Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease

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ID: 29935
2018
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Ranked #61 of 78 articles by views in Frontiers in neuroscience

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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.
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fernandez2018evaluationfrontiers Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Fernández, Maria V.;Fernández, Maria V.;Budde, John;Budde, John;Del-Aguila, Jorge L.;Del-Aguila, Jorge L.;Ibañez, Laura;Ibañez, Laura;Deming, Yuetiva;Deming, Yuetiva;Harari, Oscar;Harari, Oscar;Norton, Joanne;Norton, Joanne;Morris, John C.;Morris, John C.;Goate, Alison M.;group, NIA-LOAD family study;NCRAD, ;Cruchaga, Carlos;Cruchaga, Carlos;
Journal Frontiers in neuroscience
Year 2018
DOI
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URL
http://journal.frontiersin.org/article/10.3389/fnins.2018.00209/full
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