The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression

Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression
Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression
Glaucoma, a disease characterized by progressive optic nerve degeneration, can be prevented through timely diagnosis and treatment. We characterize optic nerve photographs of 67,040 UK Biobank participants and use a multitrait genetic model to identify risk loci for glaucoma. A glaucoma polygenic risk score (PRS) enables effective risk stratification in unselected glaucoma cases and modifies penetrance of the MYOC variant encoding p.Gln368Ter, the most common glaucoma-associated myocilin variant. In the unselected glaucoma population, individuals in the top PRS decile reach an absolute risk for glaucoma 10 years earlier than the bottom decile and are at 15-fold increased risk of developing advanced glaucoma (top 10% versus remaining 90%, odds ratio = 4.20). The PRS predicts glaucoma progression in prospectively monitored, early manifest glaucoma cases (P = 0.004) and surgical intervention in advanced disease (P = 3.6 × 10−6). This glaucoma PRS will facilitate the development of a personalized approach for earlier treatment of high-risk individuals, with less intensive monitoring and treatment being possible for lower-risk groups
1061-4036
160-166
Lotery, Andrew
5ecc2d2d-d0b4-468f-ad2c-df7156f8e514
Cree, Angela J.
609d60f6-7d1c-4ad0-a8df-81156bea8339
Lotery, Andrew
5ecc2d2d-d0b4-468f-ad2c-df7156f8e514
Cree, Angela J.
609d60f6-7d1c-4ad0-a8df-81156bea8339

Lotery, Andrew and Cree, Angela J. (2020) Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression. Nature Genetics, 52 (2), 160-166. (doi:10.1038/s41588-019-0556-y).

Record type: Article

Abstract

Glaucoma, a disease characterized by progressive optic nerve degeneration, can be prevented through timely diagnosis and treatment. We characterize optic nerve photographs of 67,040 UK Biobank participants and use a multitrait genetic model to identify risk loci for glaucoma. A glaucoma polygenic risk score (PRS) enables effective risk stratification in unselected glaucoma cases and modifies penetrance of the MYOC variant encoding p.Gln368Ter, the most common glaucoma-associated myocilin variant. In the unselected glaucoma population, individuals in the top PRS decile reach an absolute risk for glaucoma 10 years earlier than the bottom decile and are at 15-fold increased risk of developing advanced glaucoma (top 10% versus remaining 90%, odds ratio = 4.20). The PRS predicts glaucoma progression in prospectively monitored, early manifest glaucoma cases (P = 0.004) and surgical intervention in advanced disease (P = 3.6 × 10−6). This glaucoma PRS will facilitate the development of a personalized approach for earlier treatment of high-risk individuals, with less intensive monitoring and treatment being possible for lower-risk groups

Text
54764 3 merged - Accepted Manuscript
Download (1MB)

More information

Accepted/In Press date: 21 November 2019
e-pub ahead of print date: 20 January 2020
Published date: February 2020

Identifiers

Local EPrints ID: 439481
URI: http://eprints.soton.ac.uk/id/eprint/439481
ISSN: 1061-4036
PURE UUID: ef9c55a6-217c-4e0b-90fd-60ff7deda786
ORCID for Andrew Lotery: ORCID iD orcid.org/0000-0001-5541-4305

Catalogue record

Date deposited: 24 Apr 2020 16:30
Last modified: 26 Nov 2021 05:35

Export record

Altmetrics

Contributors

Author: Andrew Lotery ORCID iD
Author: Angela J. Cree

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×