Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Retinomics.org: Visualizing multi-omic spatial effects on high-resolution AI-derived retinal thickness
Julia Owen; Victoria E Jackson; Roberto Bonelli; Samaneh Farashi; Yuka Kihara; Marin Gantner; Catherine A Egan; Katie Williams; Brendan Robert E Ansell; Adnan Tufail; Melanie Bahlo; Aaron Y. Lee; Yue Wu
Author Affiliations & Notes
  • Julia Owen
    Ophthalmology, University of Washington, Seattle, Washington, United States
    The Roger and Angie Karalis Johnson Retina Center, University of Washington, Seattle, Washington, United States
  • Victoria E Jackson
    Population Health and Immunity Division, WEHI, Parkville, Victoria, Australia
    Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
  • Roberto Bonelli
    Population Health and Immunity Division, WEHI, Parkville, Victoria, Australia
    Lowy Medical Research Institute, La Jolla, California, United States
  • Samaneh Farashi
    Population Health and Immunity Division, WEHI, Parkville, Victoria, Australia
    Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
  • Yuka Kihara
    Ophthalmology, University of Washington, Seattle, Washington, United States
    The Roger and Angie Karalis Johnson Retina Center, University of Washington, Seattle, Washington, United States
  • Marin Gantner
    Lowy Medical Research Institute, La Jolla, California, United States
  • Catherine A Egan
    Moorfields Eye Hospital NHS Foundation Trust, London, London, United Kingdom
    Institute of Ophthalmology, University College London, London, United Kingdom
  • Katie Williams
    Moorfields Eye Hospital NHS Foundation Trust, London, London, United Kingdom
    Institute of Ophthalmology, University College London, London, United Kingdom
  • Brendan Robert E Ansell
    Population Health and Immunity Division, WEHI, Parkville, Victoria, Australia
    Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
  • Adnan Tufail
    Moorfields Eye Hospital NHS Foundation Trust, London, London, United Kingdom
    Institute of Ophthalmology, University College London, London, United Kingdom
  • Melanie Bahlo
    Population Health and Immunity Division, WEHI, Parkville, Victoria, Australia
    Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
  • Aaron Y. Lee
    Ophthalmology, University of Washington, Seattle, Washington, United States
    The Roger and Angie Karalis Johnson Retina Center, University of Washington, Seattle, Washington, United States
  • Yue Wu
    Ophthalmology, University of Washington, Seattle, Washington, United States
    The Roger and Angie Karalis Johnson Retina Center, University of Washington, Seattle, Washington, United States
  • Footnotes
    Commercial Relationships   Julia Owen None; Victoria Jackson None; Roberto Bonelli None; Samaneh Farashi None; Yuka Kihara None; Marin Gantner None; Catherine Egan Heidelberg Engineering, Inozyme Pharma, Code C (Consultant/Contractor), NIHR Biomedical Research Center Moorfields Eye Hospital, Lowy Medical Research Institute, Code F (Financial Support); Katie Williams None; Brendan Ansell None; Adnan Tufail 4DMT, Adverum, Annexon, Apellis, Aviceda, Boehringer Ingleheim, IvericBio, Janssen, Nanoscope, Novartis, OcuTerra, Ocular Therapeutix, Regenxbio, Roche/ Genentech, Code C (Consultant/Contractor), Bayer, Novartis , Code F (Financial Support); Melanie Bahlo Viertel Foundation Medical Advisory Board, Australian Academy of Health and Medical Sciences Australian Learned Academies, Data Internetworking Network (ALADIN) Project Steering Committee, Australian Academy of Health and Medical Sciences Reports Committee, American Epilepsy Society Basic Sciences Committee, Code S (non-remunerative); Aaron Lee Genentech / Roche, Johnson and Johnson, Boehringer Ingelheim, Code C (Consultant/Contractor), Topcon, Carl Zeiss Meditec, Code F (Financial Support), Optomed, Heidelberg, Microsoft, Amazon, Meta , Code S (non-remunerative); Yue Wu None
  • Footnotes
    Support  This research has been funded by National Institutes of Health grants K23EY029246, R01AG060942, OT2OD032644, the Latham Vision Research Innovation Award (Seattle, WA), the C. Dan and Irene Hunter Endowed Professorship, the Karalis Johnson Retina Center, and by an unrestricted grant from Research to Prevent Blindness. The sponsors or funding organizations had no role in the design or conduct of this research.
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 660. doi:
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      Julia Owen, Victoria E Jackson, Roberto Bonelli, Samaneh Farashi, Yuka Kihara, Marin Gantner, Catherine A Egan, Katie Williams, Brendan Robert E Ansell, Adnan Tufail, Melanie Bahlo, Aaron Y. Lee, Yue Wu; Retinomics.org: Visualizing multi-omic spatial effects on high-resolution AI-derived retinal thickness. Invest. Ophthalmol. Vis. Sci. 2024;65(7):660.

