, LIPC, MICA, PPARA, PLCG2, NOTCH4, and RAD51B) strongly contributed to significant KEGG, Reactome, and GO pathway associations. Five motifs were present for most of these statistical driver genes and contained known transcription factor binding sites, which may suggest that their expression is similarly regulated. Of these eight genes, only PLCG2 strongly contributed to associated pathways from all four pathway databases. This gene encodes a signaling enzyme implicated in Alzheimer’s disease and involved in the VEGF pathway, which may indicate a possible role in the choroidal neovascularization subtype of AMD.

Conclusions : We determined that several immune, metabolic, and signaling pathways were associated with AMD. Statistical signals for these pathways converged on eight statistical driver genes that may be controlled by similar transcriptional mechanisms. Of these genes, we identified PLCG2 as a promising candidate gene for AMD. Our data reinforce known AMD pathologies and implicate novel pathways and genes that may serve as therapeutic targets for AMD.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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