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Cited by 133Advanced Neuroimaging Techniques and ApplicationsGenetic Associations and EpidemiologyFunctional Brain Connectivity Studies

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

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Kochunov, Peter, Jahanshad, Neda, Sprooten, Emma, Nichols, Thomas E., Mandl, René C., Almasy, Laura, Booth, Tom, Brouwer, Rachel M. +33 more·2014·NeuroImage
DOI 10.1016/j.neuroimage.2014.03.033PMC PMC4043878
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Abstract

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

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  • Many 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 Kochunov et al., 2014

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Authors
Kochunov, P., Jahanshad, N., Sprooten, E., Nichols, T. E., Mandl, R. C., Almasy, L., Booth, T., Brouwer, R. M., Curran, J. E., de Zubicaray, G. I., Dimitrova, R., Duggirala, R., Fox, P. T., Elliot Hong, L., Landman, B. A., Lemaitre, H., Lopez, L. M., Martin, N. G., McMahon, K. L., Mitchell, B. D., Olvera, R. L., Peterson, C. P., Starr, J. M., Sussmann, J. E., Toga, A. W., Wardlaw, J. M., Wright, M. J., Wright, S. N., Bastin, M. E., McIntosh, A. M., Boomsma, D. I., Kahn, R. S., den Braber, A., de Geus, E. J. C., Deary, I. J., Hulshoff Pol, H. E., Williamson, D. E., Blangero, J., van 't Ent, D., Thompson, P. M., & Glahn, D. C.
Affiliations
  • University of Maryland, Baltimore (US)
  • University of Southern California (US)
  • Yale University (US)
  • University of Warwick (GB)
  • University Medical Center Utrecht (NL)
  • Texas Biomedical Research Institute (US)
  • University of Edinburgh (GB)
  • 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)
  • Alzheimer Scotland (GB)
  • Royal Edinburgh Hospital (GB)
  • Vrije Universiteit Amsterdam (NL)
Corresponding author
Kochunov, Peter
ORCID
Venue
NeuroImage
Publisher
Elsevier BV
Published
2014-07
Volume
95
Pages
136-150
ISSN
1053-8119 (ISSN-L)
DOI
10.1016/j.neuroimage.2014.03.033
PMC
PMC4043878
OpenAlex
W2121332562
Cited by
133
References
78
Citations by year
2026: 6 · 2025: 8 · 2024: 10 · 2023: 9 · 2022: 9 · 2021: 8 · 2020: 16 · 2019: 16 · 2018: 9 · 2017: 11 · 2016: 17 · 2015: 7 · 2014: 6
FWCI
10.02
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
  • VU Research Portal (publishedVersion)
  • Maynooth University ePrints and eTheses Archive (Maynooth University) (acceptedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • QUT ePrints (Queensland University of Technology) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion)
  • Pure Amsterdam UMC (submittedVersion)
  • Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
Funders
NIH (EB008432, EB008281, EB007813)
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
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords
fractional anisotropy, white matter, heritability, additive genetic effects, diffusion tensor imaging, meta-analysis, mega-analysis, data pooling, data harmonization, leave-one-out analysis, solar eclipse, statistical power
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Brain, Child, Female, Humans, Male, Middle Aged, Genetic Variation, Meta-Analysis as Topic, Anisotropy, Young Adult, Diffusion Tensor Imaging, White Matter

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