Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data.

Peter Kochunov, Neda Jahanshad, Daniel Marcus, Anderson Winkler, Emma Sprooten, Thomas E. Nichols, Susan N. Wright, L. Elliot Hong, Binish Patel, Timothy Behrens, Saad Jbabdi, Jesper Andersson, Christophe Lenglet, Essa Yacoub, Steen Moeller, Eddie Auerbach, Kamil Ugurbil, Stamatios N. Sotiropoulos, Rachel M. Brouwer, Bennett Landman, Hervé Lemaitre, Anouk den Braber, Marcel P. Zwiers, Stuart Ritchie, Kimm van Hulzen, Laura Almasy, Joanne Curran, Greig I. deZubicaray, Ravi Duggirala, Peter Fox, Nicholas G. Martin, Katie L. McMahon, Braxton Mitchell, Rene L. Olvera, Charles Peterson, John Starr, Jessika Sussmann, Joanna Wardlaw, Margie Wright, Dorret I. Boomsma, Rene Kahn, Eco J.C. de Geus, Douglas E. Williamson, Ahmad Hariri, Dennis van 't Ent, Mark E. Bastin, Andrew McIntosh, Ian J. Deary, Hilleke E. Hulshoff pol, John Blangero, Paul M. Thompson, David C. Glahn, David C. Van Essen
NeuroImage. 2015-05-01; 111: 300-311
DOI: 10.1016/j.neuroimage.2015.02.050

PubMed
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1. Neuroimage. 2015 May 1;111:300-11. doi: 10.1016/j.neuroimage.2015.02.050. Epub
2015 Mar 4.

Heritability of fractional anisotropy in human white matter: a comparison of
Human Connectome Project and ENIGMA-DTI data.

Kochunov P(1), Jahanshad N(2), Marcus D(3), Winkler A(4), Sprooten E(5), Nichols
TE(6), Wright SN(7), Hong LE(7), Patel B(7), Behrens T(4), Jbabdi S(4), Andersson
J(4), Lenglet C(8), Yacoub E(8), Moeller S(8), Auerbach E(8), Ugurbil K(8),
Sotiropoulos SN(4), Brouwer RM(9), Landman B(10), Lemaitre H(11), den Braber
A(12), Zwiers MP(13), Ritchie S(14), van Hulzen K(13), Almasy L(15), Curran
J(15), deZubicaray GI(16), Duggirala R(15), Fox P(17), Martin NG(18), McMahon
KL(16), Mitchell B(19), Olvera RL(17), Peterson C(15), Starr J(14), Sussmann
J(14), Wardlaw J(14), Wright M(18), Boomsma DI(12), Kahn R(9), de Geus EJ(12),
Williamson DE(17), Hariri A(20), van ‘t Ent D(12), Bastin ME(14), McIntosh A(14),
Deary IJ(14), Hulshoff Pol HE(9), Blangero J(15), Thompson PM(2), Glahn DC(5),
Van Essen DC(21).

Author information:
(1)Maryland Psychiatric Research Center, University of MD School of Medicine,
Baltimore USA. Electronic address: .
(2)Imaging Genetics Center, Institute for Neuroimaging and Informatics,
Department of Neurology Keck School of Medicine, University of Southern CA,
Marina del Rey, USA.
(3)Department of Radiology, Washington University School of Medicine, St. Louis,
USA.
(4)FMRIB Centre, Oxford University, Oxford, UK.
(5)Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital,
Hartford, USA.
(6)Department of Statistics, University of Warwick, Warwick, UK.
(7)Maryland Psychiatric Research Center, University of MD School of Medicine,
Baltimore USA.
(8)Center for Magnetic Resonance Research, Department of Radiology, University of
Minnesota Medical School, Minneapolis, MN, USA.
(9)University Medical Center Utrecht, Utrecht, The Netherlands.
(10)Vanderbilt University, Nashville, TN, USA.
(11)INSERM-CEA-Faculté de Médecine Paris-Sud, Orsay France.
(12)VU University, Amsterdam, The Netherlands.
(13)Radboud University, Nijmegen, The Netherlands.
(14)University of Edinburgh, Edinburgh, UK.
(15)Texas Biomedical Research Institute, San Antonio, TX, USA.
(16)University of Queensland, Brisbane, Australia.
(17)University of Texas Health Science Center San Antonio, San Antonio, TX, USA.
(18)QIMR Berghofer, Brisbane, Australia.
(19)University of Maryland, Baltimore, MD, USA.
(20)Duke University, Durham, NC, USA.
(21)Anatomy & Neurobiology Department, Washington University in St. Louis, St.
Louis, USA.

The degree to which genetic factors influence brain connectivity is beginning to
be understood. Large-scale efforts are underway to map the profile of genetic
effects in various brain regions. The NIH-funded Human Connectome Project (HCP)
is providing data valuable for analyzing the degree of genetic influence
underlying brain connectivity revealed by state-of-the-art neuroimaging methods.
We calculated the heritability of the fractional anisotropy (FA) measure derived
from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287
M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA
measurements were derived using (Enhancing NeuroImaging Genetics through
Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated
using the SOLAR-Eclipse imaging genetic analysis package. We compared
heritability estimates derived from HCP data to those publicly available through
the ENIGMA-DTI consortium, which were pooled together from five-family based
studies across the US, Europe, and Australia. FA measurements from the HCP cohort
for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90,
p

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