A frailty-model-based approach to estimating the age-dependent penetrance function of candidate genes using population-based case-control study designs: an application to data on the BRCA1 gene.
The population-based case-control study design is perhaps one of, if not the most, commonly used designs for investigating the genetic and environmental contributions to disease risk in epidemiological studies. Ages at onset and disease status of family members are routinely and systematically collected from the participants in this design. Considering age at onset in relatives as an outcome, this article is focused on using the family history information to obtain the hazard function, i.e., age-dependent penetrance function, of candidate genes from case-control studies. A frailty-model-based approach is proposed to accommodate the shared risk among family members that is not accounted for by observed risk factors. This approach is further extended to accommodate missing genotypes in family members and a two-phase case-control sampling design. Simulation results show that the proposed method performs well in realistic settings. Finally, a population-based two-phase case-control breast cancer study of the BRCA1 gene is used to illustrate the method.
Chen
Lu
L
Department of Preventive Medicine, University of Southern California, Los Angeles, California 90089, USA.
Hsu
Li
L
Malone
Kathleen
K
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001699:Biometry / Q000379:methods*; D001943:Breast Neoplasms / Q000235:genetics; D016022:Case-Control Studies; D030541:Databases, Genetic; D005260:Female; D019398:Genes, BRCA1; D005828:Genetics, Population / Q000706:statistics & numerical data*; D006801:Humans; D016013:Likelihood Functions; D008875:Middle Aged; D015233:Models, Statistical; D009154:Mutation; D019683:Penetrance; D016016:Proportional Hazards Models; D012307:Risk Factors; D018709:Statistics, Nonparametric; D016019:Survival Analysis; D055815:Young Adult