Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group
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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/).
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The CST ROI from the JHU WMPM atlas is limited to a small region in the inferior portion of the brain and has been shown to be the least reliable and reproducible ROI.
“However, the CST ROI from the JHU WMPM atlas is limited to a small region in the inferior portion of the brain and has been shown to be the least reliable and reproducible ROI (Jahanshad et al., 2013; Acheson et al., 2017)”
From Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3 (2019) · cites this paper as Jahanshad et al., 2013
The Methods (Region of interest extraction; page unavailable) identify the JHU white matter parcellation atlas, and the Results (Meta and mega analyses; page unavailable) describe the CST as small and, with the fornix, among the least heritable regions and difficult to register. The Discussion cautions that CST may not be a reliable endophenotype in multisite studies. These passages do not establish that its atlas ROI is confined to an inferior brain region or that it is the least reliable and reproducible ROI. (LLM, conf=0.86)
Experimental — accuracy not yet measuredMany large-scale multi-site DTI studies have obtained consistent results even when acquisition protocols across sites are not harmonized in advance.
“Although many large-scale multi-site DTI studies have obtained consistent results even when acquisition protocols across sites are not harmonized in advance (Jahanshad et al., 2013; Kochunov et al., 2014; Acheson et al., 2017; Kelly et al., 2018), differences in dMRI acquisition parameters, including vendor, voxel size, and angular resolution, are known to affect derived dMRI measures (Alexander”
From Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3 (2019) · cites this paper as Jahanshad et al., 2013
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Genetic variants in the ErbB4 gene are associated with white matter integrity
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Self-citationRelationship of a Variant in theNTRK1Gene to White Matter Microstructure in Young Adults
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Self-citationBlood pressure and cerebral white matter share common genetic factors in Mexican Americans
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Self-citationA framework for the analysis of phantom data in multicenter diffusion tensor imaging studies
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“Although many largescale multi-site DTI studies have obtained consistent results even when acquisition protocols across sites are not harmonized in advance (Jahanshad et al., 2013; Kochunov et al., 2014; Acheson et al., 2017; Kelly et al., 2018), differences in dMRI acquisition parameters, including vendor, voxel size…”
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Eye-brain connections revealed by multimodal retinal and brain imaging genetics
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Mega‐analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group
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Self-citationBrain morphologic changes in asymptomatic C9orf72 repeat expansion carriers
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Mapping connectivity in the developing brain
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Self-citationHeritability of structural brain network topology: A DTI study of 156 twins
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Self-citationChanges in white matter microstructure predict lithium response in adolescents with bipolar disorder
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Self-citationCharacterizing white matter changes in chronic schizophrenia: A free-water imaging multi-site study
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White Matter in Schizophrenia Treatment Resistance
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Self-citationThe P-factor and its genomic and neural equivalents: an integrated perspective
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Self-citationStructural Brain Connectivity as a Genetic Marker for Schizophrenia
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A White Matter Connection of Schizophrenia and Alzheimer’s Disease
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Self-citationRole of frontal white matter and corpus callosum on social function in schizophrenia
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Self-citationThe variability of MR axon radii estimates in the human white matter
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ENIGMA brain injury: Framework, challenges, and opportunities
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Self-citation
- Authors
- Jahanshad, N., Kochunov, P. V., Sprooten, E., Mandl, R. C., Nichols, T. E., Almasy, L., Blangero, J., Brouwer, R. M., Curran, J. E., de Zubicaray, G. I., Duggirala, R., Fox, P. T., Hong, L. E., Landman, B. A., Martin, N. G., McMahon, K. L., Medland, S. E., Mitchell, B. D., Olvera, R. L., Peterson, C. P., Starr, J. M., Sussmann, J. E., Toga, A. W., Wardlaw, J. M., Wright, M. J., Hulshoff Pol, H. E., Bastin, M. E., McIntosh, A. M., Deary, I. J., Thompson, P. M., & Glahn, D. C.
- Affiliations
- University of California, Los Angeles (US)
- University of Maryland, Baltimore (US)
- Royal Edinburgh Hospital (GB)
- Utrecht University (NL)
- University of Warwick (GB)
- Texas Biomedical Research Institute (US)
- The University of Texas at San Antonio Health Science Center (US)
- Vanderbilt University (US)
- QIMR Berghofer Medical Research Institute (AU)
- The University of Queensland (AU)
- University of Edinburgh (GB)
- Yale University (US)
- ORCID
- Jahanshad, Neda
- Kochunov, Peter V.
- Sprooten, Emma
- Mandl, René C.
- Nichols, Thomas E.
- Almasy, Laura
- Blangero, John
- Brouwer, Rachel M.
- Curran, Joanne E.
- Fox, Peter T.
- Hong, L. Elliot
- Landman, Bennett A.
- Martin, Nicholas G.
- McMahon, Katie L.
- Medland, Sarah E.
- Mitchell, Braxton D.
- Olvera, Rene L.
- Starr, John M.
- Toga, Arthur W.
- Wardlaw, Joanna M.
- Wright, Margaret J.
- Bastin, Mark E.
- McIntosh, Andrew M.
- Deary, Ian J.
- Thompson, Paul M.
- Glahn, David C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 81
- Pages
- 455-469
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3729717
- OpenAlex
- W2118347577
- Cited by
- 393
- References
- 86
- Citations by year
- 2026: 15 · 2025: 22 · 2024: 28 · 2023: 20 · 2022: 21 · 2021: 32 · 2020: 45 · 2019: 38 · 2018: 31 · 2017: 32 · 2016: 32 · 2015: 32 · 2014: 28 · 2013: 16
- FWCI
- 27.94
- Type
- journal article
- Language
- en
- Update notices
- erratum (2014-04-15)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
- PubMed Central (acceptedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by-nc-nd)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by-nc-nd)
- Faculty of Health; Institute of Health and Biomedical Innovation
- Funders
- R01 HD050735 (486682)
- R01 EB015611 (EB008432, EB008281, EB007813)
- MH0708143 (FT0991634)
- MH083824 (087727/Z/08/Z)
- MH078111
- MH59490
- National Health and Medical Research Council (NHMRC
- NIH (EB015611-01, U54MH091657-03)
- ARC Future Fellowship
- Wellcome Trust
- NARSAD Independent Investigator Award
- Scottish Funding Council Senior Clinical Fellowship
- Academy of Medical Sciences/Health Foundation Clinician Scientist Fellowship
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Neurology › Cerebrovascular and genetic disorders
- Keywords
- diffusion tensor imaging, fractional anisotropy, heritability, white matter integrity, ENIGMA consortium, mega-analysis
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Brain, Brain Mapping, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Pilot Projects, Registries, Anisotropy, Young Adult, Diffusion Tensor Imaging
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