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Phenotypic and genetic characteristics of retinal vascular parameters and their association with diseases

Author

Listed:
  • Sofía Ortín Vela

    (University of Lausanne
    Swiss Institute of Bioinformatics)

  • Michael J. Beyeler

    (University of Lausanne
    Swiss Institute of Bioinformatics)

  • Olga Trofimova

    (University of Lausanne
    Swiss Institute of Bioinformatics)

  • Ilaria Iuliani

    (University of Lausanne
    Swiss Institute of Bioinformatics)

  • Jose D. Vargas Quiros

    (Erasmus MC University Medical Center
    Erasmus MC University Medical Center)

  • Victor A. Vries

    (Erasmus MC University Medical Center
    Erasmus MC University Medical Center)

  • Ilenia Meloni

    (Jules Gonin Eye Hospital
    Jules Gonin Eye Hospital)

  • Adham Elwakil

    (Jules Gonin Eye Hospital
    Jules Gonin Eye Hospital)

  • Florence Hoogewoud

    (Jules Gonin Eye Hospital)

  • Bart Liefers

    (Erasmus MC University Medical Center
    Erasmus MC University Medical Center)

  • David Presby

    (University of Lausanne
    Swiss Institute of Bioinformatics)

  • Wishal D. Ramdas

    (Erasmus MC University Medical Center)

  • Mattia Tomasoni

    (Jules Gonin Eye Hospital
    Jules Gonin Eye Hospital)

  • Reinier Schlingemann

    (Jules Gonin Eye Hospital
    Amsterdam University Medical Centres)

  • Caroline C. W. Klaver

    (Erasmus MC University Medical Center
    Erasmus MC University Medical Center
    Radboud University Medical Center
    University of Basel)

  • Sven Bergmann

    (University of Lausanne
    Swiss Institute of Bioinformatics
    University of Cape Town)

Abstract

Fundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Using a fully automated image processing pipeline, we extract 17 different morphological vascular phenotypes, including median vessels diameter, diameter variability, main temporal angles, vascular density, central retinal equivalents, the number of bifurcations, and tortuosity, from over 130,000 fundus images of close to 72,000 UK Biobank subjects. We perform genome-wide association studies of these phenotypes. From this, we estimate their heritabilities, ranging between 5 and 25%, and genetic cross-phenotype correlations, which mostly mirror the corresponding phenotypic correlations, but tend to be slightly larger. Projecting our genetic association signals onto genes and pathways reveals remarkably low overlap suggesting largely decoupled mechanisms modulating the different phenotypes. We find that diameter variability, especially for the veins, associates with diseases including heart attack, pulmonary embolism, and age of death. Mendelian Randomization analysis suggests a causal influence of blood pressure and body mass index on retinal vessel morphology, among other results. We validate key findings in two independent smaller cohorts. Our analyses provide evidence that large-scale analysis of image-derived vascular phenotypes has sufficient power for obtaining functional and causal insights into the processes modulating the retinal vasculature.

Suggested Citation

  • Sofía Ortín Vela & Michael J. Beyeler & Olga Trofimova & Ilaria Iuliani & Jose D. Vargas Quiros & Victor A. Vries & Ilenia Meloni & Adham Elwakil & Florence Hoogewoud & Bart Liefers & David Presby & W, 2024. "Phenotypic and genetic characteristics of retinal vascular parameters and their association with diseases," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-52334-1
    DOI: 10.1038/s41467-024-52334-1
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    References listed on IDEAS

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    1. Yukun Zhou & Mark A. Chia & Siegfried K. Wagner & Murat S. Ayhan & Dominic J. Williamson & Robbert R. Struyven & Timing Liu & Moucheng Xu & Mateo G. Lozano & Peter Woodward-Court & Yuka Kihara & Andre, 2023. "A foundation model for generalizable disease detection from retinal images," Nature, Nature, vol. 622(7981), pages 156-163, October.
    2. Peter Bankhead & C Norman Scholfield & J Graham McGeown & Tim M Curtis, 2012. "Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-12, March.
    3. David Lamparter & Daniel Marbach & Rico Rueedi & Zoltán Kutalik & Sven Bergmann, 2016. "Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics," PLOS Computational Biology, Public Library of Science, vol. 12(1), pages 1-20, January.
    4. Jie Huang & Bryan Howie & Shane McCarthy & Yasin Memari & Klaudia Walter & Josine L. Min & Petr Danecek & Giovanni Malerba & Elisabetta Trabetti & Hou-Feng Zheng & Giovanni Gambaro & J. Brent Richards, 2015. "Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel," Nature Communications, Nature, vol. 6(1), pages 1-9, November.
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