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Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

Abstract：

:The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Zhu W,Yuan Y,Zhang J,Zhou F,Knickmeyer RC,Zhu H,Alzheimer's Disease Neuroimaging Initiative.

doi

10.1016/j.neuroimage.2016.09.055

subject

Has Abstract

pub_date

2017-02-01 00:00:00

pages

983-1002

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(16)30530-4

journal_volume

146

pub_type

杂志文章

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