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

Wensheng Zhu, Ying Yuan, Jingwen Zhang, Fan Zhou, Rebecca C. Knickmeyer, Hongtu Zhu

Research output: Contribution to journalArticle

  • 1 Citations

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.

LanguageEnglish (US)
Pages983-1002
Number of pages20
JournalNeuroImage
Volume146
DOIs
StatePublished - Feb 1 2017

Fingerprint

Genome-Wide Association Study
Neuroimaging
Alzheimer Disease
Phenotype
Molecular Epidemiology
Linear Models
Genotype

Keywords

  • Alzheimer's Disease Neuroimaging Initiative
  • Case-control
  • Genome-wide association analysis
  • Imaging genetics
  • Secondary trait

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

Cite this

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study. / Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C.; Zhu, Hongtu.

In: NeuroImage, Vol. 146, 01.02.2017, p. 983-1002.

Research output: Contribution to journalArticle

Zhu, Wensheng ; Yuan, Ying ; Zhang, Jingwen ; Zhou, Fan ; Knickmeyer, Rebecca C. ; Zhu, Hongtu. / Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study. In: NeuroImage. 2017 ; Vol. 146. pp. 983-1002
@article{e5f5187f08a347e6b5521f1ffcd23a23,
title = "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.",
keywords = "Alzheimer's Disease Neuroimaging Initiative, Case-control, Genome-wide association analysis, Imaging genetics, Secondary trait",
author = "Wensheng Zhu and Ying Yuan and Jingwen Zhang and Fan Zhou and Knickmeyer, {Rebecca C.} and Hongtu Zhu",
year = "2017",
month = "2",
day = "1",
doi = "10.1016/j.neuroimage.2016.09.055",
language = "English (US)",
volume = "146",
pages = "983--1002",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press Inc.",

}

TY - JOUR

T1 - Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study

AU - Zhu,Wensheng

AU - Yuan,Ying

AU - Zhang,Jingwen

AU - Zhou,Fan

AU - Knickmeyer,Rebecca C.

AU - Zhu,Hongtu

PY - 2017/2/1

Y1 - 2017/2/1

N2 - 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.

AB - 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.

KW - Alzheimer's Disease Neuroimaging Initiative

KW - Case-control

KW - Genome-wide association analysis

KW - Imaging genetics

KW - Secondary trait

UR - http://www.scopus.com/inward/record.url?scp=85008699019&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85008699019&partnerID=8YFLogxK

U2 - 10.1016/j.neuroimage.2016.09.055

DO - 10.1016/j.neuroimage.2016.09.055

M3 - Article

VL - 146

SP - 983

EP - 1002

JO - NeuroImage

T2 - NeuroImage

JF - NeuroImage

SN - 1053-8119

ER -