Use of a novel non-parametric version of DEPTH to identify genomic regions associated with prostate cancer risk
METHODS: We selected 1,854 prostate cancer cases and 1,894 controls from the UK for whom 541,129 SNPs were measured using the Illumina Infinium HumanHap550 array. Confirmation was sought using 4,152 cases and 2,874 controls, ascertained from the UK and Australia, for whom 211,155 SNPs were measured using the iCOGS Illumina Infinium array.
RESULTS: From the DEPTH analysis we identified 14 regions associated with prostate cancer risk that had been reported previously; five of which would not have been identified by conventional logistic regression. We also identified 112 novel putative susceptibility regions.
CONCLUSIONS: DEPTH can reveal new risk-associated regions that would not have been identified using a conventional logistic regression analysis of individual SNPs.
IMPACT: This study demonstrates that the DEPTH algorithm could identify additional genetic susceptibility regions that merit further investigation.
History
Publication title
Cancer Epidemiology, Biomarkers and PreventionVolume
25Issue
12Pagination
1619-1624ISSN
1055-9965Department/School
Menzies Institute for Medical ResearchPublisher
American Association for Cancer ResearchPlace of publication
United StatesRights statement
Copyright 2016 American Association for Cancer ResearchRepository Status
- Restricted