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Prediction of breast cancer risk based on profiling with common genetic variants

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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  • Kyriaki Michailidou
  • Jonathan Tyrer
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  • Manjeet K Bolla
  • Qin Wang
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  • Robert Luben
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  • Frank Dudbridge
  • Nichola Johnson
  • Marjanka K Schmidt
  • Annegien Broeks
  • Senno Verhoef
  • Emiel J Rutgers
  • Anthony Swerdlow
  • Alan Ashworth
  • Nick Orr
  • Minouk J Schoemaker
  • Jonine Figueroa
  • Stephen J Chanock
  • Louise Brinton
  • Jolanta Lissowska
  • Fergus J Couch
  • Janet E Olson
  • Celine Vachon
  • Vernon S Pankratz
  • Diether Lambrechts
  • Hans Wildiers
  • Chantal Van Ongeval
  • Erik van Limbergen
  • Vessela Kristensen
  • Grethe Grenaker Alnæs
  • Silje Nord
  • Anne-Lise Borresen-Dale
  • Heli Nevanlinna
  • Taru A Muranen
  • Kristiina Aittomäki
  • Carl Blomqvist
  • Jenny Chang-Claude
  • Anja Rudolph
  • Petra Seibold
  • Dieter Flesch-Janys
  • Peter A Fasching
  • Lothar Haeberle
  • Arif B Ekici
  • Matthias W Beckmann
  • Barbara Burwinkel
  • Frederik Marme
  • Andreas Schneeweiss
  • Christof Sohn
  • Amy Trentham-Dietz
  • Polly Newcomb
  • Linda Titus
  • Kathleen M Egan
  • David J Hunter
  • Sara Lindstrom
  • Rulla M Tamimi
  • Peter Kraft
  • Nazneen Rahman
  • Clare Turnbull
  • Anthony Renwick
  • Sheila Seal
  • Jingmei Li
  • Jianjun Liu
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  • Javier Benitez
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BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.

METHODS: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates.

RESULTS: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer.

CONCLUSIONS: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

OriginalsprogEngelsk
TidsskriftNational Cancer Institute. Journal (Print)
Vol/bind107
Udgave nummer5
ISSN0027-8874
DOI
StatusUdgivet - maj 2015

ID: 45699891