Journal article
A risk prediction algorithm based on family history and common genetic variants: Application to prostate cancer with potential clinical impact
RJ Macinnis, AC Antoniou, RA Eeles, G Severi, AA Al Olama, L Mcguffog, Z Kote-Jarai, M Guy, LT O'Brien, AL Hall, RA Wilkinson, E Sawyer, AT Ardern-Jones, DP Dearnaley, A Horwich, VS Khoo, CC Parker, RA Huddart, N Van As, MR Mccredie Show all
Genetic Epidemiology | WILEY | Published : 2011
DOI: 10.1002/gepi.20605
Abstract
Genome wide association studies have identified several single nucleotide polymorphisms (SNPs) that are independently associated with small increments in risk of prostate cancer, opening up the possibility for using such variants in risk prediction. Using segregation analysis of population-based samples of 4,390 families of prostate cancer patients from the UK and Australia, and assuming all familial aggregation has genetic causes, we previously found that the best model for the genetic susceptibility to prostate cancer was a mixed model of inheritance that included both a recessive major gene component and a polygenic component (P) that represents the effect of a large number of genetic var..
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Awarded by National Cancer Institute
Funding Acknowledgements
Contract grant sponsor: Cancer Research UK; Contract grant numbers: C5047/A3354; C1287/A10118; Contract grant sponsors: The Institute of Cancer Research Everyman Campaign; The Prostate Cancer Research Foundation; Tattersall's; The Whitten Foundation; National Health and Medical Research Council (NHMRC); Contract grant number: 930494; Contract grant sponsor: The National Institutes of Health; Contract grant number: U01 CA89600.