TY - JOUR
T1 - Germline variation and breast cancer incidence
T2 - A gene-based association study and whole-genome prediction of early-onset breast cancer
AU - Bryan, Molly Scannell
AU - Argos, Maria
AU - Andrulis, Irene L.
AU - Hopper, John L.
AU - Jenny, Chang Claude
AU - Malone, Kathleen E.
AU - John, Esther M.
AU - Gammon, Marilie D.
AU - Daly, Mary
AU - Terry, Mary Beth
AU - Buys, Saundra S.
AU - Huo, Dezheng
AU - Olopade, Olufunmilayo I.
AU - Genkinger, Jeanine
AU - Whittemore, Alice S.
AU - Jasmine, Farzana
AU - Kibriya, Muhammad G.
AU - Chen, Lin S.
AU - Ahsan, Habibul
N1 - Publisher Copyright:
© 2018 American Association for Cancer Research.
PY - 2018/9
Y1 - 2018/9
N2 - Background: Although germline genetics influences breast cancer incidence, published research only explains approximately half of the expected association. Moreover, the accuracy of prediction models remains low. For women who develop breast cancer early, the genetic architecture is less established. Methods: To identify loci associated with early-onset breast cancer, gene-based tests were carried out using exome array data from 3,479 women with breast cancer diagnosed before age 50 and 973 age-matched controls. Replication was undertaken in a population that developed breast cancer at all ages of onset. Results: Three gene regions were associated with breast cancer incidence: FGFR2 (P = 1.23 × 10-5; replication P < 1.00 × 10-6), NEK10 (P = 3.57 × 10-4; replication P < 1.00 × 10-6), and SIVA1 (P = 5.49 × 10-4; replication P< 1.00 × 10-6). Ofthe 151 gene regions reported in previous literature, 19 (12.5%) showed evidence of association (P < 0.05) with the risk of early-onset breast cancer in the early-onset population. To predict incidence, whole-genome prediction was implemented on a subset of 3,076 participants who were additionally genotyped on a genome wide array. The whole-genome prediction outperformed a polygenic risk score [AUC, 0.636; 95% confidence interval (CI), 0.614-0.659 compared with 0.601; 95% CI, 0.578-0.623], and when combined with known epidemiologic risk factors, the AUC rose to 0.662 (95% CI, 0.640-0.684). Conclusions: This research supports a role for variation within FGFR2 and NEK10 in breast cancer incidence, and suggests SIVA1 as a novel risk locus. Impact: This analysis supports a shared genetic etiology between women with early- and late-onset breast cancer, and suggests whole-genome data can improve risk assessment.
AB - Background: Although germline genetics influences breast cancer incidence, published research only explains approximately half of the expected association. Moreover, the accuracy of prediction models remains low. For women who develop breast cancer early, the genetic architecture is less established. Methods: To identify loci associated with early-onset breast cancer, gene-based tests were carried out using exome array data from 3,479 women with breast cancer diagnosed before age 50 and 973 age-matched controls. Replication was undertaken in a population that developed breast cancer at all ages of onset. Results: Three gene regions were associated with breast cancer incidence: FGFR2 (P = 1.23 × 10-5; replication P < 1.00 × 10-6), NEK10 (P = 3.57 × 10-4; replication P < 1.00 × 10-6), and SIVA1 (P = 5.49 × 10-4; replication P< 1.00 × 10-6). Ofthe 151 gene regions reported in previous literature, 19 (12.5%) showed evidence of association (P < 0.05) with the risk of early-onset breast cancer in the early-onset population. To predict incidence, whole-genome prediction was implemented on a subset of 3,076 participants who were additionally genotyped on a genome wide array. The whole-genome prediction outperformed a polygenic risk score [AUC, 0.636; 95% confidence interval (CI), 0.614-0.659 compared with 0.601; 95% CI, 0.578-0.623], and when combined with known epidemiologic risk factors, the AUC rose to 0.662 (95% CI, 0.640-0.684). Conclusions: This research supports a role for variation within FGFR2 and NEK10 in breast cancer incidence, and suggests SIVA1 as a novel risk locus. Impact: This analysis supports a shared genetic etiology between women with early- and late-onset breast cancer, and suggests whole-genome data can improve risk assessment.
KW - Biomarkers, Tumor/genetics
KW - Breast Neoplasms/epidemiology
KW - Exome Sequencing
KW - Female
KW - Follow-Up Studies
KW - Genetic Predisposition to Disease
KW - Genome-Wide Association Study/methods
KW - Genotype
KW - Humans
KW - Incidence
KW - Middle Aged
KW - Polymorphism, Single Nucleotide
KW - Prognosis
UR - http://www.scopus.com/inward/record.url?scp=85053045408&partnerID=8YFLogxK
U2 - 10.1158/1055-9965.EPI-17-1185
DO - 10.1158/1055-9965.EPI-17-1185
M3 - Article
C2 - 29898891
SN - 1055-9965
VL - 27
SP - 1057
EP - 1064
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 9
ER -