Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure

Nicholus M. Warstadt; Neda Jahanshad; Emily L. Dennis; Omid Kohannim; Katie L. McMahon; Greig I. De Zubicaray; Grant W. Montgomery; Anjali K. Henders; Nicholas G. Martin; John B. Whitfield; Margaret J. Wright; Paul M. Thompson

doi:10.1109/isbi.2014.6867881

Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure

Nicholus M. Warstadt, Neda Jahanshad, Emily L. Dennis, Omid Kohannim, Katie L. McMahon, Greig I. De Zubicaray, Grant W. Montgomery, Anjali K. Henders, Nicholas G. Martin, John B. Whitfield, Margaret J. Wright, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

Original language	English
Title of host publication	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	353-356
Number of pages	4
ISBN (Electronic)	9781467319591
DOIs	https://doi.org/10.1109/isbi.2014.6867881
State	Published - 29 Jul 2014
Externally published	Yes
Event	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China Duration: 29 Apr 2014 → 2 May 2014

Publication series

Name	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Conference

Conference	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Country/Territory	China
City	Beijing
Period	29/04/14 → 2/05/14

Keywords

Brain structure
DTI
Genetics
Multiple comparisons corrections
Multivariate analysis
Voxel-based

Access to Document

10.1109/isbi.2014.6867881

Cite this

Warstadt, N. M., Jahanshad, N., Dennis, E. L., Kohannim, O., McMahon, K. L., De Zubicaray, G. I., Montgomery, G. W., Henders, A. K., Martin, N. G., Whitfield, J. B., Wright, M. J., & Thompson, P. M. (2014). Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 353-356). Article 6867881 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/isbi.2014.6867881

Warstadt, Nicholus M. ; Jahanshad, Neda ; Dennis, Emily L. et al. / Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure. 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 353-356 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014).

@inproceedings{abf924ef2c784d3388cc016c823797d3,

title = "Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure",

abstract = "Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.",

keywords = "Brain structure, DTI, Genetics, Multiple comparisons corrections, Multivariate analysis, Voxel-based",

author = "Warstadt, {Nicholus M.} and Neda Jahanshad and Dennis, {Emily L.} and Omid Kohannim and McMahon, {Katie L.} and {De Zubicaray}, {Greig I.} and Montgomery, {Grant W.} and Henders, {Anjali K.} and Martin, {Nicholas G.} and Whitfield, {John B.} and Wright, {Margaret J.} and Thompson, {Paul M.}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 ; Conference date: 29-04-2014 Through 02-05-2014",

year = "2014",

month = jul,

day = "29",

doi = "10.1109/isbi.2014.6867881",

language = "English",

series = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "353--356",

booktitle = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014",

address = "United States",

}

Warstadt, NM, Jahanshad, N, Dennis, EL, Kohannim, O, McMahon, KL, De Zubicaray, GI, Montgomery, GW, Henders, AK, Martin, NG, Whitfield, JB, Wright, MJ & Thompson, PM 2014, Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure. in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014., 6867881, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Institute of Electrical and Electronics Engineers Inc., pp. 353-356, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, China, 29/04/14. https://doi.org/10.1109/isbi.2014.6867881

Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure. / Warstadt, Nicholus M.; Jahanshad, Neda; Dennis, Emily L. et al.
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 353-356 6867881 (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - McMahon, Katie L.

AU - De Zubicaray, Greig I.

AU - Montgomery, Grant W.

AU - Henders, Anjali K.

AU - Martin, Nicholas G.

AU - Whitfield, John B.

AU - Wright, Margaret J.

AU - Thompson, Paul M.

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AB - Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

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BT - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Warstadt NM, Jahanshad N, Dennis EL, Kohannim O, McMahon KL, De Zubicaray GI et al. Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 353-356. 6867881. (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). doi: 10.1109/isbi.2014.6867881

Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure

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