@article{aefec41685c94ae098de3379d44c90b5,
title = "Glaucoma Genetic Risk Scores in the Million Veteran Program",
abstract = "Purpose: Primary open-angle glaucoma (POAG) is a degenerative eye disease for which early treatment is critical to mitigate visual impairment and irreversible blindness. POAG–associated loci individually confer incremental risk. Genetic risk score(s) (GRS) could enable POAG risk stratification. Despite significantly higher POAG burden among individuals of African ancestry (AFR), GRS are limited in this population. A recent large-scale, multi-ancestry meta-analysis identified 127 POAG-associated loci and calculated cross-ancestry and ancestry-specific effect estimates, including in European ancestry (EUR) and AFR individuals. We assessed the utility of the 127-variant GRS for POAG risk stratification in EUR and AFR Veterans in the Million Veteran Program (MVP). We also explored the association between GRS and documented invasive glaucoma surgery (IGS). Design: Cross-sectional study. Participants: MVP Veterans with imputed genetic data, including 5830 POAG cases (445 with IGS documented in the electronic health record) and 64 476 controls. Methods: We tested unweighted and weighted GRS of 127 published risk variants in EUR (3382 cases and 58 811 controls) and AFR (2448 cases and 5665 controls) Veterans in the MVP. Weighted GRS were calculated using effect estimates from the most recently published report of cross-ancestry and ancestry-specific meta-analyses. We also evaluated GRS in POAG cases with documented IGS. Main Outcome Measures: Performance of 127-variant GRS in EUR and AFR Veterans for POAG risk stratification and association with documented IGS. Results: GRS were significantly associated with POAG (P < 5 × 10–5) in both groups; a higher proportion of EUR compared with AFR were consistently categorized in the top GRS decile (21.9%–23.6% and 12.9%–14.5%, respectively). Only GRS weighted by ancestry-specific effect estimates were associated with IGS documentation in AFR cases; all GRS types were associated with IGS in EUR cases. Conclusions: Varied performance of the GRS for POAG risk stratification and documented IGS association in EUR and AFR Veterans highlights (1) the complex risk architecture of POAG, (2) the importance of diverse representation in genomics studies that inform GRS construction and evaluation, and (3) the necessity of expanding diverse POAG-related genomic data so that GRS can equitably aid in screening individuals at high risk of POAG and who may require more aggressive treatment.",
keywords = "Ancestral diversity, Genetic risk score, Invasive glaucoma surgery, Million Veteran Program, Primary open-angle glaucoma",
author = "{VA Million Veteran Program} and Waksmunski, {Andrea R.} and Kinzy, {Tyler G.} and Cruz, {Lauren A.} and Nealon, {Cari L.} and Halladay, {Christopher W.} and Piana Simpson and Canania, {Rachael L.} and Anthony, {Scott A.} and Roncone, {David P.} and {Sawicki Rogers}, Lea and Leber, {Jenna N.} and Dougherty, {Jacquelyn M.} and Greenberg, {Paul B.} and Sullivan, {Jack M.} and Wu, {Wen Chih} and Iyengar, {Sudha K.} and Crawford, {Dana C.} and Peachey, {Neal S.} and {Cooke Bailey}, {Jessica N.} and Gaziano, {J. Michael} and Rachel Ramoni and Jim Breeling and Chang, {Kyong Mi} and Grant Huang and Sumitra Muralidhar and O'Donnell, {Christopher J.} and Tsao, {Philip S.} and Jennifer Moser and Whitbourne, {Stacey B.} and Brewer, {Jessica V.} and John Concato and Stuart Warren and Argyres, {Dean P.} and Brady Stephens and Brophy, {Mary T.} and Humphries, {Donald E.} and Nhan Do and Shahpoor Shayan and Nguyen, {Xuan Mai T.} and Saiju Pyarajan and Kelly Cho and Elizabeth Hauser and Yan Sun and Hongyu Zhao and Peter Wilson and Rachel McArdle and Louis Dellitalia and John Harley and Jeffrey Whittle and Jean Beckham",
note = "Funding Information: This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by award I01 BX004557. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. We are grateful to the VINCI and GENISIS support teams as well as the MVP Core Statistical Analysis team for their contributions to this study. We also appreciate the Veterans who enrolled in the MVP. Without them, this work would not be possible. This work was also funded by the Cleveland Institute for Computational Biology, NIH Core Grants (P30 EY025585, P30 EY011373), and unrestricted grants from Research to Prevent Blindness to Case Western Reserve University (CWRU), Cleveland Clinic Lerner College of Medicine of CWRU, and the University of Buffalo. A.R.W. was supported by the CWRU Visual Sciences Training Program (T32 EY 7157-19) and the CWRU Clinical and Translational Scientist Training Program (TL1 TR 002549-04). L.A.C. was supported by the National Heart, Lung, and Blood Institute (T32 HL 0075-67). This publication was made possible by the Clinical and Translational Science Collaborative of Cleveland (UL1TR0002548) from the National Center for Advancing Translational Sciences (NCATS) component of the National Institutes of Health and NIH roadmap for Medical Research. This work made use of the High Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University. Funding Information: The authors thank the VINCI and GENISIS support teams and the MVP Core Statistical Analysis team for their contributions to this study, as well as the Veterans who enrolled in the MVP. Without them, this work would not be possible. N.S.P.: Financial support – Cleveland Clinic Foundation This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by award I01 BX004557. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. We are grateful to the VINCI and GENISIS support teams as well as the MVP Core Statistical Analysis team for their contributions to this study. We also appreciate the Veterans who enrolled in the MVP. Without them, this work would not be possible. This work was also funded by the Cleveland Institute for Computational Biology, NIH Core Grants (P30 EY025585, P30 EY011373), and unrestricted grants from Research to Prevent Blindness to Case Western Reserve University (CWRU), Cleveland Clinic Lerner College of Medicine of CWRU, and the University of Buffalo. A.R.W. was supported by the CWRU Visual Sciences Training Program (T32 EY 7157-19) and the CWRU Clinical and Translational Scientist Training Program (TL1 TR 002549-04). L.A.C. was supported by the National Heart, Lung, and Blood Institute (T32 HL 0075-67). This publication was made possible by the Clinical and Translational Science Collaborative of Cleveland (UL1TR0002548) from the National Center for Advancing Translational Sciences (NCATS) component of the National Institutes of Health and NIH roadmap for Medical Research. This work made use of the High Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University. Obtained funding: Iyengar and Peachey Publisher Copyright: {\textcopyright} 2022",
year = "2022",
month = nov,
doi = "10.1016/j.ophtha.2022.06.012",
language = "English",
volume = "129",
pages = "1263--1274",
journal = "Ophthalmology",
issn = "0161-6420",
publisher = "Elsevier Inc.",
number = "11",
}