Family-based genome scan for age at onset of late-onset Alzheimer's disease in whole exome sequencing data

Mohamad Saad, Z. Brkanac, E. M. Wijsman

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Alzheimer's disease (AD) is a common and complex neurodegenerative disease. Age at onset (AAO) of AD is an important component phenotype with a genetic basis, and identification of genes in which variation affects AAO would contribute to identification of factors that affect timing of onset. Increase in AAO through prevention or therapeutic measures would have enormous benefits by delaying AD and its associated morbidities. In this paper, we performed a family-based genome-wide association study for AAO of late-onset AD in whole exome sequence data generated in multigenerational families with multiple AD cases. We conducted single marker and gene-based burden tests for common and rare variants, respectively. We combined association analyses with variance component linkage analysis, and with reference to prior studies, in order to enhance evidence of the identified genes. For variants and genes implicated by the association study, we performed a gene-set enrichment analysis to identify potential novel pathways associated with AAO of AD. We found statistically significant association with AAO for three genes (WRN, NTN4 and LAMC3) with common associated variants, and for four genes (SLC8A3, SLC19A3, MADD and LRRK2) with multiple rare-associated variants that have a plausible biological function related to AD. The genes we have identified are in pathways that are strong candidates for involvement in the development of AD pathology and may lead to a better understanding of AD pathogenesis.

Original languageEnglish
Pages (from-to)607-617
Number of pages11
JournalGenes, Brain and Behavior
Volume14
Issue number8
DOIs
Publication statusPublished - 1 Nov 2015
Externally publishedYes

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Keywords

  • DNA sequencing
  • Family-based association
  • Linear mixed model
  • Pedigree

ASJC Scopus subject areas

  • Genetics
  • Neurology
  • Behavioral Neuroscience

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