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dc.contributor.authorBarrdahl, M
dc.contributor.authorRudolph, A
dc.contributor.authorHopper, JL
dc.contributor.authorSouthey, MC
dc.contributor.authorBroeks, A
dc.contributor.authorFasching, PA
dc.contributor.authorBeckmann, MW
dc.contributor.authorGago-Dominguez, M
dc.contributor.authorCastelao, JE
dc.contributor.authorGuénel, P
dc.contributor.authorTruong, T
dc.contributor.authorBojesen, SE
dc.contributor.authorGapstur, SM
dc.contributor.authorGaudet, MM
dc.contributor.authorBrenner, H
dc.contributor.authorArndt, V
dc.contributor.authorBrauch, H
dc.contributor.authorHamann, U
dc.contributor.authorMannermaa, A
dc.contributor.authorLambrechts, D
dc.contributor.authorJongen, L
dc.contributor.authorFlesch-Janys, D
dc.contributor.authorThoene, K
dc.contributor.authorCouch, FJ
dc.contributor.authorGiles, GG
dc.contributor.authorSimard, J
dc.contributor.authorGoldberg, MS
dc.contributor.authorFigueroa, J
dc.contributor.authorMichailidou, K
dc.contributor.authorBolla, MK
dc.contributor.authorDennis, J
dc.contributor.authorWang, Q
dc.contributor.authorEilber, U
dc.contributor.authorBehrens, S
dc.contributor.authorCzene, K
dc.contributor.authorHall, P
dc.contributor.authorCox, A
dc.contributor.authorCross, S
dc.contributor.authorSwerdlow, A
dc.contributor.authorSchoemaker, MJ
dc.contributor.authorDunning, AM
dc.contributor.authorKaaks, R
dc.contributor.authorPharoah, PDP
dc.contributor.authorSchmidt, M
dc.contributor.authorGarcia-Closas, M
dc.contributor.authorEaston, DF
dc.contributor.authorMilne, RL
dc.contributor.authorChang-Claude, J
dc.date.accessioned2017-08-11T09:45:28Z
dc.date.issued2017-11
dc.identifier.citationInternational journal of cancer, 2017, 141 (9), pp. 1830 - 1840
dc.identifier.issn0020-7136
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/763
dc.identifier.eissn1097-0215
dc.identifier.doi10.1002/ijc.30859
dc.description.abstractInvestigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene-environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (OR int  = 0.77, 95% CI: 0.67-0.88, p int  = 1.8 × 10 -4 ). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (OR int =1.36, 95% CI: 1.16-1.59, p int  = 1.9 × 10 -5 ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (OR int  = 1.26, 95% CI: 1.12-1.43, p int =1.8 × 10 -4 ) and between 8q23-rs13267382 and age at first full-term pregnancy (OR int  = 0.89, 95% CI: 0.83-0.95, p int  = 5.2 × 10 -4 ). While these results do not suggest any strong gene-environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.
dc.formatPrint-Electronic
dc.format.extent1830 - 1840
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved
dc.subjectHumans
dc.subjectBreast Neoplasms
dc.subjectGenetic Predisposition to Disease
dc.subjectEstrogen Receptor alpha
dc.subjectRisk Factors
dc.subjectAlcohol Drinking
dc.subjectSmoking
dc.subjectPolymorphism, Single Nucleotide
dc.subjectFemale
dc.subjectCASP8 and FADD-Like Apoptosis Regulating Protein
dc.subjectGenetic Association Studies
dc.subjectGene-Environment Interaction
dc.titleGene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium.
dc.typeJournal Article
dcterms.dateAccepted2017-04-11
rioxxterms.funderThe Institute of Cancer Research
rioxxterms.identifier.projectUnspecified
rioxxterms.versionofrecord10.1002/ijc.30859
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2017-11
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfInternational journal of cancer
pubs.issue9
pubs.notesNot known
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/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Aetiological Epidemiology
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/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Aetiological Epidemiology
pubs.publication-statusPublished
pubs.volume141
pubs.embargo.termsNot known
icr.researchteamAetiological Epidemiologyen_US
dc.contributor.icrauthorSwerdlow, Anthonyen
dc.contributor.icrauthorSchoemaker, Minouken


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