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

Authors :
Fernández, Maria V.
Budde, John
Del-Aguila, Jorge L.
Ibañez, Laura
Deming, Yuetiva
Harari, Oscar
Norton, Joanne
Morris, John C.
Goate, Alison M.
Cruchaga, Carlos
Source :
Frontiers in Neuroscience; 4/4/2018, p1-N.PAG, 19p
Publication Year :
2018

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16624548
Database :
Complementary Index
Journal :
Frontiers in Neuroscience
Publication Type :
Academic Journal
Accession number :
128910273
Full Text :
https://doi.org/10.3389/fnins.2018.00209