Student and Faculty Publications

Authors

Burcu F Darst
Jiayi Shen
Ravi K Madduri
Alexis A Rodriguez
Yukai Xiao
Xin Sheng
Edward J Saunders
Tokhir Dadaev
Mark N Brook
Thomas J Hoffmann
Kenneth Muir
Peggy Wan
Loic Le Marchand
Lynne Wilkens
Ying Wang
Johanna Schleutker
Robert J MacInnis
Cezary Cybulski
David E Neal
Børge G Nordestgaard
Sune F Nielsen
Jyotsna Batra
Judith A Clements
Australian Prostate Cancer BioResource
Henrik Grönberg
Nora Pashayan
Ruth C Travis
Jong Y Park
Demetrius Albanes
Stephanie Weinstein
Lorelei A Mucci
David J Hunter
Kathryn L Penney
Catherine M Tangen
Robert J Hamilton
Marie-Élise Parent
Janet L Stanford
Stella Koutros
Alicja Wolk
Karina D Sørensen
William J Blot
Edward D Yeboah
James E Mensah
Yong-Jie Lu
Daniel J Schaid
Stephen N Thibodeau
Catharine M West
Christiane Maier
Adam S Kibel
Géraldine Cancel-Tassin
Florence Menegaux
Esther M John
Eli Marie Grindedal
Kay-Tee Khaw
Sue A Ingles
Ana Vega
Barry S Rosenstein
Manuel R Teixeira
NC-LA PCaP Investigators
Manolis Kogevinas
Lisa Cannon-Albright
Chad Huff
Luc Multigner
Radka Kaneva
Robin J Leach
Hermann Brenner
Ann W Hsing
Rick A Kittles
Adam B Murphy
Christopher J Logothetis
Susan L Neuhausen
William B Isaacs
Barbara Nemesure
Anselm J Hennis
John Carpten
Hardev Pandha
Kim De Ruyck
Jianfeng Xu
Azad Razack
Soo-Hwang Teo
Canary PASS Investigators
Lisa F Newcomb
Jay H Fowke
Christine Neslund-Dudas
Benjamin A Rybicki
Marija Gamulin
Nawaid Usmani
Frank Claessens
Manuela Gago-Dominguez
Jose Esteban Castelao
Paul A Townsend
Dana C Crawford
Gyorgy Petrovics
Graham Casey
Monique J Roobol
Jennifer F Hu
Sonja I Berndt
Stephen K Van Den Eeden
Douglas F Easton
Stephen J Chanock
Michael B Cook
Fredrik Wiklund
John S Witte
Rosalind A Eeles
Zsofia Kote-Jarai
Stephen Watya
John M Gaziano
Amy C Justice
David V Conti
Christopher A Haiman

Publication Date

7-6-2023

Journal

American Journal of Human Genetics

Abstract

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Keywords

Humans, Male, Black People, Genetic Predisposition to Disease, Genome-Wide Association Study, Multifactorial Inheritance, Prostatic Neoplasms, Risk Factors, White People

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