Abstract
Original language | English |
---|---|
Pages (from-to) | 56-73 |
Number of pages | 18 |
Journal | Nat. Genet. |
Volume | 52 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- transcription factor
- tumor marker
- apoptosis
- Article
- binding site
- breast cancer
- cancer risk
- chromatin
- controlled study
- female
- gene expression
- gene linkage disequilibrium
- gene mapping
- gene ontology
- genetic variability
- genome-wide association study
- genomics
- human
- human cell
- human tissue
- immune system
- MCF-7 cell line
- priority journal
- quantitative trait locus
- Bayes theorem
- breast tumor
- chromosomal mapping
- genetic predisposition
- genetics
- procedures
- regulatory sequence
- risk factor
- single nucleotide polymorphism
- Bayes Theorem
- Biomarkers, Tumor
- Breast Neoplasms
- Chromosome Mapping
- Female
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Humans
- Linkage Disequilibrium
- Polymorphism, Single Nucleotide
- Quantitative Trait Loci
- Regulatory Sequences, Nucleic Acid
- Risk Factors
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Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes : Nature Genetics. / GWASs - Genome-wide association studies.
In: Nat. Genet., Vol. 52, No. 1, 2020, p. 56-73.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes
T2 - Nature Genetics
AU - GWASs - Genome-wide association studies
AU - Fachal, L.
AU - Aschard, H.
AU - Beesley, J.
AU - Barnes, D.R.
AU - Allen, J.
AU - Kar, S.
AU - Pooley, K.A.
AU - Dennis, J.
AU - Michailidou, K.
AU - Turman, C.
AU - Soucy, P.
AU - Lemaçon, A.
AU - Lush, M.
AU - Tyrer, J.P.
AU - Ghoussaini, M.
AU - Marjaneh, M.M.
AU - Jiang, X.
AU - Agata, S.
AU - Aittomäki, K.
AU - Alonso, M.R.
AU - Andrulis, I.L.
AU - Anton-Culver, H.
AU - Antonenkova, N.N.
AU - Arason, A.
AU - Arndt, V.
AU - Aronson, K.J.
AU - Arun, B.K.
AU - Auber, B.
AU - Auer, P.L.
AU - Azzollini, J.
AU - Balmaña, J.
AU - Barkardottir, R.B.
AU - Barrowdale, D.
AU - Beeghly-Fadiel, A.
AU - Benitez, J.
AU - Bermisheva, M.
AU - Bialkowska, K.
AU - Blanco, A.M.
AU - Blomqvist, C.
AU - Bonanni, B.
AU - Mari, V.
AU - Chiesa, J.
AU - Leone, M.
AU - Caputo, S.
AU - Gambino, G.
AU - Manoukian, S.
AU - Montagna, M.
AU - Peissel, B.
AU - Radice, P.
AU - Viel, A.
N1 - Cited By :14 Export Date: 17 February 2021 CODEN: NGENE Correspondence Address: Dunning, A.M.; Centre for Cancer Genetic Epidemiology, United Kingdom; email: amd24@medschl.cam.ac.uk Chemicals/CAS: Biomarkers, Tumor Funding details: 634935 Funding details: National Institutes of Health, NIH, U19 CA148065, X01HG007492 Funding details: Genome Canada Funding details: Horizon 2020 Framework Programme, H2020, 656144 Funding details: Ministère de l'Économie, de l’Innovation et des Exportations du Québec, MEIE Funding details: Fondation du cancer du sein du Québec, FCSQ Funding details: Government of Canada Funding details: Canadian Institutes of Health Research, CIHR Funding details: Medical Research Council, MRC, MC_PC_14105 Funding details: Cancer Research UK, CRUK, C1287/A10118, C1287/A16563, C8197/A16565 Funding details: European Commission, EC, C1287/A10710, HEALTH-F2-2009-223175 Funding details: National Cancer Institute, Cairo University, NCI Funding details: Seventh Framework Programme, FP7, 223175, 633784 Funding details: Ministero dello Sviluppo Economico, MiSE, PSR-SIIRI-701, U19 CA 148065 Funding text 1: We thank all of the individuals who took part in these studies, as well as all of the researchers, clinicians, technicians and administrative staff who enabled this work to be carried out. This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under Marie Sklodowska-Curie grant agreement number 656144. Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project (funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie de la Science et de l’Innovation du Québec’ (through Genome Québec) and the Quebec Breast Cancer Foundation); the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118, C8197/A16565 and C1287/A16563). BCAC is funded by Cancer Research UK (C1287/A16563), by the European Community’s Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec (grant PSR-SIIRI-701). Combining of the GWAS data was supported in part by NIH Cancer Post-Cancer GWAS initiative grant U19 CA 148065 (DRIVE; part of the GAME-ON initiative). For a full description of funding and acknowledgments, see the Supplementary Note. 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PY - 2020
Y1 - 2020
N2 - Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes. © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
AB - Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes. © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
KW - transcription factor
KW - tumor marker
KW - apoptosis
KW - Article
KW - binding site
KW - breast cancer
KW - cancer risk
KW - chromatin
KW - controlled study
KW - female
KW - gene expression
KW - gene linkage disequilibrium
KW - gene mapping
KW - gene ontology
KW - genetic variability
KW - genome-wide association study
KW - genomics
KW - human
KW - human cell
KW - human tissue
KW - immune system
KW - MCF-7 cell line
KW - priority journal
KW - quantitative trait locus
KW - Bayes theorem
KW - breast tumor
KW - chromosomal mapping
KW - genetic predisposition
KW - genetics
KW - procedures
KW - regulatory sequence
KW - risk factor
KW - single nucleotide polymorphism
KW - Bayes Theorem
KW - Biomarkers, Tumor
KW - Breast Neoplasms
KW - Chromosome Mapping
KW - Female
KW - Genetic Predisposition to Disease
KW - Genome-Wide Association Study
KW - Humans
KW - Linkage Disequilibrium
KW - Polymorphism, Single Nucleotide
KW - Quantitative Trait Loci
KW - Regulatory Sequences, Nucleic Acid
KW - Risk Factors
U2 - 10.1038/s41588-019-0537-1
DO - 10.1038/s41588-019-0537-1
M3 - Article
VL - 52
SP - 56
EP - 73
JO - Nat. Genet.
JF - Nat. Genet.
SN - 1061-4036
IS - 1
ER -