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Bayesian Modeling for Genetic Anticipation in Presence of Mutational Heterogeneity: A Case Study in Lynch Syndrome

Boonstra, Philip S. ; Mukherjee, Bhramar ; Taylor, Jeremy M. G. ; Nilbert, Mef ; Moreno, Victor ; Gruber, Stephen B.

Biometrics, 2011-12, Vol.67 (4), p.1627-1637 [Periódico revisado por pares]

Malden, USA: Blackwell Publishing Inc

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Título:
Bayesian Modeling for Genetic Anticipation in Presence of Mutational Heterogeneity: A Case Study in Lynch Syndrome
Autor: Boonstra, Philip S. ; Mukherjee, Bhramar ; Taylor, Jeremy M. G. ; Nilbert, Mef ; Moreno, Victor ; Gruber, Stephen B.
Assuntos: Adolescent ; Adult ; Age of Onset ; Aged ; Anticipation, Genetic - genetics ; Bayes Theorem ; Bayesian analysis ; BIOMETRIC PRACTICE ; Biometrics ; biometry ; Birth-death process ; Brier score ; Case studies ; Censorship ; Child ; Child, Preschool ; Colorectal cancer ; colorectal neoplasms ; Colorectal Neoplasms, Hereditary Nonpolyposis - epidemiology ; Colorectal Neoplasms, Hereditary Nonpolyposis - genetics ; Computer Simulation ; Conditional predictive ordinate ; counseling ; Càncer colorectal ; Denmark - epidemiology ; Density estimation ; Deviance information criterion ; diagnostic techniques ; Dirichlet process ; disease detection ; Epidemiology ; Female ; genes ; genetic disorders ; Genetic mutation ; Genetics ; Genètica ; Hereditary nonpolyposis colorectal cancer ; Hereditary nonpolyposis colorectal neoplasms ; Human genetics ; Humans ; Infant ; Infant, Newborn ; Lynch syndrome II ; Male ; Mathematical models ; Medical genetics ; Middle Aged ; Modeling ; Models, Genetic ; Models, Statistical ; mutation ; Mutation - genetics ; phenotype ; Polymorphism, Single Nucleotide - genetics ; Prediction of random effects ; Prevalence ; Relative survival analysis ; Risk Assessment ; Risk Factors ; screening ; Young Adult
É parte de: Biometrics, 2011-12, Vol.67 (4), p.1627-1637
Notas: http://dx.doi.org/10.1111/j.1541-0420.2011.01607.x
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Descrição: Genetic anticipation, described by earlier age of onset (AOO) and more aggressive symptoms in successive generations, is a phenomenon noted in certain hereditary diseases. Its extent may vary between families and/or between mutation subtypes known to be associated with the disease phenotype. In this article, we posit a Bayesian approach to infer genetic anticipation under flexible random effects models for censored data that capture the effect of successive generations on AOO. Primary interest lies in the random effects. Misspecifying the distribution of random effects may result in incorrect inferential conclusions. We compare the fit of four‐candidate random effects distributions via Bayesian model fit diagnostics. A related statistical issue here is isolating the confounding effect of changes in secular trends, screening, and medical practices that may affect time to disease detection across birth cohorts. Using historic cancer registry data, we borrow from relative survival analysis methods to adjust for changes in age‐specific incidence across birth cohorts. Our motivating case study comes from a Danish cancer register of 124 families with mutations in mismatch repair (MMR) genes known to cause hereditary nonpolyposis colorectal cancer, also called Lynch syndrome (LS). We find evidence for a decrease in AOO between generations in this article. Our model predicts family‐level anticipation effects that are potentially useful in genetic counseling clinics for high‐risk families.
Editor: Malden, USA: Blackwell Publishing Inc
Idioma: Inglês;Francês

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Bayesian Modeling for Genetic Anticipation in Presence of Mutational Heterogeneity: A Case Study in Lynch Syndrome

Boonstra, Philip S. ; Mukherjee, Bhramar ; Taylor, Jeremy M. G. ; Nilbert, Mef ; Moreno, Victor ; Gruber, Stephen B.

Malden, USA: Blackwell Publishing Inc

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