Population-Calibrated Gene Characterization:
Cancer Penetrance Among BRCA1/2 Mutation Carriers
Phenotypic characterization of rare disease genes poses a significant
challenge, but the need to do so is clear: clinical management of such
patients depends crucially on an accurate characterization of the
genetically predisposed disease, including its penetrance, natural
history and response to treatment. We propose a formal yet practical
method for controlling for ascertainment bias when estimating disease
penetrance using data on high risk individuals. This approach avoids
the need to model the ascertainment criteria met by each study
participant. Instead, the likelihood is adjusted by a factor that
involves the distributions of variables instrumental in the
ascertainment process in the general population and in the high risk
data. As an example, we derive ascertainment--corrected estimates of
cancer penetrance for carriers of the breast cancer susceptibility
genes BRCA1 and BRCA2. The Bayesian analysis we employ incorporates a
modified segregation model and prior data on penetrance derived from
the literature. Markov chain Monte Carlo methods are used for
inference.
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