University Library
  • Login
A gateway to Melbourne's research publications
Minerva Access is the University's Institutional Repository. It aims to collect, preserve, and showcase the intellectual output of staff and students of the University of Melbourne for a global audience.
View Item 
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne School of Population and Global Health
  • Melbourne School of Population and Global Health - Research Publications
  • View Item
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne School of Population and Global Health
  • Melbourne School of Population and Global Health - Research Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

    Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

    Thumbnail
    Download
    published version (340.4Kb)

    Citations
    Scopus
    Web of Science
    Altmetric
    11
    10
    Author
    Barrdahl, M; Rudolph, A; Hopper, JL; Southey, MC; Broeks, A; Fasching, PA; Beckmann, MW; Gago-Dominguez, M; Castelao, JE; Guenel, P; ...
    Date
    2017-11-01
    Source Title
    International Journal of Cancer
    Publisher
    WILEY
    University of Melbourne Author/s
    Southey, Melissa; Hopper, John; Milne, Roger; Giles, Graham
    Affiliation
    Melbourne School of Population and Global Health
    Clinical Pathology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Barrdahl, M., Rudolph, A., Hopper, J. L., Southey, M. C., Broeks, A., Fasching, P. A., Beckmann, M. W., Gago-Dominguez, M., Castelao, J. E., Guenel, P., Truong, T., Bojesen, S. E., Gapstur, S. M., Gaudet, M. M., Brenner, H., Arndt, V., Brauch, H., Hamann, U., Mannermaa, A. ,... Chang-Claude, J. (2017). Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium. INTERNATIONAL JOURNAL OF CANCER, 141 (9), pp.1830-1840. https://doi.org/10.1002/ijc.30859.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256463
    DOI
    10.1002/ijc.30859
    Abstract
    Investigating 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 (ORint  = 0.77, 95% CI: 0.67-0.88, pint  = 1.8 × 10-4 ). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16-1.59, pint  = 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 (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10-4 ) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint  = 0.89, 95% CI: 0.83-0.95, pint  = 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.

    Export Reference in RIS Format     

    Endnote

    • Click on "Export Reference in RIS Format" and choose "open with... Endnote".

    Refworks

    • Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References


    Collections
    • Minerva Elements Records [53102]
    • Clinical Pathology - Research Publications [620]
    • Melbourne School of Population and Global Health - Research Publications [5352]
    Minerva AccessDepositing Your Work (for University of Melbourne Staff and Students)NewsFAQs

    BrowseCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    My AccountLoginRegister
    StatisticsMost Popular ItemsStatistics by CountryMost Popular Authors