Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity

Abstract

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance.

Adolescent Tuning of Association Cortex in Human Structural Brain Networks

“…However, the security of this interpretation rests on the more fundamental assumption that structural correlation measured from MRI data on multiple subjects is a reasonable proxy marker of the average weight of axo-synaptic connectivity between regions (Alexander-Bloch, Giedd et al 2013). Beyond humans (Gong et al 2012), there is evidence of such correspondence from animal models (Yee et al 2017). …”

“…Specifically, up to 35% variance in structural correlation in mice was explained by a combination of tract-tracing-derived structural connectivity, gene expression and distance (Yee et al 2017), providing a link of the macroscopic structural networks to underlying microscale cortical organization. The relationship of structural correlation networks to gene expression has also been investigated within humans using the present data, demonstrating overlap between regional co-expression of genes (Hawrylycz et al 2012), particularly of a subset of genes enriched in supragranular layers of cerebral cortex, and structural correlation patterns (Romero-Garcia et al 2017).…”

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain

“…In this context, Magnetic Resonance Imaging (MRI)-based methods such as regional structural covariance (Evans, 2013) offer a proxy measure of brain connectivity, with structural similarity of spatially distinct regions of cortex reflecting coordinated maturation . This inter-regional similarity is supported by similar genetic or maturational profiles , transcriptomic profiles (Yee et al, 2018), or associated with changes in disease (e.g., Zuo et al, 2018). Together with complementary information from MRI estimates of structural (tractography) and functional connectivity (Gong et al, 2013), regional similarity could capture more accurately the brain's structural and functional organization.…”

Shaping Brain Structure: Genetic and Phylogenetic Axes of Macro Scale Organization of Cortical Thickness

“…The local processes that govern the observed distribution of cortical thickness are reasonably well understood. For example, associations between structural and functional connectivity may arise due to shared trophic changes at the synaptic and cellular levels 36, 37 and/or reflect coupled expression of genes enriched in supra-granular layers 38 that are associated with transcriptomic similarity of local brain regions 39 . Importantly both of these effects converge with postmortem inter-regional correlations of gene expression 40 .…”