Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42 103 individuals

被引：98

作者：

Dunlop, Malcolm G. ^{[1
]}

Tenesa, Albert ^{[2
]}

Farrington, Susan M. ^{[1
]}

Ballereau, Stephane ^{[1
]}

Brewster, David H. ^{[3
]}

Koessler, Thibaud ^{[4
]}

Pharoah, Paul ^{[4
]}

Schafmayer, Clemens ^{[5
]}

Hampe, Jochen ^{[6
]}

Voelzke, Henry ^{[7
]}

Chang-Claude, Jenny ^{[8
]}

Hoffmeister, Michael ^{[8
]}

Brenner, Hermann ^{[9
]}

von Holst, Susanna ^{[10
]}

Picelli, Simone ^{[10
]}

Lindblom, Annika ^{[10
]}

Jenkins, Mark A. ^{[11
]}

Hopper, John L. ^{[11
]}

Casey, Graham ^{[12
]}

Duggan, David ^{[13
]}

Newcomb, Polly A. ^{[14
]}

Abuli, Anna ^{[15
]}

Bessa, Xavier ^{[15
]}

Ruiz-Ponte, Clara ^{[16
]}

Castellvi-Bel, Sergi ^{[17
]}

Niittymaeki, Iina ^{[18
]}

Tuupanen, Sari ^{[18
]}

Karhu, Auli ^{[18
]}

Aaltonen, Lauri ^{[18
]}

Zanke, Brent ^{[19
]}

Hudson, Tom ^{[20
]}

Gallinger, Steven ^{[21
,22
]}

Barclay, Ella ^{[23
]}

Martin, Lynn ^{[23
]}

Gorman, Maggie ^{[23
]}

Carvajal-Carmona, Luis ^{[23
]}

Walther, Axel ^{[23
]}

Kerr, David ^{[24
]}

Lubbe, Steven ^{[25
]}

Broderick, Peter ^{[25
]}

Chandler, Ian ^{[25
]}

Pittman, Alan ^{[25
]}

Penegar, Steven ^{[25
]}

Campbell, Harry ^{[26
]}

Tomlinson, Ian ^{[23
]}

Houlston, Richard S. ^{[25
]}

机构：

[1] Univ Edinburgh, Inst Genet & Mol Med, Colon Canc Genet Grp, MRC Human Genet Unit, Edinburgh EH4 2XU, Midlothian, Scotland

[2] Univ Edinburgh, Roslin Inst, Roslin, Midlothian, Scotland

[3] NHS Natl Serv Scotland, Informat Serv Div, Scottish Canc Registry, Edinburgh, Midlothian, Scotland

[4] Univ Cambridge, Dept Oncol, Strangeways Res Lab, Cambridge, England

[5] Univ Hosp Schleswig Holstein, POPGEN Biobank, Kiel, Germany

[6] Univ Hosp, Dept Gen Internal Med, Schleswig Holstein, Kiel, Germany

[7] Univ Hosp Greifswald, Inst Community Med, Greifswald, Germany

[8] German Canc Res Ctr, Div Canc Epidemiol, Heidelberg, Germany

[9] German Canc Res Ctr, Div Clin Epidemiol & Ageing Res, Heidelberg, Germany

[10] Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden

[11] Univ Melbourne, Ctr Mol Environm Genet & Analyt Epidemiol, Parkville, Vic 3052, Australia

[12] Univ So Calif, Keck Sch Med, Dept Prevent Med, Los Angeles, CA 90033 USA

[13] Translat Genom Res Inst TGen, Phoenix, AZ USA

[14] Fred Hutchinson Canc Res Ctr, Seattle, WA 98104 USA

[15] Pompeu Fabra Univ, IMIM, Hosp Mar, Dept Gastroenterol, Barcelona, Catalonia, Spain

[16] Univ Santiago de Compostela, Genom Med Grp, FPGMX, CIBERER, Santiago De Compostela, Spain

[17] Univ Barcelona, Hosp Clin, Dept Gastroenterol, CIBERehd, Catalonia, Spain

[18] Univ Helsinki, Dept Med Genet, Biomedicum Helsinki, Helsinki, Finland

[19] Canc Care Ontario, Toronto, ON, Canada

[20] Ontario Inst Canc Res, Toronto, ON, Canada

[21] Mt Sinai Hosp, Samuel Lunenfeld Res Inst, Toronto, ON M5G 1X5, Canada

[22] Univ Toronto, Toronto, ON, Canada

[23] Univ Oxford, Wellcome Trust Ctr Human Genet, Oxford, England

[24] Univ Oxford, Dept Clin Pharmacol, Oxford, England

[25] Inst Canc Res, Sect Canc Genet, Sutton, Surrey, England

[26] Univ Edinburgh, Edinburgh, Midlothian, Scotland

来源：

GUT | 2013年 / 62卷 / 06期

基金：

瑞典研究理事会; 芬兰科学院; 英国医学研究理事会; 美国国家卫生研究院;

关键词：

GENOME-WIDE ASSOCIATION; TYPE-2 DIABETES RISK; FAMILY-HISTORY; SUSCEPTIBILITY LOCI; ADENOMATOUS POLYPS; DISEASE RISK; PREDICTION; SURVEILLANCE; MUTATIONS; CARRIERS;

D O I：

10.1136/gutjnl-2011-300537

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. A study was conducted in a large multi-population study to assess the feasibility of CRC risk prediction using common genetic variant data combined with other risk factors. A risk prediction model was built and applied to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate CRC risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence CRC risk. Risk models were generated from case-control data incorporating genotypes alone (n=39 266) and in combination with gender, age and FH (n=11 324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4187 independent samples. The 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results The median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2x10(-16)), confirmed in external validation sets (Sweden p=1.2x10(-6), Finland p-2x10(-5)). The mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05 to 1.13). Discriminative performance was poor across the risk spectrum (area under curve for genotypes alone 0.57; area under curve for genotype/age/gender/FH 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion Genotype data provide additional information that complements age, gender and FH as risk factors, but individualised genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance.

引用

页码：871 / 881

页数：11

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