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Predicting the Future of Genetic Risk Profiling of Glaucoma: A Narrative Review
Xikun Han1,2, Alex W Hewitt3,4, Stuart MacGregor1
1QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Importance:
Glaucoma is the world's leading cause of irreversible blindness. Primary open-angle glaucoma (POAG) is typically asymptomatic early in the disease process, and unfortunately, many are diagnosed too late to prevent vision loss.
Observations:
Genome-wide association studies, which evaluate the association between genetic variants and phenotype across the genome, have mapped many genes for POAG. As well as uncovering new biology, genetic information can be combined into a polygenic risk score (PRS), which aggregates an individual's disease risk over many genetic variants. In this nonsystematic review, performed from June 21, 2019, to October 1, 2020, we address a series of questions to explain the challenges and opportunities in translating genetic discoveries in POAG. We summarize what is known about POAG genetics and how its endophenotypes, such as intraocular pressure or cup-disc ratio, can help with prediction. We discuss the sample sizes available and how increases in the future may have an effect on the utility of prediction approaches. We explore particular scenarios, such as the use of PRS in risk stratification, and applications for individuals who are particularly high risk for POAG as a result of them carrying both a high penetrance mutation and an unfavorable PRS. Finally, we discuss the issue of equity in applying these tests and the prospects for prediction for people from various ancestry groups. The cost-effectiveness evaluation of glaucoma PRS in direct-to-consumer genetic testing and across different ancestry groups is warranted in future research.
Conclusions And Relevance:
Advances in glaucoma genetics have opened the door for risk stratification based on genetic risk predictions. The PRS approach has shown good promise in predicting who will be at highest risk of POAG, which could improve outcomes if these predictions can be acted on to result in improved clinical outcomes.
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