BACKGROUND: Genome-wide association studies have discovered multiple genetic loci associated with breast cancer risk. Investigating these loci would be helpful to evaluate previous findings and identify causal variants for breast cancer. We evaluated index SNPs in 17 of these loci in a study of 1,511 cases and 1,454 controls of European descent. METHODS: We investigated the overall association with breast cancer and among subtypes defined as ER+ (estrogen receptor positive), ER- (estrogen receptor negative) and triple-negative breast cancer (TNBC). Combined effects of SNPs on breast cancer risk were assessed via a genetic risk score. We evaluated the contribution of both genetic variants and traditional risk factors to a breast cancer risk assessment model. RESULTS: Five of the 17 SNPs were significantly associated (P ≤ 0.05) with overall breast cancer in the same direction as previously reported: rs13387042 (2q35/TNP1), rs4973768 (3p24/SLC4A7), rs2046210 (6q25/ESR1), rs1219648 (10q26/FGFR2), and rs4784227 (16q12/TOX3). When stratified by breast cancer subtype, all five SNPs were associated (P < 0.05) with ER+ cancer, three with ER- cancer (rs13387042, rs1219648, and rs4784227), and one with TNBC (rs1219648). A GRS, based on those five significant SNPs, showed strong association with overall breast cancer with ORs (95 % CI) of 1.48 (1.22-1.79), 1.85 (1.52-2.25) and 2.26 (1.82-2.80), respectively, for each quartile, (P = 2.0 × 10(-15)). Traditional risk factors, including previous benign breast disease, breast cancer family history and parity, were significantly associated with breast cancer risk in the present study. These factors, together with the GRS, were used to build a breast cancer risk assessment model with a c statistic of 0.6321 from receiver operating characteristic analysis. The contribution of the GRS to the model was greater than prior benign breast disease, family history and parity with the c statistic change of 0.0374, 0.0324, 0.0103, 0.0012, respectively. CONCLUSIONS: Our study demonstrates that five SNPs were associated with overall breast cancer, with stronger association for ER+ than ER- cancer as previously reported, and suggests that a risk assessment model incorporating the GRS from five loci is useful in identifying women at high risk of breast cancer.
BACKGROUND: Genome-wide association studies have discovered multiple genetic loci associated with breast cancer risk. Investigating these loci would be helpful to evaluate previous findings and identify causal variants for breast cancer. We evaluated index SNPs in 17 of these loci in a study of 1,511 cases and 1,454 controls of European descent. METHODS: We investigated the overall association with breast cancer and among subtypes defined as ER+ (estrogen receptor positive), ER- (estrogen receptor negative) and triple-negative breast cancer (TNBC). Combined effects of SNPs on breast cancer risk were assessed via a genetic risk score. We evaluated the contribution of both genetic variants and traditional risk factors to a breast cancer risk assessment model. RESULTS: Five of the 17 SNPs were significantly associated (P ≤ 0.05) with overall breast cancer in the same direction as previously reported: rs13387042 (2q35/TNP1), rs4973768 (3p24/SLC4A7), rs2046210 (6q25/ESR1), rs1219648 (10q26/FGFR2), and rs4784227 (16q12/TOX3). When stratified by breast cancer subtype, all five SNPs were associated (P < 0.05) with ER+ cancer, three with ER- cancer (rs13387042, rs1219648, and rs4784227), and one with TNBC (rs1219648). A GRS, based on those five significant SNPs, showed strong association with overall breast cancer with ORs (95 % CI) of 1.48 (1.22-1.79), 1.85 (1.52-2.25) and 2.26 (1.82-2.80), respectively, for each quartile, (P = 2.0 × 10(-15)). Traditional risk factors, including previous benign breast disease, breast cancer family history and parity, were significantly associated with breast cancer risk in the present study. These factors, together with the GRS, were used to build a breast cancer risk assessment model with a c statistic of 0.6321 from receiver operating characteristic analysis. The contribution of the GRS to the model was greater than prior benign breast disease, family history and parity with the c statistic change of 0.0374, 0.0324, 0.0103, 0.0012, respectively. CONCLUSIONS: Our study demonstrates that five SNPs were associated with overall breast cancer, with stronger association for ER+ than ER- cancer as previously reported, and suggests that a risk assessment model incorporating the GRS from five loci is useful in identifying women at high risk of breast cancer.
Authors: David J Hunter; Peter Kraft; Kevin B Jacobs; David G Cox; Meredith Yeager; Susan E Hankinson; Sholom Wacholder; Zhaoming Wang; Robert Welch; Amy Hutchinson; Junwen Wang; Kai Yu; Nilanjan Chatterjee; Nick Orr; Walter C Willett; Graham A Colditz; Regina G Ziegler; Christine D Berg; Saundra S Buys; Catherine A McCarty; Heather Spencer Feigelson; Eugenia E Calle; Michael J Thun; Richard B Hayes; Margaret Tucker; Daniela S Gerhard; Joseph F Fraumeni; Robert N Hoover; Gilles Thomas; Stephen J Chanock Journal: Nat Genet Date: 2007-05-27 Impact factor: 38.330
Authors: Simon N Stacey; Andrei Manolescu; Patrick Sulem; Thorunn Rafnar; Julius Gudmundsson; Sigurjon A Gudjonsson; Gisli Masson; Margret Jakobsdottir; Steinunn Thorlacius; Agnar Helgason; Katja K Aben; Luc J Strobbe; Marjo T Albers-Akkers; Dorine W Swinkels; Brian E Henderson; Laurence N Kolonel; Loic Le Marchand; Esther Millastre; Raquel Andres; Javier Godino; Maria Dolores Garcia-Prats; Eduardo Polo; Alejandro Tres; Magali Mouy; Jona Saemundsdottir; Valgerdur M Backman; Larus Gudmundsson; Kristleifur Kristjansson; Jon T Bergthorsson; Jelena Kostic; Michael L Frigge; Frank Geller; Daniel Gudbjartsson; Helgi Sigurdsson; Thora Jonsdottir; Jon Hrafnkelsson; Jakob Johannsson; Thorarinn Sveinsson; Gardar Myrdal; Hlynur Niels Grimsson; Thorvaldur Jonsson; Susanna von Holst; Barbro Werelius; Sara Margolin; Annika Lindblom; Jose I Mayordomo; Christopher A Haiman; Lambertus A Kiemeney; Oskar Th Johannsson; Jeffrey R Gulcher; Unnur Thorsteinsdottir; Augustine Kong; Kari Stefansson Journal: Nat Genet Date: 2007-05-27 Impact factor: 38.330
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