June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
Combining glaucoma and correlated risk factors dramatically expands gene discovery for glaucoma
Author Affiliations & Notes
  • Stuart MacGregor
    QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
  • Xikun Han
    QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
  • Puya Gharahkhani
    QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
  • Maciej Trzaskowski
    Max Kelsen, Brisbane, Queensland, Australia
  • Jamie E Craig
    Flinders University, Adelaide, South Australia, Australia
  • Alex W Hewitt
    University of Tasmania, Hobart, Tasmania, Australia
  • David A Mackey
    University of Western Australia Centre for Ophthalmology and Visual Science, Perth, Western Australia, Australia
  • Janey L Wiggs
    Harvard Medical School, Boston, Massachusetts, United States
  • Anthony P Khawaja
    Moorfields Eye Hospital NHS Foundation Trust, London, London, United Kingdom
  • Footnotes
    Commercial Relationships   Stuart MacGregor, Glaucoma genetic risk score patent application (P); Xikun Han, None; Puya Gharahkhani, None; Maciej Trzaskowski, Max Kelsen (E); Jamie Craig, Glaucoma genetic risk score patent application (P); Alex Hewitt, Glaucoma genetic risk score patent application (P); David Mackey, None; Janey Wiggs, None; Anthony Khawaja, None
  • Footnotes
    Support  Australian National Health and Medical Research Council (Fellowship, Centre of Research Excellence, Program grant)
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 1512. doi:
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      Stuart MacGregor, Xikun Han, Puya Gharahkhani, Maciej Trzaskowski, Jamie E Craig, Alex W Hewitt, David A Mackey, Janey L Wiggs, Anthony P Khawaja; Combining glaucoma and correlated risk factors dramatically expands gene discovery for glaucoma. Invest. Ophthalmol. Vis. Sci. 2021;62(8):1512.

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

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Purpose : Glaucoma is one of the most heritable human diseases and hence mapping the specific genes is expected to both provide insights into disease biology as well as enhance our ability to detect who will be at highest risk. While genome-wide association studies (GWAS) have identified 127 open angle glaucoma risk loci to date, these only account for a small fraction of disease heritability. Traditionally glaucoma genes were mapped using a case-control design but we recently showed (Craig et al, Nature Genetics, 2020) that power to identify genes can be dramatically increased (effective sample size increased 2.5 fold) by augmenting cases and controls with glaucoma risk factor data. Our aim here is to leverage the correlation between glaucoma, intraocular pressure (IOP) and vertical cup to disc ratio (VCDR) to identify novel glaucoma risk loci.

Methods : We conducted a multi-trait analysis of glaucoma and its risk factors, using new and existing GWASs we have collected from around the world (34,179 glaucoma cases, 349,321 controls, supplemented by 111,724 individuals with VCDR and 153,604 individuals with IOP measures, drawn from studies in the International Glaucoma Genetics Consortium, UK Biobank and the Canadian Longitudinal Study of Aging). A key novelty over previous work is that VCDR measures were derived using a machine learning approach instead of using human graders, dramatically improving accuracy and power. The input traits were combined in a multi-trait GWAS framework using the software MTAG; an important feature of the approach is that it generates results which are specific to glaucoma risk.

Results : Our analysis of European ancestry samples identified 263 genome-wide significant loci, with most showing very good concordance in other ancestries. Combining across ancestries further improved power and identified 312 independent loci associated with glaucoma. Novel loci implicated by our analysis include associations at the genes TCF7 (implicating overlapping pathways with cataract) and SYN3 (implicating overlapping pathways with macular degeneration). We are currently working on replicating the novel loci in a large case-control cohort.

Conclusions : This work dramatically expands our knowledge of glaucoma genetics by identifying a large number of new risk loci, providing new insights into glaucoma aetiology and helping enable improved prediction of who is at highest disease risk.

This is a 2021 ARVO Annual Meeting abstract.


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