Relating quantitative 7T MRI across cortical depths to cytoarchitectonics, gene expression and connectomics

Abstract

Ultra-high field MRI across the depth of the cortex has the potential to provide anatomically precise biomarkers and mechanistic insights into neurodegenerative disease like Huntington's disease that show layer-selective vulnerability. Here we compare multi-parametric mapping (MPM) measures across cortical depths for a 7T 500 μm whole brain acquisition to (a) layer-specific cell measures from the von Economo histology atlas, (b) layer-specific gene expression, using the Allen Human Brain atlas and (c) white matter connections using high-fidelity diffusion tractography, at a 1.3 mm isotropic voxel resolution, from a 300mT/m Connectom MRI system. We show that R2*, but not R1, across cortical depths is highly correlated with layer-specific cell number and layer-specific gene expression. R1- and R2*-weighted connectivity strength of cortico-striatal and intra-hemispheric cortical white matter connections was highly correlated with grey matter R1 and R2* across cortical depths. Limitations of the layer-specific relationships demonstrated are at least in part related to the high cross-correlations of von Economo atlas cell counts and layer-specific gene expression across cortical layers. These findings demonstrate the potential and limitations of combining 7T MPMs, gene expression and white matter connections to provide an anatomically precise framework for tracking neurodegenerative disease.

Keywords: gene expression; histology; neurodegeneration; ultra-high field MRI.

FIGURE 1

R2* and R1 values sampled at 50% cortical depth projected on FreeSurfer average inflated cortical surfaces (a) R2* (in 1/s) (b) R1 (in 1/s)

FIGURE 2

R1 and R2* profiles across primary sensory, primary motor and association cortices. Cortical depth profile, where y‐axis is MRI contrast (R1 or R2*) and x‐axis is equi‐volume cortical depth (1—nearest pial surface, 8—nearest grey matter/white matter [GM/WM] boundary), for visual cortex (a) R1 and (b) R2*, sensorimotor motor cortex (c) R1 and (d) R2*, auditory cortex (e) R1 and (f) R2* and superior parietal cortex (g) R1 and (h) R2*. GM—grey matter, WM—white matter, V1—primary visual area, V2–V6—visual areas 2 to 6, MT—middle temporal area. 1—area 1, 2—area 2, 3a—area 3a, 3b—area 3b, 4—area 4 (primary motor cortex). A1—primary auditory cortex, RI—retroinsular cortex, MBelt—medial belt, LBelt—lateral belt, PBelt—parabelt. 7PL—lateral area 7P, LIPv—area lateral intra‐parietal ventral, IP1—intra‐parietal 1, MIP—medial intra‐parietal area, LIPd—area lateral intra‐parietal dorsal. Standard error of the mean (SEM) is displayed as error bars for each cortical depth. Cortical labels refer to Glasser et al. (2016). Myeloarchitectonic profiles presented alongside graphs are reproduced from Zilles, Palomero‐Gallagher, and Amunts (2015) and based on original drawings by Vogt and Vogt (1919) were layers are defined based on myeloarchitectonics not equi‐volume cortical layers. Profiles are provided for areas V1 (singulostriate—absence of inner Baillarger stripe), BA4 (astriate—Baillarger stripes cannot be delineated), A1 (unitostriate—both Baillarger stripes appear to be fused to a broad band) and IPL (bistriate—both Baillarger stripes are clearly detectable). These images are not included in the CC‐BY 4.0 licence

FIGURE 3

Relationship between R2*, R1 and von Economo cell count. (a) Average R2* against von Economo (VE) cell count for each VE MRI region of interest (ROI). Each blue dot is an ROI, were the y‐axis represents the average R2*, for each ROI across participants, and the x‐axis represents the average VE cell count, the red line represents a least squares linear regression line. (b) R2* across cortical depths against von Economo cortical layer cell count, where the y‐axis represents R2* for each equi‐volume cortical depth 1–8 and the x‐axis represents VE cell number for each cortical layer I‐VI, the colours represent the correlations across VE ROIs for R2* and VE cell count (highest—yellow, lowest—blue). (c) Average R1 against von Economo (VE) cell count for each VE MRI region of interest (ROI). (d) R1 across cortical depths against von Economo cortical layer cell count. Asterisks indicate Bonferroni‐corrected significant correlations

FIGURE 4

7T MRI R2* and cortical layer‐specific genes. R2* against (a) layer 2 genes, (b) layer 3 genes, (c) layer 4 genes, (d) layer 5 genes. Each blue dot represents an ROI from the HCP‐MMP 1.0 atlas, the y‐axis represents R2*, averaged across participants, and the x‐axis represents the PCA score for each ROI from the first PCA component of layer‐specific gene expression. (e) R2* across cortical depths, where the y‐axis represents R2* for each equi‐volume cortical depth 1–8 and the x‐axis represents the PCA score for each ROI from the first PCA component of layer‐specific gene expression for layers II–VI, the colours represent the correlations across HCP‐MMP 1.0 ROIs for R2* and layer‐specific gene expression (most positive—yellow, most negative—blue). Asterisks indicate Bonferroni‐corrected significant correlations

FIGURE 5

Cortical depth 7T qMRI is related to white matter connection subtypes. (a) R1 cortical depth against streamline‐weighted connections, where the y‐axis represents R1 across cortical depths averaged across participants and the x‐axis represents streamline weighted connectivity for different white matter connection subtypes (cortical‐striatal (C‐S), cortical‐thalamic (C‐T), cortical‐cortical (C‐C), Inter‐hemispheric (Inter‐H), Intra‐hemispheric (Intra‐H), averaged across participants. Colours represent correlation across Desikan‐Killiany atlas ROIs for R1 and streamline weighted connectivity (highest—yellow, lowest—blue), (b) R2* cortical depth against streamline‐weighted connections, (c) R1 cortical depth against R1‐weighted connections, (d) R2* cortical depth against R2*‐weighted connections. Asterisks indicate Bonferroni‐corrected significant correlations

FIGURE 6

A high anatomical precision framework for neurodegenerative disease. Schematic showing how we can use qMRI and the relationships identified in this study to combine information on white matter (R1, R2*), neuronal count across cortical depths (R2*), myelination across cortical depths (R1, R2*) and pathogenic gene expression (R2*) to provide a comprehensive picture of neurodegeneration