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Capture Hi-C identifies putative target genes at 33 breast cancer risk loci

Genome-wide association studies (GWAS) have identified approximately 100 breast cancer risk loci. Translating these findings into a greater understanding of the mechanisms that influence disease risk requires identification of the genes or non-coding RNAs that mediate these associations. Here, we us...

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Autores principales: Baxter, Joseph S., Leavy, Olivia C., Dryden, Nicola H., Maguire, Sarah, Johnson, Nichola, Fedele, Vita, Simigdala, Nikiana, Martin, Lesley-Ann, Andrews, Simon, Wingett, Steven W., Assiotis, Ioannis, Fenwick, Kerry, Chauhan, Ritika, Rust, Alistair G., Orr, Nick, Dudbridge, Frank, Haider, Syed, Fletcher, Olivia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5847529/
https://www.ncbi.nlm.nih.gov/pubmed/29531215
http://dx.doi.org/10.1038/s41467-018-03411-9
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author Baxter, Joseph S.
Leavy, Olivia C.
Dryden, Nicola H.
Maguire, Sarah
Johnson, Nichola
Fedele, Vita
Simigdala, Nikiana
Martin, Lesley-Ann
Andrews, Simon
Wingett, Steven W.
Assiotis, Ioannis
Fenwick, Kerry
Chauhan, Ritika
Rust, Alistair G.
Orr, Nick
Dudbridge, Frank
Haider, Syed
Fletcher, Olivia
author_facet Baxter, Joseph S.
Leavy, Olivia C.
Dryden, Nicola H.
Maguire, Sarah
Johnson, Nichola
Fedele, Vita
Simigdala, Nikiana
Martin, Lesley-Ann
Andrews, Simon
Wingett, Steven W.
Assiotis, Ioannis
Fenwick, Kerry
Chauhan, Ritika
Rust, Alistair G.
Orr, Nick
Dudbridge, Frank
Haider, Syed
Fletcher, Olivia
author_sort Baxter, Joseph S.
collection PubMed
description Genome-wide association studies (GWAS) have identified approximately 100 breast cancer risk loci. Translating these findings into a greater understanding of the mechanisms that influence disease risk requires identification of the genes or non-coding RNAs that mediate these associations. Here, we use Capture Hi-C (CHi-C) to annotate 63 loci; we identify 110 putative target genes at 33 loci. To assess the support for these target genes in other data sources we test for associations between levels of expression and SNP genotype (eQTLs), disease-specific survival (DSS), and compare them with somatically mutated cancer genes. 22 putative target genes are eQTLs, 32 are associated with DSS and 14 are somatically mutated in breast, or other, cancers. Identifying the target genes at GWAS risk loci will lead to a greater understanding of the mechanisms that influence breast cancer risk and prognosis.
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spelling pubmed-58475292018-03-15 Capture Hi-C identifies putative target genes at 33 breast cancer risk loci Baxter, Joseph S. Leavy, Olivia C. Dryden, Nicola H. Maguire, Sarah Johnson, Nichola Fedele, Vita Simigdala, Nikiana Martin, Lesley-Ann Andrews, Simon Wingett, Steven W. Assiotis, Ioannis Fenwick, Kerry Chauhan, Ritika Rust, Alistair G. Orr, Nick Dudbridge, Frank Haider, Syed Fletcher, Olivia Nat Commun Article Genome-wide association studies (GWAS) have identified approximately 100 breast cancer risk loci. Translating these findings into a greater understanding of the mechanisms that influence disease risk requires identification of the genes or non-coding RNAs that mediate these associations. Here, we use Capture Hi-C (CHi-C) to annotate 63 loci; we identify 110 putative target genes at 33 loci. To assess the support for these target genes in other data sources we test for associations between levels of expression and SNP genotype (eQTLs), disease-specific survival (DSS), and compare them with somatically mutated cancer genes. 22 putative target genes are eQTLs, 32 are associated with DSS and 14 are somatically mutated in breast, or other, cancers. Identifying the target genes at GWAS risk loci will lead to a greater understanding of the mechanisms that influence breast cancer risk and prognosis. Nature Publishing Group UK 2018-03-12 /pmc/articles/PMC5847529/ /pubmed/29531215 http://dx.doi.org/10.1038/s41467-018-03411-9 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Baxter, Joseph S.
Leavy, Olivia C.
Dryden, Nicola H.
Maguire, Sarah
Johnson, Nichola
Fedele, Vita
Simigdala, Nikiana
Martin, Lesley-Ann
Andrews, Simon
Wingett, Steven W.
Assiotis, Ioannis
Fenwick, Kerry
Chauhan, Ritika
Rust, Alistair G.
Orr, Nick
Dudbridge, Frank
Haider, Syed
Fletcher, Olivia
Capture Hi-C identifies putative target genes at 33 breast cancer risk loci
title Capture Hi-C identifies putative target genes at 33 breast cancer risk loci
title_full Capture Hi-C identifies putative target genes at 33 breast cancer risk loci
title_fullStr Capture Hi-C identifies putative target genes at 33 breast cancer risk loci
title_full_unstemmed Capture Hi-C identifies putative target genes at 33 breast cancer risk loci
title_short Capture Hi-C identifies putative target genes at 33 breast cancer risk loci
title_sort capture hi-c identifies putative target genes at 33 breast cancer risk loci
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5847529/
https://www.ncbi.nlm.nih.gov/pubmed/29531215
http://dx.doi.org/10.1038/s41467-018-03411-9
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