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 LandmanHervé 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

Research output: Contribution to journalArticlepeer-review

117 Scopus citations

Abstract

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 (h2=0.53-0.90, p<10-5), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application.

Original languageEnglish (US)
Pages (from-to)300-311
Number of pages12
JournalNeuroImage
Volume111
DOIs
StatePublished - May 1 2015

Bibliographical note

Funding Information:
The TAOS study (PI DEW) was supported by the National Institute on Alcohol Abuse and Alcoholism (R01AA016274) — “Affective and Neurobiological Predictors of Adolescent-Onset AUD” and the Dielmann Family.

Funding Information:
This work was supported in part by a Consortium grant ( U54 EB020403 ) from the NIH Institutes contributing to the Big Data to Knowledge (BD2K) Initiative, including the NIBIB and NCI.

Funding Information:
The BrainSCALE study (PI HH and DB) was supported by grants from the Dutch Organization for Scientific Research (NWO) to HEH (051.02.061) and HEH, DIB and RSK (051.02.060).

Funding Information:
The QTIM study was supported by National Health and Medical Research Council (NHMRC 486682), Australia. GdZ is supported by an ARC Future Fellowship (FT0991634).

Funding Information:
This study was supported by R01 EB015611 to PK, R01 HD050735 to PT, MH0708143 and MH083824 grants to DCG and by MH078111 and MH59490 to JB. Additional support for algorithm development was provided by NIH R01 grants EB008432 , EB008281 , and EB007813 (to PT). JES is supported by a Clinical Research Training Fellowship from the Wellcome Trust ( 087727/Z/08/Z ). AMM is supported by a NARSAD Independent Investigator Award and by a Scottish Funding Council Senior Clinical Fellowship.

Funding Information:
Data collection for the Bipolar Family Study was supported by an Academy of Medical Sciences/Health Foundation Clinician Scientist Fellowship to AMM. The methods employed for data acquisition and image reconstruction in the Human Connectome Project were supported in part by Biotechnology Research Center grant (Principal Investigator Kamil Ugurbil; P41 EB0 15894 ) from NIBIB, NIH.

Funding Information:
Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.

Funding Information:
The NTR study (PI DvtE) was supported by The Netherlands Organisation for Scientific Research (NWO) [Medical Sciences (MW): grant no. 904-61-193; Social Sciences (MaGW): grant no. 400-07-080; Social Sciences (MaGW): grant no. 480-04-004].

Funding Information:
The GOBS study (PI DG and JB) was supported by the National Institute of Mental Health Grants MH0708143 (Principal Investigator [PI]: DCG), MH078111 (PI: JB), and MH083824 (PI: DCG & JB).

Publisher Copyright:
© 2015 Elsevier Inc.

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