Prostate cancer segregation analyses using 4390 families from UK and Australian population-based studies

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MacInnis RJ, Antoniou AC, Eeles RA, Severi G, Guy M, McGuffog L, Hall AL, O'Brien LT, Wilkinson RA, Dearnaley DP, Ardern-Jones AT, Horwich A, Khoo VS, Parker CC, Huddart RA, McCredie MR, Smith C, Southey MC, Staples MP, English DR, Hopper JL, Giles GG, Easton DF (2010) Prostate cancer segregation analyses using 4390 families from UK and Australian population-based studies. Genet Epidemiol 34:42-50


Familial aggregation of prostate cancer is likely to be due to multiple susceptibility loci, perhaps acting in conjunction with shared lifestyle risk factors. Models that assume a single mode of inheritance may be unrealistic. We analyzed genetic models of susceptibility to prostate cancer using segregation analysis of occurrence in families ascertained through population-based series totaling 4390 incident cases. We investigated major gene models (dominant, recessive, general, X-linked), polygenic models, and mixed models of susceptibility using the pedigree analysis software MENDEL. The hypergeometric model was used to approximate polygenic inheritance. The best-fitting model for the familial aggregation of prostate cancer was the mixed recessive model. The frequency of the susceptibility allele in the population was estimated to be 0.15 (95% confidence interval (CI) 0.11-0.20), with a relative risk for homozygote carriers of 94 (95% CI 46-192), and a polygenic standard deviation of 2.01 (95% CI 1.72-2.34). These analyses suggest that one or more genes having a strong recessively inherited effect on risk, as well as a number of genes with variants having small multiplicative effects on risk, may account for the genetic susceptibility to prostate cancer. The recessive component would predict the observed higher familial risk for siblings of cases than for fathers, but this could also be due to other factors such as shared lifestyle by siblings, targeted screening effects, and/or non-additive effects of one or more genes.

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