Polygenic scores for risk of pancreatic ductal adenocarcinoma: evaluation of novel and published models

Polygenic risk scores (PRSs) may enhance risk stratification for pancreatic ductal adenocarcinoma (PDAC), but existing models vary widely in design, predictive performance, and cross-ancestry transferability. We developed genome-wide PRSs using Bayesian methods (LDpred2 and PRS-CS) and p value thresholding (PRSice-2) and systematically evaluated these alongside 13 published PRSs to identify models with robust predictive performance across ancestries. Using GWAS summary statistics from 7531 cases and 10,631 controls, we derived the PRSs and tested associations in an independent sample of 4508 PDAC cases and 46,189 controls, with adjustment for well-established PDAC risk factors. Among all models, the genome-wide LDpred2-based PRS showed the strongest association with PDAC (OR = 1.57 per standard deviation increase; 95% CI: 1.51-1.62) and significantly improved discrimination beyond established risk factors alone (AUC = 0.74-0.76; p < 0.0001). Importantly, the genome-wide LDpred2 PRS demonstrated consistent associations across African, Admixed American, and European ancestry groups, whereas the best-performing published PRS was associated with PDAC risk only in individuals of European ancestry. These findings support genome-wide PRSs as a promising framework for multi-ancestry risk stratification for PDAC and to inform targeted early detection strategies.

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Publication Details

Journal
npj Precision Oncology
Published
2026-05-27
DOI
https://doi.org/10.1038/s41698-026-01479-x
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Polygenic scores for risk of pancreatic ductal adenocarcinoma: evaluation of novel and published models

Andrew J. Danielsen, Erin Fuller, Phyllis J. Goodman, Federico Canzian et al.
npj Precision Oncology
Genetic Associations and Epidemiology
article

Polygenic scores for risk of pancreatic ductal adenocarcinoma: evaluation of novel and published models

Andrew J. Danielsen, Erin Fuller, Phyllis J. Goodman, Federico Canzian, Caitlin Forsythe, D SCHAID, Jean Wactawski‐Wende, Lisa K. Colborn, Samuel O. Antwi, Luca Lotta, Stephen K. Van Den Eeden, Alan A. Arslan, John D. Overton, Laura M. Cremona, Christina Beechert, Yu Chen, C Willer, Miquel Porta, Hunter J. Atkinson, Xie Shu, Jonathan J. Harrington, Rayjean J. Hung, Jeffrey G. Reid, Maya Ghoussaini, Marcus B. Jones, Herbert Yu, Rachel Ε. Neale, Kari G. Rabe, Mona Nafde, Gabriella Andreotti, Alison Fenney, Manuel Allen Revez Ferreira, Mengmeng Du, Zachary S. Fredericksen, Verena Katzke, Katherine Siminovitch, Jason Portnoy, Andrew Deubler, Jones, Jonathan Marchini, Edward Giovannucci, Josh Atkins, Eugene Kalyuskin, Steven Moore, Christopher Haiman, Lyndon Mitnaul, Alan Shuldiner, Sandra Perdomo, Mayo-RGC Project Generation, Lourdes Crane, David McKean, Manal Hassan, Burcu Darst, William R. Bamlet, Aris Baras, Loic Le Marchand, Ulrike Peters, Núria Malats, Zhenhua Gu, Paul Brennan, Adolfo Ferrando, Brandon J. Coombes, Mine Cicek, Alpa V. Patel, Jun Zhong, Michael Goggins, Laura E. Beane Freeman, Kimmie Ng, Nicholas B. Larson, Thérèse Truong, Pietro Ferrari, Eric W. Klee, Fergus J. Couch, Howard D. Sesso, Hang Du, Caroline Y. Um, Charles Kooperberg, Paige M. Bracci, Peter Kraft, Melissa C. Southey, Nathaniel Rothman, Chen Yuan, Stephen J. Chanock, Janet E. Olson, Erin E. Carlson, Steven Gallinger, William Salerno, Demetrius Albanes, Emily White, Shounak Majumder, James R. Cerhan, Gonçalo Abecasis, Debra T. Silverman, Giovanni Coppola, Kala Visvanathan, Wei Zheng, Maria-José Sánchez, Roger L. Milne, Daniele Campa
article en

Abstract

Polygenic risk scores (PRSs) may enhance risk stratification for pancreatic ductal adenocarcinoma (PDAC), but existing models vary widely in design, predictive performance, and cross-ancestry transferability. We developed genome-wide PRSs using Bayesian methods (LDpred2 and PRS-CS) and p value thresholding (PRSice-2) and systematically evaluated these alongside 13 published PRSs to identify models with robust predictive performance across ancestries. Using GWAS summary statistics from 7531 cases and 10,631 controls, we derived the PRSs and tested associations in an independent sample of 4508 PDAC cases and 46,189 controls, with adjustment for well-established PDAC risk factors. Among all models, the genome-wide LDpred2-based PRS showed the strongest association with PDAC (OR = 1.57 per standard deviation increase; 95% CI: 1.51-1.62) and significantly improved discrimination beyond established risk factors alone (AUC = 0.74-0.76; p < 0.0001). Importantly, the genome-wide LDpred2 PRS demonstrated consistent associations across African, Admixed American, and European ancestry groups, whereas the best-performing published PRS was associated with PDAC risk only in individuals of European ancestry. These findings support genome-wide PRSs as a promising framework for multi-ancestry risk stratification for PDAC and to inform targeted early detection strategies.

npj Precision Oncology
University of Pisa (IT), University of Southern California (US), University of Hawaiʻi at Mānoa (US), Universitat Autònoma de Barcelona (ES), Brigham and Women's Hospital (US), American Cancer Society (US), National Institutes of Health (US), University of Hawaii System (US), Memorial Sloan Kettering Cancer Center (US), Kaiser Permanente (US), The University of Texas MD Anderson Cancer Center (US), Harvard University (US), Johns Hopkins University (US), Inserm (FR), The University of Queensland (AU), The University of Melbourne (AU), German Cancer Research Center (DE), University of California, San Francisco (US), Regeneron (United States) (US), Université de Versailles Saint-Quentin-en-Yvelines (FR), Cancer Council Victoria (AU), Vanderbilt University (US), Lunenfeld-Tanenbaum Research Institute (CA), QIMR Berghofer Medical Research Institute (AU), Heidelberg University (DE), Université Paris-Saclay (FR), Jacksonville College (US), University of Oxford (GB), NYU Langone Health (US), Fred Hutch Cancer Center (US), Spanish National Cancer Research Centre (ES), Cancer Center of Hawaii (US), Centre de recherche en Epidémiologie et Santé des Populations (FR), Instituto de Investigación Biosanitaria de Granada (ES), Dana-Farber Cancer Institute (US), Monash Health (AU), Mayo Clinic in Arizona (US), Cancer Research Center (US), National Cancer Institute (US), Mayo Clinic in Florida (US), Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (ES), Sidney Kimmel Comprehensive Cancer Center (US), Centre international de recherche sur le cancer (FR), University of Hawaii Cancer Center, Monash University (AU), New York University (US), Andalusian School of Public Health (ES), University at Buffalo, State University of New York (US)
Lustgarten Foundation, National Cancer Institute
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 7%
Genetic Associations and Epidemiology
DOIOpen Access PDFOpenAlex
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