Performance Of African-ancestry-specific Polygenic Hazard Score Varies According To Local Ancestry In 8q24

Roshan A. Karunamuni, Department of Radiation Medicine and Applied Sciences
Minh Phuong Huynh-Le, The George Washington University
Chun C. Fan, The Center for Human Development
Wesley Thompson, Department of Family Medicine and Public Health
Asona Lui, Department of Radiation Medicine and Applied Sciences
Maria Elena Martinez, University of California, San Diego
Brent S. Rose, Department of Radiation Medicine and Applied Sciences
Brandon Mahal, University of Miami Leonard M. Miller School of Medicine
Rosalind A. Eeles, The Institute of Cancer Research
Zsofia Kote-Jarai, The Institute of Cancer Research
Kenneth Muir, The University of Manchester
Artitaya Lophatananon, The University of Manchester
Catherine M. Tangen, Fred Hutchinson Cancer Research Center
Phyllis J. Goodman, Fred Hutchinson Cancer Research Center
Ian M. Thompson, CHRISTUS Santa Rosa Hospital
William J. Blot, Vanderbilt University Medical Center
Wei Zheng, Vanderbilt University Medical Center
Adam S. Kibel, Brigham and Women's Hospital
Bettina F. Drake, Washington University School of Medicine in St. Louis
Olivier Cussenot, Sorbonne Université
Géraldine Cancel-Tassin, Sorbonne Université
Florence Menegaux, Inserm
Thérèse Truong, Inserm
Jong Y. Park, Moffitt Cancer Center
Hui Yi Lin, LSU Health Sciences Center - New Orleans
Jack A. Taylor, National Institute of Environmental Health Sciences (NIEHS)
Jeannette T. Bensen, The University of North Carolina at Chapel Hill
James L. Mohler, The University of North Carolina at Chapel Hill

Abstract

Background: We previously developed an African-ancestry-specific polygenic hazard score (PHS46+African) that substantially improved prostate cancer risk stratification in men with African ancestry. The model consists of 46 SNPs identified in Europeans and 3 SNPs from 8q24 shown to improve model performance in Africans. Herein, we used principal component (PC) analysis to uncover subpopulations of men with African ancestry for whom the utility of PHS46+African may differ. Materials and methods: Genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Genetic variation in a window spanning 3 African-specific 8q24 SNPs was estimated using 93 PCs. A Cox proportional hazards framework was used to identify the pair of PCs most strongly associated with the performance of PHS46+African. A calibration factor (CF) was formulated using Cox coefficients to quantify the extent to which the performance of PHS46+African varies with PC. Results: CF of PHS46+African was strongly associated with the first and twentieth PCs. Predicted CF ranged from 0.41 to 2.94, suggesting that PHS46+African may be up to 7 times more beneficial to some African men than others. The explained relative risk for PHS46+African varied from 3.6% to 9.9% for individuals with low and high CF values, respectively. By cross-referencing our data set with 1000 Genomes, we identified significant associations between continental and calibration groupings. Conclusion: We identified PCs within 8q24 that were strongly associated with the performance of PHS46+African. Further research to improve the clinical utility of polygenic risk scores (or models) is needed to improve health outcomes for men of African ancestry.