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Record W2977390077 · doi:10.1093/ije/dyz193

Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium

2019· article· en· W2977390077 on OpenAlexfundno aff
Pooja Middha, Sara Lindström, Sabine Behrens, Xiaoliang Wang, Kyriaki Michailidou, Manjeet K. Bolla, Qin Wang, Joe Dennis, Alison M. Dunning, Paul D.P. Pharoah, Marjanka K. Schmidt, Peter Kraft, Montserrat García‐Closas, Douglas F. Easton, Roger L. Milne, Jenny Chang‐Claude

Bibliographic record

VenueInternational Journal of Epidemiology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
FundersNiilo Helanderin SäätiöMedical Research and Materiel CommandNational Heart, Lung, and Blood InstituteServicio Gallego de SaludProgramme Grants for Applied ResearchInstituto de Salud Carlos IIICancer Council TasmaniaNational Health and Medical Research CouncilWorld Cancer Research FundMedical Research CouncilCanadian Institutes of Health ResearchNational Institute of Environmental Health SciencesU.S. ArmyNational Institutes of HealthHellenic Health FoundationXunta de GaliciaInstitut Gustave-RoussyCenters for Disease Control and PreventionInstitut National Du CancerDeutsche KrebshilfeSwedish Cancer FoundationAgence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du TravailVetenskapsrådetUniversity of CambridgeGovernment of CanadaMinisterio de Sanidad, Servicios Sociales e IgualdadHealth and Medical Research FundOvarian Cancer Research FundBundesministerium für Bildung und ForschungMinisterio de Economía y CompetitividadInstitut National de la Santé et de la Recherche MédicaleCancer AustraliaAgence Nationale de la RechercheNational Institute on AgingRobert Bosch StiftungAgency for Science, Technology and ResearchCancer Council South AustraliaAmerican Cancer SocietyFonds Wetenschappelijk OnderzoekCancerfondenNational Cancer InstituteCancer Institute NSWFondation de FranceNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchDeutsche Gesetzliche UnfallversicherungGentofte HospitalDivision of Cancer Prevention, National Cancer InstituteNational Institute for Health and Care ResearchAssociazione Italiana per la Ricerca sul CancroGenome CanadaLon V. Smith FoundationFondation du cancer du sein du QuébecNational Breast Cancer FoundationSundhed og Sygdom, Det Frie ForskningsrådCentre International de Recherche sur le CancerDavid F. and Margaret T. Grohne Family FoundationCancer Research UKHamburger KrebsgesellschaftLigue Contre le CancerDeutsches KrebsforschungszentrumVicHealthCancer Council VictoriaCalifornia Department of Public HealthU.S. Department of Health and Human ServicesCancer Council Western AustraliaEuropean CommissionBreast Cancer Research FoundationStavros Niarchos FoundationCancer Council NSWSusan G. Komen for the CureKWF Kankerbestrijding
KeywordsBreast cancerOdds ratioOncologyMedicineSNPCancerSingle-nucleotide polymorphismInternal medicineLogistic regressionEstrogen receptorCase-control studyGenotypeBiologyGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions. METHODS: Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions. RESULTS: Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth. CONCLUSIONS: Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.367
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2019
Admission routes1
Has abstractyes

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