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

Maria V. Fernández, John Budde, Jorge L. Del-Aguila, Laura Ibañez, Yuetiva Deming, Oscar Harari, Joanne Norton, John C. Morris, Alison M. Goate, NIA-LOAD family study group, NCRAD and Carlos Cruchaga. Frontiers in Neuroscience, Volume 12, Issue APR, 4 April 2018, Article number 209 Read More

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. © 2018 Fernández, Budde, Del-Aguila, Ibañez, Deming, Harari, Norton, Morris, Goate, NIA-LOAD family study group, NCRAD and Cruchaga.

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Posted on April 18, 2018
Posted in: HPAN, Neurodegeneration, Neurogenetics & Transcriptomics, Publications Authors: , , ,