دورية أكاديمية

Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

التفاصيل البيبلوغرافية
العنوان: Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations
المؤلفون: Thomas, M., Su, Y.-R., Rosenthal, E.A., Sakoda, L.C., Schmit, S.L., Timofeeva, M.N., Chen, Z., Fernandez-Rozadilla, C., Law, P.J., Murphy, N., Carreras-Torres, R., Diez-Obrero, V., van Duijnhoven, F.J.B., Jiang, S., Shin, A., Wolk, A., Phipps, A.I., Burnett-Hartman, A., Gsur, A., Chan, A.T., Zauber, A.G., Wu, A.H., Lindblom, A., Um, C.Y., Tangen, C.M., Gignoux, C., Newton, C., Haiman, C.A., Qu, C., Bishop, D.T., Buchanan, D.D., Crosslin, D.R., Conti, D.V., Kim, D.-H., Hauser, E., White, E., Siegel, E., Schumacher, F.R., Rennert, G., Giles, G.G., Hampel, H., Brenner, H., Oze, I., Oh, J.H., Lee, J.K., Schneider, J.L., Chang-Claude, J., Kim, J., Huyghe, J.R., Zheng, J., Hampe, J., Greenson, J., Hopper, J.L., Palmer, J.R., Visvanathan, K., Matsuo, K., Matsuda, K., Jung, K.J., Li, L., Le Marchand, L., Vodickova, L., Bujanda, L., Gunter, M.J., Matejcic, M., Jenkins, M.A., Slattery, M.L., D’Amato, M., Wang, M., Hoffmeister, M., Woods, M.O., Kim, M., Song, M., Iwasaki, M., Du, M., Udaltsova, N., Sawada, N., Vodicka, P., Campbell, P.T., Newcomb, P.A., Cai, Q., Pearlman, R., Pai, R.K., Schoen, R.E., Steinfelder, R.S., Haile, R.W., Vandenputtelaar, R., Prentice, R.L., Küry, S., Castellví-Bel, S., Tsugane, S., Berndt, S.I., Lee, S.C., Brezina, S., Weinstein, S.J., Chanock, S.J., Jee, S.H., Kweon, S.-S., Vadaparampil, S., Harrison, T.A., Yamaji, T., Keku, T.O., Vymetalkova, V., Arndt, V., Jia, W.-H., Shu, X.-O., Lin, Y., Ahn, Y.-O., Stadler, Z.K., Van Guelpen, B., Ulrich, C.M., Platz, E.A., Potter, J.D., Li, C.I., Meester, R., Moreno, V., Figueiredo, J.C., Casey, G., Lansdorp Vogelaar, I., Dunlop, M.G., Gruber, S.B., Hayes, R.B., Pharoah, P.D.P., Houlston, R.S., Jarvik, G.P., Tomlinson, I.P., Zheng, W., Corley, D.A., Peters, U., Hsu, L.
بيانات النشر: Springer
سنة النشر: 2023
المجموعة: White Rose Research Online (Universities of Leeds, Sheffield & York)
الوصف: Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.
نوع الوثيقة: article in journal/newspaper
وصف الملف: text
اللغة: English
العلاقة: https://eprints.whiterose.ac.uk/206626/1/s41467-023-41819-0.pdfTest; Thomas, M. orcid.org/0000-0001-9337-7015 , Su, Y.-R., Rosenthal, E.A. orcid.org/0000-0001-6042-4487 et al. (126 more authors) (2023) Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations. Nature Communications, 14. 6147. ISSN 2041-1723
الإتاحة: https://eprints.whiterose.ac.uk/206626Test/
https://eprints.whiterose.ac.uk/206626/1/s41467-023-41819-0.pdfTest
https://www.nature.com/articles/s41467-023-41819-0Test
حقوق: cc_by_4
رقم الانضمام: edsbas.5845049B
قاعدة البيانات: BASE