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

Overview of attention for article published in NeuroImage, March 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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27 X users
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2 Facebook pages

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Title
Heritability of fractional anisotropy in human white matter: A comparison of Human Connectome Project and ENIGMA-DTI data
Published in
NeuroImage, March 2015
DOI 10.1016/j.neuroimage.2015.02.050
Pubmed ID
Authors

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

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 (h(2)=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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
United Kingdom 2 <1%
Germany 1 <1%
Austria 1 <1%
Brazil 1 <1%
Japan 1 <1%
Spain 1 <1%
Unknown 228 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 58 24%
Researcher 44 18%
Student > Master 21 9%
Student > Doctoral Student 13 5%
Student > Bachelor 13 5%
Other 48 20%
Unknown 41 17%
Readers by discipline Count As %
Neuroscience 58 24%
Medicine and Dentistry 32 13%
Psychology 26 11%
Agricultural and Biological Sciences 23 10%
Engineering 12 5%
Other 26 11%
Unknown 61 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 May 2016.
All research outputs
#2,255,472
of 25,547,904 outputs
Outputs from NeuroImage
#1,716
of 12,237 outputs
Outputs of similar age
#27,681
of 273,150 outputs
Outputs of similar age from NeuroImage
#24
of 185 outputs
Altmetric has tracked 25,547,904 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,237 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 273,150 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 185 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.