Principal components regression: Multivariate, gene-based tests in imaging genomics

Derrek P. Hibar, Jason L. Stein, Omid Kohannim, Neda Jahanshad, Clifford R Jr. Jack, Michael W. Weiner, Arthur W. Toga, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In imaging genomics, there have been rapid advances in genome-wide, image-wide searches for genes that influence brain structure. Most efforts focus on univariate tests that treat each genetic variation independently, ignoring the joint effects of multiple variants. Instead, we present a gene-based method to detect the joint effect of multiple single nucleotide polymorphisms (SNPs) in 18,044 genes across 31,662 voxels of the whole brain in a tensor-based morphometry analysis of baseline MRI scans from 731 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our gene-based multivariate statistics use principal components regression to test the combined effect of multiple genetic variants on an image, using a single test statistic. In some situations, which we describe, this can boost power by encoding population variations within each gene, reducing the effective number of statistical tests, and reducing the effect dimension of the search space. Multivariate gene-based methods may discover gene effects undetectable with standard, univariate methods, accelerating ongoing imaging genomics efforts worldwide.

Original languageEnglish (US)
Title of host publicationProceedings - International Symposium on Biomedical Imaging
Pages289-293
Number of pages5
DOIs
StatePublished - 2011
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: Mar 30 2011Apr 2 2011

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
CountryUnited States
CityChicago, IL
Period3/30/114/2/11

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Keywords

  • GWAS
  • imaging genomics
  • multivariate
  • principal components regression
  • voxelwise

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Hibar, D. P., Stein, J. L., Kohannim, O., Jahanshad, N., Jack, C. R. J., Weiner, M. W., Toga, A. W., & Thompson, P. M. (2011). Principal components regression: Multivariate, gene-based tests in imaging genomics. In Proceedings - International Symposium on Biomedical Imaging (pp. 289-293). [5872408] https://doi.org/10.1109/ISBI.2011.5872408