Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk

被引：135

作者：

Thomas, Minta ^{[1
]}

Sakoda, Lori C. ^{[1
,2
]}

Hoffmeister, Michael ^{[3
]}

Rosenthal, Elisabeth A. ^{[4
]}

Lee, Jeffrey K. ^{[2
]}

van Duijnhoven, Franzel J. B. ^{[5
]}

Platz, Elizabeth A. ^{[6
,7
]}

Wu, Anna H. ^{[8
]}

Dampier, Christopher H. ^{[9
]}

de la Chapelle, Albert ^{[10
,11
]}

Wolk, Alicja ^{[12
]}

Joshi, Amit D. ^{[13
,14
,15
]}

Burnett-Hartman, Andrea ^{[16
]}

Gsur, Andrea ^{[17
]}

Lindblom, Annika ^{[18
,19
]}

Castells, Antoni ^{[20
]}

Win, Aung Ko ^{[21
]}

Namjou, Bahram ^{[22
,23
,24
]}

Van Guelpen, Bethany ^{[25
,26
]}

Tangen, Catherine M. ^{[27
]}

He, Qianchuan ^{[1
]}

Li, Christopher, I ^{[1
]}

Schafmayer, Clemens ^{[28
]}

Joshu, Corinne E. ^{[6
,7
]}

Ulrich, Cornelia M. ^{[29
,30
]}

Bishop, D. Timothy ^{[31
]}

Buchanan, Daniel D. ^{[32
,33
,34
]}

Schaid, Daniel ^{[35
]}

Drew, David A. ^{[13
,14
]}

Muller, David C. ^{[36
]}

Duggan, David ^{[37
]}

Crosslin, David R. ^{[38
]}

Albanes, Demetrius ^{[39
]}

Giovannucci, Edward L. ^{[15
,40
,41
,42
]}

Larson, Eric ^{[43
]}

Qu, Flora ^{[1
]}

Mentch, Frank ^{[44
]}

Giles, Graham G. ^{[21
,45
,46
]}

Hakonarson, Hakon ^{[44
]}

Hampel, Heather ^{[47
]}

Stanaway, Ian B. ^{[4
]}

Figueiredo, Jane C. ^{[48
,49
]}

Huyghe, Jeroen R. ^{[1
]}

Minnier, Jessica ^{[50
]}

Chang-Claude, Jenny ^{[51
,52
]}

Hampe, Jochen ^{[53
]}

Harley, John B. ^{[22
,23
,24
]}

Visvanathan, Kala ^{[6
,7
]}

Curtis, Keith R. ^{[1
]}

Offit, Kenneth ^{[54
,55
]}

机构：

[1] Fred Hutchinson Canc Res Ctr, Publ Hlth Sci Div, Seattle, WA 98109 USA

[2] Kaiser Permanente Northern Calif, Div Res, Oakland, CA 94612 USA

[3] German Canc Res Ctr, Div Clin Epidemiol & Aging Res, D-69120 Heidelberg, Germany

[4] Univ Washington, Dept Med Med Genet, Med Ctr, Seattle, WA 98195 USA

[5] Wageningen Univ & Res, Div Human Nutr & Hlth, NL-176700 Wageningen, Netherlands

[6] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD 21287 USA

[7] Sidney Kimmel Comprehens Canc Ctr Johns Hopkins, Baltimore, MD 21287 USA

[8] Univ Southern Calif, Preventat Med, Los Angeles, CA 90089 USA

[9] Univ Virginia Hlth Syst, Dept Surg, Charlottesville, VA 22903 USA

[10] Ohio State Univ, Dept Canc Biol & Genet, Columbus, OH 43210 USA

[11] Ohio State Univ, Comprehens Canc Ctr, Columbus, OH 43210 USA

[12] Karolinska Inst, Inst Environm Med, S-17177 Stockholm, Sweden

[13] Massachusetts Gen Hosp, Clin & Translat Epidemiol Unit, Boston, MA 02114 USA

[14] Harvard Med Sch, Boston, MA 02114 USA

[15] Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA

[16] Kaiser Permanente Colorado, Inst Hlth Res, Denver, CO 80014 USA

[17] Med Univ Vienna, Inst Canc Res, Dept Med 1, A-1090 Vienna, Austria

[18] Karolinska Univ Hosp, Dept Clin Genet, S-17177 Stockholm, Sweden

[19] Karolinska Inst, Dept Mol Med & Surg, S-17177 Stockholm, Sweden

[20] Univ Barcelona, Hosp Clin, Gastroenterol Dept,Ctr Invest Biomed Red Enfermed, Inst Invest Biomed August Pi i Sunyer IDIBAP, Barcelona 08007, Spain

