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dc.contributor.authorFachal, Len_US
dc.contributor.authorAschard, Hen_US
dc.contributor.authorBeesley, Jen_US
dc.contributor.authorBarnes, DRen_US
dc.contributor.authorAllen, Jen_US
dc.contributor.authorKar, Sen_US
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dc.contributor.authorHe, Wen_US
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dc.contributor.authorSaunders, Cen_US
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dc.contributor.authorvan der Kolk, LEen_US
dc.contributor.authorvan Rensburg, EJen_US
dc.contributor.authorVega, Aen_US
dc.contributor.authorViel, Aen_US
dc.contributor.authorVijai, Jen_US
dc.contributor.authorVogel, MJen_US
dc.contributor.authorWang, Qen_US
dc.contributor.authorWappenschmidt, Ben_US
dc.contributor.authorWeinberg, CRen_US
dc.contributor.authorWeitzel, JNen_US
dc.contributor.authorWendt, Cen_US
dc.contributor.authorWildiers, Hen_US
dc.contributor.authorWinqvist, Ren_US
dc.contributor.authorWolk, Aen_US
dc.contributor.authorWu, AHen_US
dc.contributor.authorYannoukakos, Den_US
dc.contributor.authorZhang, Yen_US
dc.contributor.authorZheng, Wen_US
dc.contributor.authorHunter, Den_US
dc.contributor.authorPharoah, PDPen_US
dc.contributor.authorChang-Claude, Jen_US
dc.contributor.authorGarcía-Closas, Men_US
dc.contributor.authorSchmidt, MKen_US
dc.contributor.authorMilne, RLen_US
dc.contributor.authorKristensen, VNen_US
dc.contributor.authorFrench, JDen_US
dc.contributor.authorEdwards, SLen_US
dc.contributor.authorAntoniou, ACen_US
dc.contributor.authorChenevix-Trench, Gen_US
dc.contributor.authorSimard, Jen_US
dc.contributor.authorEaston, DFen_US
dc.contributor.authorKraft, Pen_US
dc.contributor.authorDunning, AMen_US
dc.date.accessioned2020-03-02T10:40:37Z
dc.date.issued2020-01-07en_US
dc.identifier.citationNature genetics, 2020, 52 (1), pp. 56 - 73en_US
dc.identifier.issn1061-4036en_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3522
dc.identifier.eissn1546-1718en_US
dc.identifier.doi10.1038/s41588-019-0537-1en_US
dc.description.abstractGenome-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.en_US
dc.formatPrint-Electronicen_US
dc.format.extent56 - 73en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden_US
dc.subjectGEMO Study Collaboratorsen_US
dc.subjectEMBRACE Collaboratorsen_US
dc.subjectKConFab Investigatorsen_US
dc.subjectHEBON Investigatorsen_US
dc.subjectABCTB Investigatorsen_US
dc.subjectHumansen_US
dc.subjectBreast Neoplasmsen_US
dc.subjectGenetic Predisposition to Diseaseen_US
dc.subjectBayes Theoremen_US
dc.subjectRisk Factorsen_US
dc.subjectChromosome Mappingen_US
dc.subjectRegulatory Sequences, Nucleic Aciden_US
dc.subjectLinkage Disequilibriumen_US
dc.subjectPolymorphism, Single Nucleotideen_US
dc.subjectQuantitative Trait Locien_US
dc.subjectFemaleen_US
dc.subjectGenome-Wide Association Studyen_US
dc.subjectBiomarkers, Tumoren_US
dc.titleFine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.en_US
dc.typeJournal Article
dcterms.dateAccepted2019-10-24en_US
rioxxterms.versionofrecord10.1038/s41588-019-0537-1en_US
rioxxterms.licenseref.startdate2020-01-07en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfNature geneticsen_US
pubs.issue1en_US
pubs.notesNot knownen_US
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Aetiological Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Complex Trait Genetics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Functional Genetic Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Aetiological Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Oncogenetics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Oncogenetics
pubs.publication-statusPublisheden_US
pubs.volume52en_US
pubs.embargo.termsNot knownen_US
icr.researchteamComplex Trait Geneticsen_US
icr.researchteamFunctional Genetic Epidemiologyen_US
icr.researchteamAetiological Epidemiologyen_US
icr.researchteamOncogeneticsen_US
dc.contributor.icrauthorJones, Michaelen_US
dc.contributor.icrauthorFletcher, Oliviaen_US
dc.contributor.icrauthorOrr, Nicholasen_US
dc.contributor.icrauthorSchoemaker, Minouken_US
dc.contributor.icrauthorEeles, Rosalinden_US
dc.contributor.icrauthorSwerdlow, Anthonyen_US


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