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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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