Multivariate variance-components analysis in DTI

Agatha D. Lee, Natasha Leporé, Jan De Leeuw, Caroline C. Brun, Marina Barysheva, Katie L. McMahon, Greig I. De Zubicaray, Nicholas G. Martin, Margaret J. Wright, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations


Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

Original languageEnglish
Title of host publication2010 7th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2010 - Proceedings
Number of pages4
StatePublished - 2010
Externally publishedYes
Event7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Rotterdam, Netherlands
Duration: 14 Apr 201017 Apr 2010

Publication series

Name2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings


Conference7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010


  • DTI
  • Genetics
  • Multivariate statistics
  • Twin studies


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