Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses
Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses
Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype
1–3. 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.
572–581
Zhang, Haoyu
73010046-df4a-4e67-9831-c79ab96ff80c
Ahearn, Thomas U.
d39b659c-4972-4295-8553-2a441143878c
Lecarpentier, Julie
b47aa9ae-5d41-49ee-b65c-b08b38daf800
Eccles, Diana
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
June 2020
Zhang, Haoyu
73010046-df4a-4e67-9831-c79ab96ff80c
Ahearn, Thomas U.
d39b659c-4972-4295-8553-2a441143878c
Lecarpentier, Julie
b47aa9ae-5d41-49ee-b65c-b08b38daf800
Eccles, Diana
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
Zhang, Haoyu, Ahearn, Thomas U. and Lecarpentier, Julie
,
et al.
(2020)
Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.
Nature Genetics, 52 (6), .
(doi:10.1038/s41588-020-0609-2).
Abstract
Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype
1–3. 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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Discovery_SNPs_paper_09052019
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Accepted/In Press date: 23 January 2020
e-pub ahead of print date: 18 May 2020
Published date: June 2020
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Funding Information:
We thank all of the individuals who took part in these studies, and all of the researchers, clinicians, technicians and administrative staff who enabled this work to be carried out. This project has been funded in part with Federal funds from the National Cancer Institute Intramural Research Program, National Institutes of Health. Genotyping for the OncoArray was funded by the government of Canada through Genome Canada and the Canadian Institutes of Health Research (GPH-129344), the Ministère de l'Économie et de la Science et de l'Innovation du Québec through Génome Québec, the Quebec Breast Cancer Foundation for the PERSPECTIVE project, the US National Institutes of Health (NIH) (1U19 CA148065 for the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project and X01HG007492 to the Center for Inherited Disease Research under contract HHSN268201200008I), Cancer Research UK (C1287/A16563), the Odense University Hospital Research Foundation (Denmark), the National R&D Program for Cancer Control–Ministry of Health and Welfare (Republic of Korea; 1420190), the Italian Association for Cancer Research (AIRC; IG16933), the Breast Cancer Research Foundation, the National Health and Medical Research Council (Australia) and German Cancer Aid (110837). Genotyping for the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710, C1287/A10118 and C12292/A11174), NIH grants (CA128978, CA116167 and CA176785) and the Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 (GAME-ON initiative)), an NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, the Ministère de l'Économie, Innovation et Exportation du Québec (PSR-SIIRI-701), the Komen Foundation for the Cure, the Breast Cancer Research Foundation and the Ovarian Cancer Research Fund. Combination of the GWAS data was supported in part by the NIH Cancer Post-Cancer GWAS initiative (1U19 CA148065) (DRIVE, part of the GAME-ON initiative). Linkage disequilibrium score regression analysis was supported by grant CA194393. BCAC was funded by Cancer Research UK (C1287/A16563) and by the European Union via its Seventh Framework Programme (HEALTH-F2-2009-223175; COGS) and the Horizon 2020 Research and Innovation Programme (633784 (B-CAST) and 634935 (BRIDGES)). CIMBA was funded by Cancer Research UK (C12292/A20861 and C12292/A11174). N.C. was funded by NHGRI (1R01 HG010480-01). For a full description of funding and acknowledgments, see the Supplementary Note.
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© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
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Local EPrints ID: 444258
URI: http://eprints.soton.ac.uk/id/eprint/444258
ISSN: 1061-4036
PURE UUID: f2dce79d-d474-4d8b-ad80-fcde8acc9910
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Last modified: 17 Mar 2024 05:16
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Author:
Haoyu Zhang
Author:
Thomas U. Ahearn
Author:
Julie Lecarpentier
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