Polygenic scores for risk of pancreatic ductal adenocarcinoma: evaluation of novel and published models
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.
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BibTeX
@article{antwi2026polygenic,
title = {{Polygenic scores for risk of pancreatic ductal adenocarcinoma: evaluation of novel and published models}},
author = {Samuel O. Antwi and Brandon J. Coombes and Erin E. Carlson and Nicholas B. Larson and Kari G. Rabe and Hunter J. Atkinson and Shounak Majumder and William R. Bamlet and Daniel J. Schaid and Jun Zhong and David Mckean and Alan A. Arslan and Laura E. Beane Freeman and Paige M. Bracci and Federico Canzian and Thérèse Truong and Josh Atkins and Mengmeng Du and Steven Gallinger and Phyllis J. Goodman and Verena Katzke and Daniele Campa and Charles Kooperberg and Loic Le Marchand and Rachel E. Neale and Alpa V. Patel and Jean Wactawski-Wende and Sandra Perdomo and Xiao-Ou Shu and Kala Visvanathan and Stephen K. van den Eeden and Emily White and Wei Zheng and Demetrius Albanes and Gabriella Andreotti and Paul Brennan and Stephen J. Chanock and Yu Chen and Burcu Darst and Pietro Ferrari and Edward L. Giovannucci and Michael Goggins and Christopher Haiman and Manal Hassan and Rayjean J. Hung and Miranda R. Jones and Peter Kraft and Núria Malats and Steven C. Moore and Kimmie Ng and Ulrike Peters and Miquel Porta and Nathaniel Rothman and Maria-José Sánchez and Howard D. Sesso and Debra T. Silverman and Melissa C. Southey and Roger L. Milne and Caroline Y. Um and Herbert Yu},
journal = {npj Precision Oncology},
year = {2026},
month = may,
doi = {10.1038/s41698-026-01479-x},
url = {https://hal.science/hal-05748763v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Polygenic scores for risk of pancreatic ductal adenocarcinoma: evaluation of novel and published models
AU - Samuel O. Antwi
AU - Brandon J. Coombes
AU - Erin E. Carlson
AU - Nicholas B. Larson
AU - Kari G. Rabe
AU - Hunter J. Atkinson
AU - Shounak Majumder
AU - William R. Bamlet
AU - Daniel J. Schaid
AU - Jun Zhong
AU - David Mckean
AU - Alan A. Arslan
AU - Laura E. Beane Freeman
AU - Paige M. Bracci
AU - Federico Canzian
AU - Thérèse Truong
AU - Josh Atkins
AU - Mengmeng Du
AU - Steven Gallinger
AU - Phyllis J. Goodman
AU - Verena Katzke
AU - Daniele Campa
AU - Charles Kooperberg
AU - Loic Le Marchand
AU - Rachel E. Neale
AU - Alpa V. Patel
AU - Jean Wactawski-Wende
AU - Sandra Perdomo
AU - Xiao-Ou Shu
AU - Kala Visvanathan
AU - Stephen K. van den Eeden
AU - Emily White
AU - Wei Zheng
AU - Demetrius Albanes
AU - Gabriella Andreotti
AU - Paul Brennan
AU - Stephen J. Chanock
AU - Yu Chen
AU - Burcu Darst
AU - Pietro Ferrari
AU - Edward L. Giovannucci
AU - Michael Goggins
AU - Christopher Haiman
AU - Manal Hassan
AU - Rayjean J. Hung
AU - Miranda R. Jones
AU - Peter Kraft
AU - Núria Malats
AU - Steven C. Moore
AU - Kimmie Ng
AU - Ulrike Peters
AU - Miquel Porta
AU - Nathaniel Rothman
AU - Maria-José Sánchez
AU - Howard D. Sesso
AU - Debra T. Silverman
AU - Melissa C. Southey
AU - Roger L. Milne
AU - Caroline Y. Um
AU - Herbert Yu
PY - 2026
DA - 2026/05/27
JO - npj Precision Oncology
DO - 10.1038/s41698-026-01479-x
UR - https://hal.science/hal-05748763v1
AB - 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.
SN - 2397-768X
ER -