Comparative fine-mapping of breast cancer susceptibility loci using summary statistics methods and multinomial regression
strongly influences results, and combining analytical approaches with functional validation can improve causal variant identification.
Authors
- K Kyriaki Michailidou
- Joe Dennis (ORCID: https://orcid.org/0000-0003-4591-1214)
- Diptavo Dutta (ORCID: https://orcid.org/0000-0002-6634-9040)
- Georgia Chenevix‐Trench (ORCID: https://orcid.org/0000-0002-1878-2587)
- Denise G O'Mahony (ORCID: https://orcid.org/0000-0002-7212-0920)
- Maria Zanti (ORCID: https://orcid.org/0000-0002-0136-9921)
- VN Kristensen
- Peter Kraft
- Jonathan Beasley
- Douglas F Easton
Institutions
- Oslo University Hospital (NO)
- National Institutes of Health (US)
- The University of Queensland (AU)
- University of Oslo (NO)
- QIMR Berghofer Medical Research Institute (AU)
- University of Cambridge (GB)
- Cancer Research UK Cambridge Center (GB)
- National Cancer Institute (US)
- MRC Epidemiology Unit (GB)
- Cyprus Institute of Neurology and Genetics (CY)
Publication Details
- Journal
- medRxiv
- Published
- 2026-04-22
- DOI
- https://doi.org/10.64898/2026.04.21.26351364
- Primary Topic
- BRCA gene mutations in cancer
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Genome Canada
- Government of Canada
- Cancer Research UK
- National Institute for Health and Care Research
- European Commission
- National Institutes of Health
- Horizon 2020 Framework Programme
- Canadian Institutes of Health Research
- NIHR Cambridge Biomedical Research Centre