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Ordered subset analysis of copy number variation association with age at onset of Alzheimer's disease

  • SUNY Buffalo
  • Baylor College of Medicine

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Genetic heterogeneity is a common problem for genome-wide association studies of complex human diseases. Ordered-subset analysis (OSA) reduces genetic heterogeneity and optimizes the use of phenotypic information, thus improving power under some disease models. We hypothesized that in a genetically heterogeneous disorder such as Alzheimer's disease (AD), utilizing OSA by age at onset (AAO) of AD may increase the power to detect relevant loci. Using this approach, 8 loci were detected, including the chr15: 30,44 region harboring CHRFAM7A. The association was replicated in the NIA-LOAD Familial Study dataset. CHRFAM7A is a dominant negative regulator of CHRNA7 function, the receptor that facilitates amyloid-β1-42 internalization through endocytosis and has been implicated in AD. OSA, using AAO as a quantitative trait, optimized power and detected replicable signals suggesting that AD is genetically heterogeneous between AAO subsets.

Original languageEnglish
Pages (from-to)1063-1071
Number of pages9
JournalJournal of Alzheimer's Disease
Volume41
Issue number4
DOIs
StatePublished - 2014

Keywords

  • Age at onset
  • Alzheimer's disease
  • copy number variation

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