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@ARTICLE{ScannellBryan:137598,
      author       = {M. Scannell Bryan and M. Argos and I. L. Andrulis and J. L.
                      Hopper and J. Chang-Claude$^*$ and K. E. Malone and E. M.
                      John and M. D. Gammon and M. B. Daly and M. B. Terry and S.
                      S. Buys and D. Huo and O. I. Olopade and J. M. Genkinger and
                      A. S. Whittemore and F. Jasmine and M. G. Kibriya and L. S.
                      Chen and H. Ahsan},
      title        = {{G}ermline {V}ariation and {B}reast {C}ancer {I}ncidence:
                      {A} {G}ene-{B}ased {A}ssociation {S}tudy and
                      {W}hole-{G}enome {P}rediction of {E}arly-{O}nset {B}reast
                      {C}ancer.},
      journal      = {Cancer epidemiology, biomarkers $\&$ prevention},
      volume       = {27},
      number       = {9},
      issn         = {1538-7755},
      address      = {Philadelphia, Pa.},
      publisher    = {AACR},
      reportid     = {DKFZ-2018-01478},
      pages        = {1057 - 1064},
      year         = {2018},
      abstract     = {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). Of the 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. Cancer
                      Epidemiol Biomarkers Prev; 27(9); 1057-64. ©2018 AACR.},
      cin          = {C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331},
      pnm          = {313 - Cancer risk factors and prevention (POF3-313)},
      pid          = {G:(DE-HGF)POF3-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:29898891},
      pmc          = {pmc:PMC6125194},
      doi          = {10.1158/1055-9965.EPI-17-1185},
      url          = {https://inrepo02.dkfz.de/record/137598},
}