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Performance of Polygenic Risk Scores for Primary Open-Angle Glaucoma in Populations of African Descent

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ImportancePrimary open-angle glaucoma (POAG) polygenic risk scores (PRSs) continue to be evaluated in primarily European-ancestry populations despite higher prevalence and worse outcomes in African-ancestry populations.ObjectiveTo evaluate how established POAG PRSs perform in African-ancestry samples from the Genetics in Glaucoma Patients of African Descent (GIGA), Genetics of Glaucoma in Individuals of African Descent (GGLAD), and Million Veteran Program (MVP) datasets and compare these with European-ancestry samples.Design, Setting, and ParticipantsThis was a multicenter, cross-sectional study of POAG cases and controls from Tanzania, South Africa, Nigeria, Ghana, and the US. Included were individuals of African descent from South Africa and Tanzania from the GIGA dataset; individuals of African descent from Ghana, Nigeria, and the US from the GGLAD dataset; and individuals of African or European descent from the US in the MVP dataset. Data were analyzed from January 2022 to July 2023.ExposuresThree PRSs derived from large meta-analyses of European and Asian populations, namely Gharahkhani et al (Gharahkhani PRS), Han et al (Han PRS), and Craig et al (Craig PRS).Main Outcomes and MeasuresOdds ratios (ORs) for POAG risk stratification comparing the highest and lowest quintiles; area under the receiver operating characteristic curve (AUROC), and liability coefficient of determination (R2) for the addition of PRS to a baseline of age, sex, and first 5 principal components.ResultsA total of 11 673 cases and 66 432 controls were included in this study across 7 ancestral groups. Mean (SD) age of the total participants was 76.9 (8.7) years, with 74 304 males (95.1%). The following were included in each dataset: GIGA (663 cases, 476 controls), GGLAD (1471 cases, 1482 controls), and MVP (9559 cases, 64 474 controls). Increases in ORs were found for the highest POAG risk quintile ranging from an OR of 1.68 (95% CI, 1.17-2.43) in Ghanaians to 7.05 (95% CI, 2.73-19.6) in the South African multiple ancestry group (which derives from at least 5 distinct ancestral groups: Khoisan, Bantus, Europeans, Indians, and Southeast Asians) with the Gharahkhani PRS. The Han PRS showed OR increases for the highest POAG risk quintile ranging from 2.27 (95% CI, 1.49-3.47) in African American individuals in the GGLAD dataset to 7.24 (95% CI, 6.47-8.12) in Europeans. The Craig PRS predicted OR increases in the highest quintile for all groups ranging from 1.51 (95% CI, 1.05-2.18) in Ghanaians to 6.31 (95% CI, 5.67-7.04) in Europeans. However, AUROC and R2 increases above baseline were lower for all African-ancestry compared with European-ancestry groups in the 3 tested PRSs.Conclusions and RelevanceIn this cross-sectional study, despite some improvements in OR-based risk stratification using the Gharahkhani PRSs, Han PRSs, and Craig PRSs, consistently lower improvements in AUROC and R2 for African-ancestry compared with European-ancestry groups highlight the need for risk prediction models tailored to diverse populations.
