June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
A Systems Genetics Approach to More Effectively Model Age-Related Macular Degeneration (AMD)
Author Affiliations & Notes
  • TJ Hollingsworth
    Hamilton Eye Institute, University of Tennessee Health Science Center, Memphis, Tennessee, United States
  • Anand Swaroop
    National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States
  • Emily Chew
    National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States
  • David Ashbook
    Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, United States
  • Robert Williams
    Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, United States
  • Monica M Jablonski
    Hamilton Eye Institute, University of Tennessee Health Science Center, Memphis, Tennessee, United States
  • Footnotes
    Commercial Relationships   TJ Hollingsworth, None; Anand Swaroop, None; Emily Chew, None; David Ashbook, None; Robert Williams, None; Monica Jablonski, None
  • Footnotes
    Support  Catalyst Award for Innovative Research Approaches for Age-Related Macular Degeneration, Research to Prevent Blindness, New York, NY
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 2277. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      TJ Hollingsworth, Anand Swaroop, Emily Chew, David Ashbook, Robert Williams, Monica M Jablonski; A Systems Genetics Approach to More Effectively Model Age-Related Macular Degeneration (AMD). Invest. Ophthalmol. Vis. Sci. 2020;61(7):2277.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : Creating animal models recapitulating the degenerative phenotypes of AMD is very difficult due to the plethora of heterogeneities associated with the disease including genetic variations in many genes involved in different functional aspects (i.e. immunity, lipid processing, etc.) and environmental factors known to play a role in the disease onset and progression such as age, smoking, and diet. Herein, we report on the use of a systems genetics approach applied to the BXD mouse family to identify spontaneous polygenetic models that more accurately depict disease pathology.

Methods : Genes with an association to AMD diagnosis were assessed to have the following inclusion criteria: single nucleotide polymorphisms (SNPs) with a functional impact; cis-eQTL regulation; differential expression between both C57BL/6J (B6) and DBA/2J (D2) parental strains. All BXD strains were assessed for D2 haplotypes in AMD-associated genes. Only strains with Tyrp1 and Gpnmb B6 haplotypes are included in our analyses to remove the pigmentary dispersion glaucoma phenotype.

Results : Of AMD-associated genes, only four fulfilled our inclusion criteria: complement factors H (Cfh) and I (Cfi), retinaldehyde binding protein 1 (Rlbp1), and syndecan 2 (Sdc2). Preliminary data from BXD mice containing D2 haplotypes for both Cfh and Cfi reveal the combined genetic variations produce an ultrastructural AMD-like phenotype that is more pronounced than either gene alone including larger and more numerous basolaminar deposits, increased RPE vacuoles and undigested phagosomes. The strains selected will be aged to 18 months and in vivo anatomical and functional tests performed.

Conclusions : Several AMD-associated SNPs segregate in the BXD family of mice. Our data show particular SNP combinations yield AMD-like pathology while others do not. In direct support for this experimental approach, recent evidence suggests that genetic variation at multiple AMD risk alleles yields a better indication of disease susceptibility, supporting our hypothesis that multiple risk alleles work synergistically to exacerbate human AMD pathophysiology. The outcomes of these studies will provide unique AMD models to the vision research community, greatly facilitating the quest for a deeper understanding of disease mechanisms and the development of novel targeted therapies to halt the progression of vision loss in AMD.

This is a 2020 ARVO Annual Meeting abstract.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×