title: PEL: an unbiased method for estimating age-dependent genetic disease risk from pedigree data unselected for family history.
abstract: Providing valid risk estimates of a genetic disease with variable age of onset is a major challenge for prevention strategies. When data are obtained from pedigrees ascertained through affected individuals, an adjustment for ascertainment bias is necessary. This article focuses on ascertainment through at least one affected and presents an estimation method based on maximum likelihood, called the Proband's phenotype exclusion likelihood or PEL for estimating age-dependent penetrance using disease status and genotypic information of family members in pedigrees unselected for family history. We studied the properties of the PEL and compared with another method, the prospective likelihood, in terms of bias and efficiency in risk estimate. For that purpose, family samples were simulated under various disease risk models and under various ascertainment patterns. We showed that, whatever the genetic model and the ascertainment scheme, the PEL provided unbiased estimates, whereas the prospective likelihood exhibited some bias in a number of situations. As an illustration, we estimated the disease risk for transthyretin amyloid neuropathy from a French sample and a Portuguese sample and for BRCA1/2 associated breast cancer from a sample ascertained on early-onset breast cancer cases.
authors.affiliation: University Paris-Sud, Villejuif, France. flora.alarcon@inserm.fr
authors.forename: F
authors.initials: F
authors.lastname: Alarcon
authors.forename: C
authors.initials: C
authors.lastname: Bourgain
authors.forename: M
authors.initials: M
authors.lastname: Gauthier-Villars
authors.forename: V
authors.initials: V
authors.lastname: Planté-Bordeneuve
authors.forename: D
authors.initials: D
authors.lastname: Stoppa-Lyonnet
authors.forename: C
authors.initials: C
authors.lastname: Bonaïti-Pellié
mesh_terms: D000367:Age Factors; D017772:Amyloid Neuropathies / Q000235:genetics; D015982:Bias; D001943:Breast Neoplasms / Q000235:genetics; D005602:France; D019398:Genes, BRCA1; D024522:Genes, BRCA2; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D010375:Pedigree; D010641:Phenotype; D011174:Portugal; D011228:Prealbumin / Q000235:genetics; D012306:Risk
chemical_list: D011228:Prealbumin