title: Prostate cancer segregation analyses using 4390 families from UK and Australian population-based studies.
abstract: 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.
authors.affiliation: Cancer Research UK Genetic Epidemiology Unit, Strangeways Laboratory, University of Cambridge, Cambridge, UK.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: MacInnis
authors.forename: Antonis C
authors.initials: AC
authors.lastname: Antoniou
authors.forename: Rosalind A
authors.initials: RA
authors.lastname: Eeles
authors.forename: Gianluca
authors.initials: G
authors.lastname: Severi
authors.forename: Michelle
authors.initials: M
authors.lastname: Guy
authors.forename: Lesley
authors.initials: L
authors.lastname: McGuffog
authors.forename: Amanda L
authors.initials: AL
authors.lastname: Hall
authors.forename: Lynne T
authors.initials: LT
authors.lastname: O'Brien
authors.forename: Rosemary A
authors.initials: RA
authors.lastname: Wilkinson
authors.forename: David P
authors.initials: DP
authors.lastname: Dearnaley
authors.forename: Audrey T
authors.initials: AT
authors.lastname: Ardern-Jones
authors.forename: Alan
authors.initials: A
authors.lastname: Horwich
authors.forename: Vincent S
authors.initials: VS
authors.lastname: Khoo
authors.forename: Christopher C
authors.initials: CC
authors.lastname: Parker
authors.forename: Robert A
authors.initials: RA
authors.lastname: Huddart
authors.forename: Margaret R
authors.initials: MR
authors.lastname: McCredie
authors.forename: Charmaine
authors.initials: C
authors.lastname: Smith
authors.forename: Melissa C
authors.initials: MC
authors.lastname: Southey
authors.forename: Margaret P
authors.initials: MP
authors.lastname: Staples
authors.forename: Dallas R
authors.initials: DR
authors.lastname: English
authors.forename: John L
authors.initials: JL
authors.lastname: Hopper
authors.forename: Graham G
authors.initials: GG
authors.lastname: Giles
authors.forename: Douglas F
authors.initials: DF
authors.lastname: Easton
mesh_terms: D000328:Adult; D032721:Adult Children; D000368:Aged; D000369:Aged, 80 and over; D001315:Australia; D016022:Case-Control Studies; D005220:Fathers; D005808:Genes, Recessive; D020022:Genetic Predisposition to Disease; D005828:Genetics, Population; D006801:Humans; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D011471:Prostatic Neoplasms / Q000235:genetics*; D012307:Risk Factors; D035781:Siblings; D006113:United Kingdom