Variability and heritability of mouse brain structure: Microscopic MRI atlases and connectomes for diverse strains

Nian Wang; Robert J. Anderson; David G. Ashbrook; Vivek Gopalakrishnan; Youngser Park; Carey E. Priebe; Yi Qi; Rick Laoprasert; Joshua T. Vogelstein; Robert W. Williams; G. Allan Johnson

NeuroImage (Nov 2020)

Variability and heritability of mouse brain structure: Microscopic MRI atlases and connectomes for diverse strains

Nian Wang,
Robert J. Anderson,
David G. Ashbrook,
Vivek Gopalakrishnan,
Youngser Park,
Carey E. Priebe,
Yi Qi,
Rick Laoprasert,
Joshua T. Vogelstein,
Robert W. Williams,
G. Allan Johnson

Affiliations

Nian Wang: Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Duke University Medical Center Box 3302, Durham, NC 27710, USA
Robert J. Anderson: Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Duke University Medical Center Box 3302, Durham, NC 27710, USA
David G. Ashbrook: Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
Vivek Gopalakrishnan: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA
Youngser Park: Center for Imaging Science, Johns Hopkins University, Baltimore, MD 21287, USA
Carey E. Priebe: Center for Imaging Science, Johns Hopkins University, Baltimore, MD 21287, USA; Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21287, USA
Yi Qi: Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Duke University Medical Center Box 3302, Durham, NC 27710, USA
Rick Laoprasert: Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Duke University Medical Center Box 3302, Durham, NC 27710, USA
Joshua T. Vogelstein: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA; Center for Imaging Science, Johns Hopkins University, Baltimore, MD 21287, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21287, USA; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21287, USA
Robert W. Williams: Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
G. Allan Johnson: Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Duke University Medical Center Box 3302, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA; Corresponding author at: Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Duke University Medical Center Box 3302, Durham, NC 27710, USA.

Journal volume & issue: Vol. 222
p. 117274

Abstract

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Genome-wide association studies have demonstrated significant links between human brain structure and common DNA variants. Similar studies with rodents have been challenging because of smaller brain volumes. Using high field MRI (9.4 T) and compressed sensing, we have achieved microscopic resolution and sufficiently high throughput for rodent population studies. We generated whole brain structural MRI and diffusion connectomes for four diverse isogenic lines of mice (C57BL/6J, DBA/2J, CAST/EiJ, and BTBR) at spatial resolution 20,000 times higher than human connectomes. We measured narrow sense heritability (h2) I.e. the fraction of variance explained by strains in a simple ANOVA model for volumes and scalar diffusion metrics, and estimates of residual technical error for 166 regions in each hemisphere and connectivity between the regions. Volumes of discrete brain regions had the highest mean heritability (0.71 ± 0.23 SD, n = 332), followed by fractional anisotropy (0.54 ± 0.26), radial diffusivity (0.34 ± 0.022), and axial diffusivity (0.28 ± 0.19). Connection profiles were statistically different in 280 of 322 nodes across all four strains. Nearly 150 of the connection profiles were statistically different between the C57BL/6J, DBA/2J, and CAST/EiJ lines. Microscopic whole brain MRI/DTI has allowed us to identify significant heritable phenotypes in brain volume, scalar DTI metrics, and quantitative connectomes.

Published in NeuroImage

ISSN: 1053-8119 (Print); 1095-9572 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Website: https://www.journals.elsevier.com/neuroimage

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