Journal
GUT
Volume 62, Issue 6, Pages 871-881Publisher
BMJ PUBLISHING GROUP
DOI: 10.1136/gutjnl-2011-300537
Keywords
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Categories
Funding
- Cancer Research UK [C348/A12076]
- Bobby Moore Fund
- Scottish Government Chief Scientist Office [K/OPR/2/2/D333, CZB/4/94]
- Medical Research Council [G0000657-53203]
- Centre Grant from CORE as part of the Digestive Cancer Campaign
- Foundation Dr Henri Dubois-Ferriere Dinu Lipatti
- German National Genome Research Network (NGFN) through the PopGen biobank [BmBF 01GR0468]
- National Genotyping Platform
- MediGrid
- services@medigrid projects [01AK803G, 01IG07015B]
- Federal Ministry of Education and Research [ZZ9603]
- Ministry of Cultural Affairs
- Social Ministry of the Federal State of Mecklenburg-West Pomerania
- German Research Council (Deutsche Forschungsgemeinschaft) [BR 1704/6-1, BR 1704/6-3, CH 117/1-1]
- German Federal Ministry for Education and Research [01 KH 0404]
- Stockholm County Council
- Karolinska Institute
- Swedish Cancer Society
- Stockholm Cancer Foundation
- Swedish Research Council
- Fondo de Investigacion Sanitaria/FEDER [06/1384, 06/1712, 08/0024, 08/1276]
- Xunta de Galicia [PGIDIT07PXIB9101209PR]
- Fundacion de Investigacion Medica Mutua Madrilena
- Ministerio de Educacion y Ciencia [SAF 07-64873]
- Asociacion Espanola contra el Cancer (Fundacion Cientifica and Junta de Barcelona)
- Fundacion Olga Torres
- Accion Transversal de Cancer (Instituto de Salud Carlos III)
- Instituto de Salud Carlos III
- Fondo de Investigacion Sanitaria [CP 03-0070]
- Academy of Finland (Finnish Centre of Excellence Program)
- Finnish Cancer Society
- Sigrid Juselius Foundation
- European Commission [9LSHG-CT-2004-512142, QLG2-CT-2001-01861]
- Genome Canada through the Ontario Genomics Institute
- Genome Quebec
- Ministere du Developement Economique et Regional et de la Recherche du Quebec
- Ontario Institute for Cancer Research
- National Cancer Institute of Canada (NCIC) through the Cancer Risk Assessment (CaRE) Program Project Grant
- Colon Cancer Family Registry and PIs
- National Cancer Institute, National Institutes of Health [RFA CA-95-011]
- Ontario Registry for Studies of Familial CRC [U01 CA076783]
- Cancer Research UK
- Bobby Moore Fund [C1298/A8362]
- European Union [CPRB LSHC-CT-2004-503465]
- CORE
- Oxford Biomedical Research Centre
- Medical Research Council
- Bobby Moore Cancer Cancer Research UK [C1298/A8362]
- St. George's Hospital
- [NIH/NCI U01CA122839]
- MRC [MC_U127527198, MC_PC_U127527198, MR/K018647/1] Funding Source: UKRI
- Cancer Research UK [13154, 16459, 12076, 16561] Funding Source: researchfish
- Cancer Research UK
- The Francis Crick Institute [10124] Funding Source: researchfish
- Medical Research Council [MC_U127527198, MC_PC_U127527198] Funding Source: researchfish
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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.
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