[21] Univ Melbourne, Ctr Epidemiol & Biostat, Melbourne Sch Populat & Global Hlth, Melbourne, Vic 3000, Australia

[22] Cincinnati Childrens Hosp Med Ctr, Ctr Autoimmune Genom & Etiol CAGE, Cincinnati, OH 45229 USA

[23] Univ Cincinnati, Coll Med, Cincinnati, OH 45229 USA

[24] Cincinnati VA Med Ctr, Cincinnati, OH 45229 USA

[25] Umea Univ, Dept Radiat Sci, Oncol Unit, S-90187 Umea, Sweden

[26] Umea Univ, Wallenberg Ctr Mol Med, S-90187 Umea, Sweden

[27] Fred Hutchinson Canc Res Ctr, SWOG Stat Ctr, Seattle, WA 98109 USA

[28] Univ Hosp Rostock, Dept Gen Surg, D-18051 Rostock, Germany

[29] Univ Utah, Huntsman Canc Inst, Salt Lake City, UT 84112 USA

[30] Univ Utah, Dept Populat Hlth Sci, Salt Lake City, UT 84112 USA

[31] Univ Leeds, Leeds Inst Canc & Pathol, Leeds LS2 9JT, W Yorkshire, England

[32] Univ Melbourne, Victorian Comprehens Canc Ctr, Ctr Canc Res, Parkville, Vic 3010, Australia

[33] Univ Melbourne, Dept Clin Pathol, Colorectal Oncogen Grp, Parkville, Vic 3010, Australia

[34] Royal Melbourne Hosp, Genom Med & Family Canc Clin, Parkville, Vic 3010, Australia

[35] Mayo Clin, Dept Hlth Sci Res, Rochester, MN 55905 USA

[36] Imperial Coll London, Sch Publ Hlth, London SW7 2AZ, England

[37] City Hope Natl Med Ctr, Translat Genom Res Inst, Phoenix, AZ 85003 USA

[38] Univ Washington, Dept Bioinformat & Med Educ, Med Ctr, Seattle, WA 98195 USA

[39] NCI, Div Canc Epidemiol & Genet, NIH, Bethesda, MD 20892 USA

[40] Brigham & Womens Hosp, Channing Div Network Med, Boston, MA 02115 USA

[41] Harvard Med Sch, Boston, MA 02115 USA

[42] Harvard Univ, Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA 02108 USA

[43] Kaiser Permanente Washington Res Inst, Seattle, WA 98101 USA

[44] Childrens Hosp Philadelphia, Ctr Appl Genom, Philadelphia, PA 19104 USA

[45] Canc Council Victoria, Canc Epidemiol Div, 615 St Kilda Rd, Melbourne, Vic 3004, Australia

[46] Monash Univ, Sch Clin Sci, Precis Med, Monash Hlth, Clayton, Vic 3168, Australia

[47] Ohio State Univ, Dept Internal Med, Div Human Genet, Comprehens Canc Ctr, Columbus, OH 43210 USA

[48] Cedars Sinai Med Ctr, Samuel Oschin Comprehens Canc Inst, Dept Med, Los Angeles, CA 90048 USA

[49] Univ Southern Calif, Keck Sch Med, Dept Prevent Med, Los Angeles, CA 90033 USA

[50] Oregon Hlth & Sci Univ, Sch Publ Hlth, Portland, OR 97239 USA

来源：

AMERICAN JOURNAL OF HUMAN GENETICS | 2020年 / 107卷 / 03期

关键词：

LINKAGE DISEQUILIBRIUM; PREDICTION; ASSOCIATION; PERFORMANCE; POPULATION; HEALTH;

D O I：

10.1016/j.ajhg.2020.07.006

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

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 linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.

引用

页码：432 / 444

页数：13

共 49 条

[1] Performance and Robustness of Penalized and Unpenalized Methods for Genetic Prediction of Complex Human Disease [J].

Abraham, Gad ;

Kowalczyk, Adam ;

Zobel, Justin ;

Inouye, Michael .

GENETIC EPIDEMIOLOGY, 2013, 37 (02) :184-195

[2] Importance of patient-centered care in enhancing patient well-being: a cancer survivor's perspective [J].

Arora, Neeraj K. .

QUALITY OF LIFE RESEARCH, 2009, 18 (01) :1-4

[3] Enrichment of colorectal cancer associations in functional regions: Insight for using epigenomics data in the analysis of whole genome sequence-imputed GWAS data [J].

