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Identifying Alzheimer's disease (AD) exclusive genes is challenging. A new Bayesian method reveals a small set of AD exclusive drug targets and a larger set of potentially repurposable AD pleiotropic genes.

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Area of Science:

  • Genetics
  • Neuroscience
  • Pharmacology

Background:

  • Distinguishing Alzheimer's disease (AD) exclusive genes from those associated with other conditions (AD pleiotropic) is difficult due to limited inferential methods.
  • AD exclusive genes offer potential as drug targets with fewer off-target effects.
  • AD pleiotropic genes may serve as repurposable drug candidates if their associations are protective for AD and other traits.

Purpose of the Study:

  • To introduce a novel Bayesian method for identifying AD exclusive and AD pleiotropic genes.
  • To estimate the posterior probabilities of genes being AD exclusive or pleiotropic based on shared polygenic architecture.
  • To identify potential drug targets and repurposable candidates for Alzheimer's disease.

Main Methods:

  • Developed a general Bayesian method utilizing summary-level GWAS data.
  • Calculated posterior probabilities (PP) for genes being AD exclusive or pleiotropic.
  • Analyzed 16,232 genes against 31 complex disease and cardiometabolic phenotypes.

Main Results:

  • Estimated 367 independently associated genes with AD; only 17 (4.6%) are AD exclusive and druggable (e.g., INPP5D, CD55).
  • Identified 140 (38.1%) druggable genes as AD pleiotropic (e.g., CLU, APOA2, APOE).
  • Example: APOA2 showed high PP for AD and Bipolar I/II, suggesting repurposing potential for AD prevention.

Conclusions:

  • The pool of viable AD exclusive druggable targets is likely small.
  • AD pleiotropic genes represent a significantly larger set of repurposable drug candidates.
  • The developed method effectively identifies safer and potentially efficacious drug targets for AD and related dementias.