Evaluation of gene-based family-based methods to detect novel genes associated with familial late onset Alzheimer disease

NIA-LOAD family study group, NCRAD

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L) as candidate genes for familial LOAD.

Original languageEnglish
Article number209
JournalFrontiers in Neuroscience
Volume12
Issue numberAPR
DOIs
StatePublished - Apr 4 2018

Keywords

  • Alzheimer's disease
  • Clustering
  • Family-based
  • Gene-based
  • Rare variants
  • Transmission disequilibrium
  • Variance-component
  • Whole exome sequencing

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