English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

When considering a genetic disease with variable age at onset (ex: diabetes ,familial amyloid neuropathy, cancers, etc.), computing the individual risk ofthe disease based on family history (FH) is of critical interest both forclinicians and patients. Such a risk is very challenging to compute because: 1)the genotype X of the individual of interest is in general unknown; 2) theposterior distribution P(X|FH, T > t) changes with t (T is the age at diseaseonset for the targeted individual); 3) the competing risk of death is notnegligible. In this work, we present a modeling of this problem using aBayesian network mixed with (right-censored) survival outcomes where hazardrates only depend on the genotype of each individual. We explain how beliefpropagation can be used to obtain posterior distribution of genotypes given theFH, and how to obtain a time-dependent posterior hazard rate for any individualin the pedigree. Finally, we use this posterior hazard rate to computeindividual risk, with or without the competing risk of death. Our method isillustrated using the Claus-Easton model for breast cancer (BC). This modelassumes an autosomal dominant genetic risk factor such as non-carriers(genotype 00) have a BC hazard rate $\lambda$ 0 (t) while carriers (genotypes01, 10 and 11) have a (much greater) hazard rate $\lambda$ 1 (t). Both hazardrates are assumed to be piecewise constant with known values (cuts at 20, 30,... , 80 years). The competing risk of death is derived from the national Frenchregistry.

Computing Individual Risks based on Family History in Genetic Disease in the Presence of Competing Risks