A hierarchical Bayesian model to predict APOE4 genotype and the age of Alzheimer's disease onset

PLoS One. 2018 Jul 12;13(7):e0200263. doi: 10.1371/journal.pone.0200263. eCollection 2018.

Abstract

In this work we use a hierarchical Bayesian paradigm to introduce a theoretical framework to determine an individual's Apolipoprotein ε4 (APOE4) genotype, which heavily influences both the age of onset and probability of acquiring Alzheimer's disease (AD). This calculation is based solely on an individual's family history. This APOE4 genotype estimation is then combined with a number of known factors that influence AD onset to produce a function that estimates the onset of AD as a function of age. We disseminated our Alzheimer's predictive tool online at http://www.alzheimerspredictor.com.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age of Onset
  • Aged
  • Aged, 80 and over
  • Alzheimer Disease / genetics*
  • Apolipoprotein E4 / genetics*
  • Bayes Theorem
  • Female
  • Genotype
  • Humans
  • Male
  • Middle Aged

Substances

  • Apolipoprotein E4

Grants and funding

The authors received no specific funding for this work. FH is supported by a post doctoral fellowship from the BrightFocus Foundation (A2015344F).