Non-parametric estimation of survival in age-dependent genetic disease and application to the transthyretin-related hereditary amyloidosis

In genetic diseases with variable age of onset, survival function estimation for the mutation carriers as well as estimation of the modifying factors effects are essential to provide individual risk assessment, both for mutation carriers management and prevention strategies. In practice, this surviv...

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Bibliographic Details
Published in:PloS one 2018-09, Vol.13 (9), p.e0203860-e0203860
Main Authors: Alarcon, Flora, Planté-Bordeneuve, Violaine, Olsson, Malin, Nuel, Grégory
Format: Article
Language:English
Subjects:
Age
Age determination
Algorithms
Amyloidosis
Bayesian analysis
Bioinformatics
Biology and Life Sciences
Carriers
Colorectal cancer
Computer and Information Sciences
Computer simulation
Data processing
Disease
Engineering and Technology
Estimates
Gene mutation
Genetic aspects
Genetics
Genotypes
Life Sciences
Mathematics
Medical diagnosis
Medicine and Health Sciences
Methods
Mutation
Nonparametric statistics
Parameter estimation
People and places
Physical Sciences
Research and Analysis Methods
Risk assessment
Risk factors
Santé publique et épidémiologie
Statistical analysis
Statistical methods
Statistical models
Statistics
Survival
Survival analysis
Transthyretin
Transthyretin amyloidosis
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Summary:In genetic diseases with variable age of onset, survival function estimation for the mutation carriers as well as estimation of the modifying factors effects are essential to provide individual risk assessment, both for mutation carriers management and prevention strategies. In practice, this survival function is classically estimated from pedigrees data where most genotypes are unobserved. In this article, we present a unifying Expectation-Maximization (EM) framework combining probabilistic computations in Bayesian networks with standard statistical survival procedures in order to provide mutation carrier survival estimates. The proposed approach allows to obtain previously published parametric estimates (e.g. Weibull survival) as particular cases as well as more general Kaplan-Meier non-parametric estimates, which is the main contribution. Note that covariates can also be taken into account using a proportional hazard model. The whole methodology is both validated on simulated data and applied to family samples with transthyretin-related hereditary amyloidosis (a rare autosomal dominant disease with highly variable age of onset), showing very promising results.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0203860