American Medical Association (AMA)
Jennifer M. Chang-Wolf Tyler G. Kinzy Sjoerd J. Driessen Lauren A. Cruz Sudha K. Iyengar Neal S. Peachey Tin Aung Chiea Chuen Khor Susan E. Williams Michele Ramsay Olusola Olawoye Adeyinka Ashaye Caroline C. W. Klaver Michael A. Hauser Alberta A. H. J. Thiadens Jessica N. Cooke Bailey Pieter W. M. Bonnemaijer Anna J. Sanywia Colin Cook Hassan G. Hassan Neema Kanyaro Cyprian Ntomoka R.R. Allingham Carly J van der Heide Kent D Taylor Jerome I Rotter Shih-Hsiu J Wang Sadiq M ABDULLAHI Khaled K. Abu-Amero Michael G Anderson Stephen Akafo Mahmoud B ALHASSAN Ifeoma Asimadu Radha Ayyagari Seydou BAKAYOKO Prisca BIANGOUP NYAMSI Donald W Bowden William C Bromley Donald L Budenz Trevor R Carmichael Pratap Challa Yii-Der Ida Chen Chimdi M Chuka-Okosa Vital Paulino Costa Dianne A Cruz Harvey DuBiner JF Ervin Robert M Feldman Miles Flamme-Wiese Douglas E Gaasterland Sarah Garnai Christopher A Girkin Nouhoum GUIROU Xiuqing Guo Jonathan Haines CJ Hammond Leon Herndon Thomas J Hoffmann Christine M Hulette Abba Hydara Robert P Igo Jr. Eric Jorgenson Joyce KABWE Ngoy Janvier KILANGALANGA Nkiru Kizor-Akaraiwe Rachel W Kuchtey Hasnaa LAMARI Zheng Li Jeffrey M Liebmann Yutao Liu Ruth JF Loos Monica B Melo Sayoko E Moroi Joseph M Msosa Robert F Mullins Girish Nadkarni Abdoulaye NAPO Maggie C.Y. Ng Hugo Freire Nunes Ebenezer Obeng-Nyarkoh Anthony Okeke Suhanya Okeke Olusegun OLANIYI Mariana Borges Oliveira Louis R Pasquale Rodolfo A. Perez-Grossmann Margaret A Pericak-Vance XJ Qin Serge RESNIKOFF Julia E Richards Rui Barroso Schimiti Kar Seng Sim William E Sponsel Paulo Vinícius Svidnicki Nkechinyere J Uche CM van Duijn José Paulo Cabral de Vasconcellos Janey L Wiggs Linda M Zangwill Neil Risch Dan Milea Robert N Weinreb Allison E Ashley-Koch John H Fingert Mihaela Aslan M Antonelli M de Asis MS Bauer Mary Brophy John Concato F Cunningham R Freedman Michael Gaziano Theresa Gleason Philip Harvey Grant Huang J Kelsoe Thomas Kosten T Lehner JB Lohr SR Marder P Miller Timothy O Leary T Patterson P Peduzzi Ronald Przygodski Larry Siever P Sklar S Strakowski Hongyu Zhao Ayman Fanous W Farwell A Malhorta S Mane P Palacios Tim Bigdeli M Corsey L Zaluda Juanita Johnson Melyssa Sueiro D Cavaliere V Jeanpaul Alysia Maffucci L Mancini J Deen G Muldoon Stacey Whitbourne J Canive L Adamson L Calais G Fuldauer R Kushner G Toney M Lackey A Mank N Mahdavi G Villarreal EC Muly F Amin M Dent J Wold B Fischer A Elliott C Felix G Gill PE Parker C Logan J McAlpine LE DeLisi SG Reece MB Hammer D Agbor‐Tabie W Goodson M Aslam M Grainger Neil Richtand Alexander Rybalsky R Al Jurdi E Boeckman T Natividad D Smith M Stewart S Torres Z Zhao A Mayeda A Green J Hofstetter S Ngombu MK Scott A Strasburger J Sumner G Paschall J Mucciarelli R Owen S Theus D Tompkins SG Potkin C Reist M Novin S Khalaghizadeh Richard Douyon Nita Kumar Becky Martinez SR Sponheim TL Bender HL Lucas AM Lyon MP Marggraf LH Sorensen CR Surerus C Sison J Amato DR Johnson N Pagan‐Howard LA Adler S Alerpin T Leon KM Mattocks N Araeva JC Sullivan T Suppes K Bratcher L Drag EG Fischer L Fujitani S Gill D Grimm J Hoblyn T Nguyen E Nikolaev L Shere R Relova A Vicencio M Yip I Hurford S Acheampong G Carfagno GL Haas C Appelt E Brown B Chakraborty E Kelly G Klima S Steinhauer RA Hurley R Belle D Eknoyan K Johnson J Lamotte E Granholm K Bradshaw J Holden RH Jones T Le IG Molina M Peyton I Ruiz L Sally A Tapp S Devroy V Jain N Kilzieh L Maus K Miller H Pope A Wood E Meyer P Givens PB Hicks S Justice K McNair JL Pena DF Tharp L Davis M Ban L Cheatum P Darr W Grayson J Munford B Whitfield E Wilson SE Melnikoff BL Schwartz MA Tureson D D Souza K Forselius M Ranganathan L Rispoli M Sather C Colling C Haakenson D Kruegar Sumitra Muralidhar Rachel Ramoni Jim Breeling Kyong‐Mi Chang Christopher O Donnell Philip Tsao Jennifer Moser Jessica Brewer Stuart Warren Dean Argyres Brady Stevens Donald Humphries Nhan Do Shahpoor Shayan Xuan‐Mai Nguyen Saiju Pyarajan Kelly Cho Elizabeth Hauser Yan Sun Peter Wilson Rachel McArdle Louis Dellitalia John Harley Jeffrey Whittle
Title: Performance of Polygenic Risk Scores for Primary Open-Angle Glaucoma in Populations of African Descent
Description:
ImportancePrimary open-angle glaucoma (POAG) polygenic risk scores (PRSs) continue to be evaluated in primarily European-ancestry populations despite higher prevalence and worse outcomes in African-ancestry populations.
