Journal article
Estimating single nucleotide polymorphism associations using pedigree data: Applications to breast cancer
DR Barnes, D Barrowdale, J Beesley, X Chen, PA James, JL Hopper, D Goldgar, G Chenevix-Trench, AC Antoniou, G Mitchell
British Journal of Cancer | Published : 2013
DOI: 10.1038/bjc.2013.277
Abstract
Background: Pedigrees with multiple genotyped family members have been underutilised in breast cancer (BC) geneticassociation studies. We developed a pedigree-based analytical framework to characterise single-nucleotide polymorphism (SNP) associations with BC risk using data from 736 BC families ascertained through multiple affected individuals. On average, eight family members had been genotyped for 24 SNPs previously associated with BC. Methods: Breast cancer incidence was modelled on the basis of SNP effects and residual polygenic effects. Relative risk (RR) estimates were obtained by maximising the retrospective likelihood (RL) of observing the family genotypes conditional on all disease..
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Awarded by Cancer Research UK
Funding Acknowledgements
This research was funded by Cancer Australia's Priority-driven Collaborative Cancer Research Scheme no. 566791. DRB is funded by a Cancer Research UK studentship (C12292/A11168). ACA is a Cancer Research UK Senior Cancer Research Fellow. GC-T is an NHMRC Senior Principal Research Fellow. We thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (funded 2001-2009 by NHMRC and currently by the National Breast Cancer Foundation and Cancer Australia no. 628333) for their contributions to this resource, and the many families who contribute to kConFab. kConFab is supported by grants from the National Breast Cancer Foundation, the National Health and Medical Research Council (NHMRC) and by the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. We also thank the Australian Ovarian Cancer Study Management Group (D. Bowtell, P. M. Webb, A. deFazio, D. Gertig, A. Green, P. Parsons, N. Hayward and D. Whiteman) for the AOCS data.