Multiple polygenic score approach in colorectal cancer risk prediction
Abstract
Abstract Recent studies have demonstrated that for various diseases, incorporating polygenic risk scores (PRSs) for other traits and diseases into the PRS-based risk prediction model may improve predictive performance – known as Multiple Polygenic Score (MPS) approach. We aimed to examine whether the MPS approach improves colorectal cancer (CRC) risk prediction. We included 2,187 non-CRC PRSs from the polygenic Score (PGS) Catalog and used machine learning (ML) models to select the most predictive non-CRC PRSs, utilizing individual-level data from 31,257 CRC cases and 33,408 controls. An independent dataset from the Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort (4,852 cases and 67,939 controls) was randomly split into subsets for model estimation and validation. The model combined MPS with two existing CRC-PRSs based on known loci and genome-wide genotyping. We then assessed model performance by calculating the area under the receiver operating curve (AUC) in the validation set and performed 1,000 bootstrapped iterations to evaluate AUC improvements. The ML model selected 337 non-CRC PRSs predictive of CRC risk. Adding MPS to the CRC-PRSs significantly improved AUC by 0.017 (95% CI: 0.011–0.022, p < 0.0001) when combined with known-loci CRC-PRS, 0.005 (95% CI: 0.002–0.007, p = 0.0005) with genome-wide CRC-PRS, and 0.004 (95% CI: 0.002–0.006, p = 0.0005) with both the known loci and genome-wide CRC-PRSs. These findings demonstrate MPS’s potential to refine CRC risk prediction models and highlight opportunities for further advancements in risk prediction.
Article Details
Authors (44)
Shangqing Joyce Jiang
Minta Thomas
Elisabeth A. Rosenthal
Amanda I. Phipps
Lori C. Sakoda
Franzel J. B. van Duijnhoven
Andrew J. Pellatt
Christy L. Avery
Sonja I. Berndt
D. Timothy Bishop
Sergi Castellví-Bel
Andrew T. Chan
Robert C. Grant
Chris Gignoux
Stanford University, Stanford, CA, USA.
Andrea Gsur
Marc J. Gunter
Christopher A. Haiman
Michael Hoffmeister
Gail P. Jarvik
Mark A. Jenkins
Temitope O. Keku
Sébastien Küry
Jeffrey K. Lee
Loic Le Marchand
Víctor Moreno
Polly A. Newcomb
Christina C. Newton
Shuji Ogino
Julie R. Palmer
Rachel Pearlman
Conghui Qu
Robert E. Schoen
Caroline Y. Um
Bethany Van Guelpen
Kala Visvanathan
Veronika Vymetalkova
Emily White
Michael O. Woods
Elizabeth A. Platz
Hermann Brenner
Douglas A. Corley
Iris Landorp Vogelaar
Li Hsu
Ulrike Peters
Fred Hutchinson Cancer Research Center, Seattle, WA, USA.