Bivariate genome-wide association study of genetically correlated neuroimaging phenotypes from DTI and MRI through a seemingly unrelated regression model

Neda Jahanshad, Priya Bhatt, Derrek P. Hibar, Julio E. Villalon, Talia M. Nir, Arthur W. Toga, Clifford R Jr. Jack, Matthew A Bernstein, Michael W. Weiner, Katie L. McMahon, Greig I. De Zubicaray, Nicholas G. Martin, Margaret J. Wright, Paul M. Thompson

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

3 Citations (Scopus)

Abstract

Large multisite efforts (e.g., the ENIGMA Consortium), have shown that neuroimaging traits including tract integrity (from DTI fractional anisotropy, FA) and subcortical volumes (from T1-weighted scans) are highly heritable and promising phenotypes for discovering genetic variants associated with brain structure. However, genetic correlations (rg) among measures from these different modalities for mapping the human genome to the brain remain unknown. Discovering these correlations can help map genetic and neuroanatomical pathways implicated in development and inherited risk for disease. We use structural equation models and a twin design to find rg between pairs of phenotypes extracted from DTI and MRI scans. When controlling for intracranial volume, the caudate as well as related measures from the limbic system - hippocampal volume - showed high rg with the cingulum FA. Using an unrelated sample and a Seemingly Unrelated Regression model for bivariate analysis of this connection, we show that a multivariate GWAS approach may be more promising for genetic discovery than a univariate approach applied to each trait separately.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages189-201
Number of pages13
Volume8159 LNCS
DOIs
StatePublished - 2013
Event3rd International Workshop on Multimodal Brain Image Analysis, MBIA 2013, Held in Conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan
Duration: Sep 22 2013Sep 22 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8159 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd International Workshop on Multimodal Brain Image Analysis, MBIA 2013, Held in Conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
CountryJapan
CityNagoya
Period9/22/139/22/13

Fingerprint

Seemingly Unrelated Regression
Neuroimaging
Phenotype
Magnetic resonance imaging
Brain
Regression Model
Genome
Anisotropy
Genes
Fractional
Structural Equation Model
Integrity
Modality
Univariate
Pathway
Unknown
Magnetic Resonance Imaging

Keywords

  • bivariate analysis
  • brain connectivity
  • genetic correlation
  • GWAS
  • Neuroimaging genetics

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Jahanshad, N., Bhatt, P., Hibar, D. P., Villalon, J. E., Nir, T. M., Toga, A. W., ... Thompson, P. M. (2013). Bivariate genome-wide association study of genetically correlated neuroimaging phenotypes from DTI and MRI through a seemingly unrelated regression model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8159 LNCS, pp. 189-201). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8159 LNCS). https://doi.org/10.1007/978-3-319-02126-3_19

Bivariate genome-wide association study of genetically correlated neuroimaging phenotypes from DTI and MRI through a seemingly unrelated regression model. / Jahanshad, Neda; Bhatt, Priya; Hibar, Derrek P.; Villalon, Julio E.; Nir, Talia M.; Toga, Arthur W.; Jack, Clifford R Jr.; Bernstein, Matthew A; Weiner, Michael W.; McMahon, Katie L.; De Zubicaray, Greig I.; Martin, Nicholas G.; Wright, Margaret J.; Thompson, Paul M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8159 LNCS 2013. p. 189-201 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8159 LNCS).

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

Jahanshad, N, Bhatt, P, Hibar, DP, Villalon, JE, Nir, TM, Toga, AW, Jack, CRJ, Bernstein, MA, Weiner, MW, McMahon, KL, De Zubicaray, GI, Martin, NG, Wright, MJ & Thompson, PM 2013, Bivariate genome-wide association study of genetically correlated neuroimaging phenotypes from DTI and MRI through a seemingly unrelated regression model. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8159 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8159 LNCS, pp. 189-201, 3rd International Workshop on Multimodal Brain Image Analysis, MBIA 2013, Held in Conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, Nagoya, Japan, 9/22/13. https://doi.org/10.1007/978-3-319-02126-3_19
Jahanshad N, Bhatt P, Hibar DP, Villalon JE, Nir TM, Toga AW et al. Bivariate genome-wide association study of genetically correlated neuroimaging phenotypes from DTI and MRI through a seemingly unrelated regression model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8159 LNCS. 2013. p. 189-201. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-02126-3_19
Jahanshad, Neda ; Bhatt, Priya ; Hibar, Derrek P. ; Villalon, Julio E. ; Nir, Talia M. ; Toga, Arthur W. ; Jack, Clifford R Jr. ; Bernstein, Matthew A ; Weiner, Michael W. ; McMahon, Katie L. ; De Zubicaray, Greig I. ; Martin, Nicholas G. ; Wright, Margaret J. ; Thompson, Paul M. / Bivariate genome-wide association study of genetically correlated neuroimaging phenotypes from DTI and MRI through a seemingly unrelated regression model. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8159 LNCS 2013. pp. 189-201 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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