ObjectiveTo evaluate how established POAG PRSs perform in African-ancestry samples from the Genetics in Glaucoma Patients of African Descent (GIGA), Genetics of Glaucoma in Individuals of African Descent (GGLAD), and Million Veteran Program (MVP) datasets and compare these with European-ancestry samples.
Design, Setting, and ParticipantsThis was a multicenter, cross-sectional study of POAG cases and controls from Tanzania, South Africa, Nigeria, Ghana, and the US.
Included were individuals of African descent from South Africa and Tanzania from the GIGA dataset; individuals of African descent from Ghana, Nigeria, and the US from the GGLAD dataset; and individuals of African or European descent from the US in the MVP dataset.
Data were analyzed from January 2022 to July 2023.
ExposuresThree PRSs derived from large meta-analyses of European and Asian populations, namely Gharahkhani et al (Gharahkhani PRS), Han et al (Han PRS), and Craig et al (Craig PRS).
Main Outcomes and MeasuresOdds ratios (ORs) for POAG risk stratification comparing the highest and lowest quintiles; area under the receiver operating characteristic curve (AUROC), and liability coefficient of determination (R2) for the addition of PRS to a baseline of age, sex, and first 5 principal components.
ResultsA total of 11 673 cases and 66 432 controls were included in this study across 7 ancestral groups.
Mean (SD) age of the total participants was 76.
9 (8.
7) years, with 74 304 males (95.
1%).
The following were included in each dataset: GIGA (663 cases, 476 controls), GGLAD (1471 cases, 1482 controls), and MVP (9559 cases, 64 474 controls).
Increases in ORs were found for the highest POAG risk quintile ranging from an OR of 1.
68 (95% CI, 1.
17-2.
43) in Ghanaians to 7.
05 (95% CI, 2.
73-19.
6) in the South African multiple ancestry group (which derives from at least 5 distinct ancestral groups: Khoisan, Bantus, Europeans, Indians, and Southeast Asians) with the Gharahkhani PRS.
The Han PRS showed OR increases for the highest POAG risk quintile ranging from 2.
27 (95% CI, 1.
49-3.
47) in African American individuals in the GGLAD dataset to 7.
24 (95% CI, 6.
47-8.
12) in Europeans.
The Craig PRS predicted OR increases in the highest quintile for all groups ranging from 1.
51 (95% CI, 1.
05-2.
18) in Ghanaians to 6.
31 (95% CI, 5.
67-7.
04) in Europeans.
However, AUROC and R2 increases above baseline were lower for all African-ancestry compared with European-ancestry groups in the 3 tested PRSs.
Conclusions and RelevanceIn this cross-sectional study, despite some improvements in OR-based risk stratification using the Gharahkhani PRSs, Han PRSs, and Craig PRSs, consistently lower improvements in AUROC and R2 for African-ancestry compared with European-ancestry groups highlight the need for risk prediction models tailored to diverse populations.

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