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NCUEIR > College of Science > ma > Periodical Articles > Item 987654321/14460

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/14460

Title:	Extended Bayesian Model Averaging in Generalized Linear Mixed Models Applied to Schizophrenia Family Data
Authors:	Tsai, Miao-Yu;Hsiao, Chuhsing K.;Chen, Wei J.
Contributors:	統計資訊研究所
Keywords:	Bayesian model averaging;Genotype combination;Heritability;Interactions;Multiplex family
Date:	2011-01
Issue Date:	2012-10-25T09:04:04Z
Publisher:	Blackwell Publishing Ltd
Abstract:	The study of disease etiology and the search for susceptible genes of schizophrenia have attracted scientists’ attention for decades.Many findings however are inconsistent, possibly due to the higher order interactions involvingmulti-dimensional genetic and environmental factors or due to the commingling of different ethnic groups. Several studies applied generalized linear mixed models (GLMMs) with family data to identify the genetic contribution to, and environmental influence on, schizophrenia, and to clarify the existence and sources of familial aggregation. Based on an extended Bayesian model averaging (EBMA) procedure, here we estimate the gene-gene (GG) and gene-environment (GE) interactions, and heritability of schizophrenia via variance components of random-effects in GLMMs. Our proposal takes into account the uncertainty in covariates and in genetic model structures, where each competing model includes environmental and genetic covariates, and GE and GG interactions. Simulation studies are conducted to compare the performance of the EBMA approach, permutation test procedure and GEE method. We also illustrate this approach with data from singleton and multiplex schizophrenia families. The results indicate that EBMA is a flexible and stable tool in exploring true candidate genes, and GE and GG interactions, after adjusting for explanatory variables and correlation structures within family members.
Relation:	Annals of Human Genetics, 75(1): 62-77
Appears in Collections:	[ma] Periodical Articles

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