@article{c07eae6da7154a56ba43ef72b65779e2,
title = "Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA-DTI working group",
abstract = "The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).",
keywords = "Diffusion Tensor Imaging (DTI), Heritability, Imaging genetics, Meta-analysis, Multi-site, Reliability",
author = "Neda Jahanshad and Kochunov, \{Peter V.\} and Emma Sprooten and Mandl, \{Ren{\'e} C.\} and Nichols, \{Thomas E.\} and Almasy, \{Laura A\} and Blangero, \{John C\} and Brouwer, \{Rachel M.\} and Curran, \{Joanne E\} and \{de Zubicaray\}, \{Greig I.\} and Ravindranath Duggirala and Fox, \{Peter T.\} and Hong, \{L. Elliot\} and Landman, \{Bennett A.\} and Martin, \{Nicholas G.\} and McMahon, \{Katie L.\} and Medland, \{Sarah E.\} and Mitchell, \{Braxton D.\} and Olvera, \{Rene L.\} and Peterson, \{Charles P.\} and Starr, \{John M.\} and Sussmann, \{Jessika E.\} and Toga, \{Arthur W.\} and Wardlaw, \{Joanna M.\} and Wright, \{Margaret J.\} and \{Hulshoff Pol\}, \{Hilleke E.\} and Bastin, \{Mark E.\} and McIntosh, \{Andrew M.\} and Deary, \{Ian J.\} and Thompson, \{Paul M.\} and Glahn, \{David C.\}",
note = "Funding Information: This study was supported by R01 HD050735 to PT, R01 EB015611 to PK, MH0708143 and MH083824 grants to DCG, MH078111 to JB. SOLAR is supported by MH59490 to JB. The QTIM study was supported by National Health and Medical Research Council (NHMRC 486682 ), Australia. Additional support for algorithm development was provided by NIH R01 grants EB008432 , EB008281 , and EB007813 (to PT). NIH R01 EB015611-01 \& U54MH091657-03 to TN GdZ is supported by an ARC Future Fellowship ( FT0991634 ). 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 . Data collection for the Bipolar Family Study was supported by an Academy of Medical Sciences/Health Foundation Clinician Scientist Fellowship to AMM.",
year = "2013",
month = nov,
day = "1",
doi = "10.1016/j.neuroimage.2013.04.061",
language = "English (US)",
volume = "81",
pages = "455--469",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press Inc.",
}