Bien, Stephanie A. ;

Auer, Paul L. ;

Harrison, Tabitha A. ;

Qu, Conghui ;

Connolly, Charles M. ;

Greenside, Peyton G. ;

Chen, Sai ;

Berndt, Sonja I. ;

Bezieau, Stephane ;

Kang, Hyun M. ;

Huyghe, Jeroen ;

Brenner, Hermann ;

Casey, Graham ;

Chan, Andrew T. ;

Hopper, John L. ;

Banbury, Barbara L. ;

Chang-Claude, Jenny ;

Chanock, Stephen J. ;

Haile, Robert W. ;

Hoffmeister, Michael ;

Fuchsberger, Christian ;

Jenkins, Mark A. ;

Leal, Suzanne M. ;

Lemire, Mathieu ;

Newcomb, Polly A. ;

Gallinger, Steven ;

Potter, John D. ;

Schoen, Robert E. ;

Slattery, Martha L. ;

Smith, Joshua D. ;

Le Marchand, Loic ;

White, Emily ;

Zanke, Brent W. ;

Abecasis, Goncalo R. ;

Carlson, Christopher S. ;

Peters, Ulrike ;

Nickerson, Deborah A. ;

Kundaje, Anshul ;

Hsu, Li .

PLOS ONE, 2017, 12 (11)

[4] Mapping complex traits using Random Forests [J].

Bureau, A ;

Dupuis, J ;

Hayward, B ;

Falls, K ;

Van Eerdewegh, P .

BMC GENETICS, 2003, 4 (Suppl 1)

[5] Second-generation PLINK: rising to the challenge of larger and richer datasets [J].

Chang, Christopher C. ;

Chow, Carson C. ;

Tellier, Laurent C. A. M. ;

Vattikuti, Shashaank ;

Purcell, Shaun M. ;

Lee, James J. .

GIGASCIENCE, 2015, 4

[6] Projecting the performance of risk prediction based on polygenic analyses of genome-wide association studies [J].

Chatterjee, Nilanjan ;

Wheeler, Bill ;

Sampson, Joshua ;

Hartge, Patricia ;

Chanock, Stephen J. ;

Park, Ju-Hyun .

NATURE GENETICS, 2013, 45 (04) :400-405

[7] Complications of diagnostic within a defined population and therapeutic colonoscopy in Sweden [J].

Dafnis, G ;

Ekbom, A ;

Pahlman, L ;

Blomqvist, P .

GASTROINTESTINAL ENDOSCOPY, 2001, 54 (03) :302-309

[8] Polygenic risk scores: a biased prediction? [J].

De La Vega, Francisco M. ;

Bustamante, Carlos D. .

GENOME MEDICINE, 2018, 10

[9] The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics [J].

de Vlaming, Ronald ;

Groenen, Patrick J. F. .

BIOMED RESEARCH INTERNATIONAL, 2015, 2015

[10] Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42 103 individuals [J].

Dunlop, Malcolm G. ;

Tenesa, Albert ;

Farrington, Susan M. ;

Ballereau, Stephane ;

Brewster, David H. ;

Koessler, Thibaud ;

Pharoah, Paul ;

Schafmayer, Clemens ;

Hampe, Jochen ;

Voelzke, Henry ;

Chang-Claude, Jenny ;

Hoffmeister, Michael ;

Brenner, Hermann ;

von Holst, Susanna ;

Picelli, Simone ;

Lindblom, Annika ;

Jenkins, Mark A. ;

Hopper, John L. ;

Casey, Graham ;

Duggan, David ;

Newcomb, Polly A. ;

Abuli, Anna ;

Bessa, Xavier ;

Ruiz-Ponte, Clara ;

Castellvi-Bel, Sergi ;

Niittymaeki, Iina ;

Tuupanen, Sari ;

Karhu, Auli ;

Aaltonen, Lauri ;

Zanke, Brent ;

Hudson, Tom ;

Gallinger, Steven ;

Barclay, Ella ;

Martin, Lynn ;

Gorman, Maggie ;

Carvajal-Carmona, Luis ;

Walther, Axel ;

Kerr, David ;

Lubbe, Steven ;

Broderick, Peter ;

Chandler, Ian ;

Pittman, Alan ;

Penegar, Steven ;

Campbell, Harry ;

Tomlinson, Ian ;

Houlston, Richard S. .

GUT, 2013, 62 (06) :871-881

← 1 2 3 4 5 →