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Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Zhang, Haoyu ; Ahearn, Thomas U ; Lecarpentier, Julie ; Barnes, Daniel ; Beesley, Jonathan ; Qi, Guanghao ; Jiang, Xia ; O'Mara, Tracy A ; Zhao, Ni and Bolla, Manjeet K , et al. (2020) In Nature Genetics 52(6). p.572-581
Abstract

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in... (More)

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

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published
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Nature Genetics
volume
52
issue
6
pages
10 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85085167024
  • pmid:32424353
ISSN
1546-1718
DOI
10.1038/s41588-020-0609-2
language
English
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yes
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bec20543-984a-40de-8ece-aff18cf1a5a9
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2020-05-29 14:26:45
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2021-04-11 05:09:00
@article{bec20543-984a-40de-8ece-aff18cf1a5a9,
  abstract     = {<p>Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P &lt; 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate &lt; 0.05). Five loci showed associations (P &lt; 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.</p>},
  author       = {Zhang, Haoyu and Ahearn, Thomas U and Lecarpentier, Julie and Barnes, Daniel and Beesley, Jonathan and Qi, Guanghao and Jiang, Xia and O'Mara, Tracy A and Zhao, Ni and Bolla, Manjeet K and Dunning, Alison M and Dennis, Joe and Wang, Qin and Ful, Zumuruda Abu and Aittomäki, Kristiina and Andrulis, Irene L and Anton-Culver, Hoda and Arndt, Volker and Aronson, Kristan J and Arun, Banu K and Auer, Paul L and Azzollini, Jacopo and Barrowdale, Daniel and Becher, Heiko and Beckmann, Matthias W and Behrens, Sabine and Benitez, Javier and Bermisheva, Marina and Bialkowska, Katarzyna and Blanco, Ana and Blomqvist, Carl and Bogdanova, Natalia V and Bojesen, Stig E and Bonanni, Bernardo and Bondavalli, Davide and Borg, Ake and Brauch, Hiltrud and Brenner, Hermann and Briceno, Ignacio and Broeks, Annegien and Brucker, Sara Y and Brüning, Thomas and Burwinkel, Barbara and Buys, Saundra S and Byers, Helen and Caldés, Trinidad and Caligo, Maria A and Calvello, Mariarosaria and Campa, Daniele and Hall, Per and Olsson, Håkan},
  issn         = {1546-1718},
  language     = {eng},
  number       = {6},
  pages        = {572--581},
  publisher    = {Nature Publishing Group},
  series       = {Nature Genetics},
  title        = {Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses},
  url          = {http://dx.doi.org/10.1038/s41588-020-0609-2},
  doi          = {10.1038/s41588-020-0609-2},
  volume       = {52},
  year         = {2020},
}