Authors
Minta Thomas, Lori C Sakoda, Michael Hoffmeister, Elisabeth A Rosenthal, Jeffrey K Lee, Franzel JB van Duijnhoven, Elizabeth A Platz, Anna H Wu, Christopher H Dampier, Albert de la Chapelle, Alicja Wolk, Amit D Joshi, Andrea Burnett-Hartman, Andrea Gsur, Annika Lindblom, Antoni Castells, Aung Ko Win, Bahram Namjou, Bethany Van Guelpen, Catherine M Tangen, Qianchuan He, Christopher I Li, Clemens Schafmayer, Corinne E Joshu, Cornelia M Ulrich, D Timothy Bishop, Daniel D Buchanan, Daniel Schaid, David A Drew, David C Muller, David Duggan, David R Crosslin, Demetrius Albanes, Edward L Giovannucci, Eric Larson, Flora Qu, Frank Mentch, Graham G Giles, Hakon Hakonarson, Heather Hampel, Ian B Stanaway, Jane C Figueiredo, Jeroen R Huyghe, Jessica Minnier, Jenny Chang-Claude, Jochen Hampe, John B Harley, Kala Visvanathan, Keith R Curtis, Kenneth Offit, Li Li, Loic Le Marchand, Ludmila Vodickova, Marc J Gunter, Mark A Jenkins, Martha L Slattery, Mathieu Lemire, Michael O Woods, Mingyang Song, Neil Murphy, Noralane M Lindor, Ozan Dikilitas, Paul DP Pharoah, Peter T Campbell, Polly A Newcomb, Roger L Milne, Robert J MacInnis, Sergi Castellví-Bel, Shuji Ogino, Sonja I Berndt, Stéphane Bézieau, Stephen N Thibodeau, Steven J Gallinger, Syed H Zaidi, Tabitha A Harrison, Temitope O Keku, Thomas J Hudson, Veronika Vymetalkova, Victor Moreno, Vicente Martín, Volker Arndt, Wei-Qi Wei, Wendy Chung, Yu-Ru Su, Richard B Hayes, Emily White, Pavel Vodicka, Graham Casey, Stephen B Gruber, Robert E Schoen, Andrew T Chan, John D Potter, Hermann Brenner, Gail P Jarvik, Douglas A Corley, Ulrike Peters, Li Hsu
Publication date
2020/9/3
Journal
The American journal of human genetics
Volume
107
Issue
3
Pages
432-444
Publisher
Elsevier
Description
Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on …
Scholar articles
M Thomas, LC Sakoda, M Hoffmeister, EA Rosenthal… - The American journal of human genetics, 2020