Voxelwise genome-wide association study (vGWAS)

Jason L. Stein, Xue Hua, Suh Lee, April J. Ho, Alex D. Leow, Arthur W. Toga, Andrew Saykin, Li Shen, Tatiana Foroud, Nathan Pankratz, Matthew J. Huentelman, David W. Craig, Jill D. Gerber, April N. Allen, Jason J. Corneveaux, Bryan M. DeChairo, Steven G. Potkin, Michael W. Weiner, Paul M. Thompson

Research output: Contribution to journalArticle

165 Citations (Scopus)

Abstract

The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448,293 single nucleotide polymorphisms in each of 31,622 voxels of the entire brain across 740 elderly subjects (mean age ± s.d.: 75.52 ± 6.82 years; 438 male) including subjects with Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.

Original languageEnglish
Pages (from-to)1160-1174
Number of pages15
JournalNeuroImage
Volume53
Issue number3
DOIs
StatePublished - Nov 2010

Fingerprint

Genome-Wide Association Study
Brain
Neuroimaging
Alzheimer Disease
Genome
Genes
Individuality
Single Nucleotide Polymorphism
Healthy Volunteers
Genotype

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology

Cite this

Stein, J. L., Hua, X., Lee, S., Ho, A. J., Leow, A. D., Toga, A. W., ... Thompson, P. M. (2010). Voxelwise genome-wide association study (vGWAS). NeuroImage, 53(3), 1160-1174. https://doi.org/10.1016/j.neuroimage.2010.02.032

Voxelwise genome-wide association study (vGWAS). / Stein, Jason L.; Hua, Xue; Lee, Suh; Ho, April J.; Leow, Alex D.; Toga, Arthur W.; Saykin, Andrew; Shen, Li; Foroud, Tatiana; Pankratz, Nathan; Huentelman, Matthew J.; Craig, David W.; Gerber, Jill D.; Allen, April N.; Corneveaux, Jason J.; DeChairo, Bryan M.; Potkin, Steven G.; Weiner, Michael W.; Thompson, Paul M.

In: NeuroImage, Vol. 53, No. 3, 11.2010, p. 1160-1174.

Research output: Contribution to journalArticle

Stein, JL, Hua, X, Lee, S, Ho, AJ, Leow, AD, Toga, AW, Saykin, A, Shen, L, Foroud, T, Pankratz, N, Huentelman, MJ, Craig, DW, Gerber, JD, Allen, AN, Corneveaux, JJ, DeChairo, BM, Potkin, SG, Weiner, MW & Thompson, PM 2010, 'Voxelwise genome-wide association study (vGWAS)', NeuroImage, vol. 53, no. 3, pp. 1160-1174. https://doi.org/10.1016/j.neuroimage.2010.02.032
Stein JL, Hua X, Lee S, Ho AJ, Leow AD, Toga AW et al. Voxelwise genome-wide association study (vGWAS). NeuroImage. 2010 Nov;53(3):1160-1174. https://doi.org/10.1016/j.neuroimage.2010.02.032
Stein, Jason L. ; Hua, Xue ; Lee, Suh ; Ho, April J. ; Leow, Alex D. ; Toga, Arthur W. ; Saykin, Andrew ; Shen, Li ; Foroud, Tatiana ; Pankratz, Nathan ; Huentelman, Matthew J. ; Craig, David W. ; Gerber, Jill D. ; Allen, April N. ; Corneveaux, Jason J. ; DeChairo, Bryan M. ; Potkin, Steven G. ; Weiner, Michael W. ; Thompson, Paul M. / Voxelwise genome-wide association study (vGWAS). In: NeuroImage. 2010 ; Vol. 53, No. 3. pp. 1160-1174.
@article{a803dfc518ad49e39165ad57bce998a8,
title = "Voxelwise genome-wide association study (vGWAS)",
abstract = "The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448,293 single nucleotide polymorphisms in each of 31,622 voxels of the entire brain across 740 elderly subjects (mean age ± s.d.: 75.52 ± 6.82 years; 438 male) including subjects with Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.",
author = "Stein, {Jason L.} and Xue Hua and Suh Lee and Ho, {April J.} and Leow, {Alex D.} and Toga, {Arthur W.} and Andrew Saykin and Li Shen and Tatiana Foroud and Nathan Pankratz and Huentelman, {Matthew J.} and Craig, {David W.} and Gerber, {Jill D.} and Allen, {April N.} and Corneveaux, {Jason J.} and DeChairo, {Bryan M.} and Potkin, {Steven G.} and Weiner, {Michael W.} and Thompson, {Paul M.}",
year = "2010",
month = "11",
doi = "10.1016/j.neuroimage.2010.02.032",
language = "English",
volume = "53",
pages = "1160--1174",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press Inc.",
number = "3",

}

TY - JOUR

T1 - Voxelwise genome-wide association study (vGWAS)

AU - Stein, Jason L.

AU - Hua, Xue

AU - Lee, Suh

AU - Ho, April J.

AU - Leow, Alex D.

AU - Toga, Arthur W.

AU - Saykin, Andrew

AU - Shen, Li

AU - Foroud, Tatiana

AU - Pankratz, Nathan

AU - Huentelman, Matthew J.

AU - Craig, David W.

AU - Gerber, Jill D.

AU - Allen, April N.

AU - Corneveaux, Jason J.

AU - DeChairo, Bryan M.

AU - Potkin, Steven G.

AU - Weiner, Michael W.

AU - Thompson, Paul M.

PY - 2010/11

Y1 - 2010/11

N2 - The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448,293 single nucleotide polymorphisms in each of 31,622 voxels of the entire brain across 740 elderly subjects (mean age ± s.d.: 75.52 ± 6.82 years; 438 male) including subjects with Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.

AB - The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448,293 single nucleotide polymorphisms in each of 31,622 voxels of the entire brain across 740 elderly subjects (mean age ± s.d.: 75.52 ± 6.82 years; 438 male) including subjects with Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.

UR - http://www.scopus.com/inward/record.url?scp=77954918835&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77954918835&partnerID=8YFLogxK

U2 - 10.1016/j.neuroimage.2010.02.032

DO - 10.1016/j.neuroimage.2010.02.032

M3 - Article

C2 - 20171287

AN - SCOPUS:77954918835

VL - 53

SP - 1160

EP - 1174

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

IS - 3

ER -