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

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Abstract

Purpose : We developed a free and open website (https://retinomics.org) to visualize and interact with the results of our multiple ‘Omics analyses on more than 54,000 individuals from the UK Biobank dataset. The website allows visitors to dynamically explore the relationship between retinal thickness at a micron-level resolution across the macula and ~11M SNPs, 249 metabolites, thousands of clinical diagnoses, and other -omics.

Methods : Association analyses were run for AI-derived internal limiting membrane (ILM) to retinal pigment epithelium (RPE) thickness at each retinal coordinate against multi-omic data: SNP-array (GWAS), metabolomics, ICD10 codes, hematology, infections and comorbidity, resulting in over 29,000 separate analyses. The website visualizes effect sizes and p-values across the macula with ETDRS grid for reference, as well as heatmaps, volcano and Manhattan plots using d3js. Users can search for variables by name/description or for SNP by name, location or associated gene.

Results : A total of 294 retinal genetic loci (Bonferroni corrected) were identified through GWAS analyses. SNPs rs150408004 and rs3138142 were the top two loci. LINC00461, a long non-coding RNA gene, targeted by rs150408004 is integral to the early development of Müller glial cells and astrocytes in the retina. rs3138142 is associated with RDH5, which codes for 11-cis retinol dehydrogenase 5 and is essential for night vision. Most SNPs, metabolites and other phenotypes have nonuniform effects across the macula; for example, a predominantly nasal positive effect between retinal thickness and a SNP (rs371894855) is displayed in Figure 1. In Figure 2, we show a negative effect between retinal thickness and a metabolite (lactate) in the center of the ETDRS grid and a weaker positive effect towards the periphery of the grid.

Conclusions : We developed a free and open website for dynamic exploration of multi-omics spatial analyses across the retina. The website also allows users to download the results data for further analysis.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

 

SNP page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; middle: Manhattan plot of top SNPs for a grid location and zoomed in Manhattan plot of top SNP; bottom: full Manhattan plot
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SNP page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; middle: Manhattan plot of top SNPs for a grid location and zoomed in Manhattan plot of top SNP; bottom: full Manhattan plot

SNP page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; middle: Manhattan plot of top SNPs for a grid location and zoomed in Manhattan plot of top SNP; bottom: full Manhattan plot

SNP page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; middle: Manhattan plot of top SNPs for a grid location and zoomed in Manhattan plot of top SNP; bottom: full Manhattan plot
View OriginalDownload Slide
 
Metabolite page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; bottom: volcano plot of top metabolite and bar plot of significant metabolites for grid location
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Metabolite page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; bottom: volcano plot of top metabolite and bar plot of significant metabolites for grid location

Metabolite page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; bottom: volcano plot of top metabolite and bar plot of significant metabolites for grid location

Metabolite page with spatial maps on top: effect size, p-value, and mean ILM-RPE thickness; bottom: volcano plot of top metabolite and bar plot of significant metabolites for grid location
View OriginalDownload Slide

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Copyright © 2025 Association for Research in Vision and Ophthalmology.
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