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Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

Accepted version
Peer-reviewed

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Authors

Romero-Garcia, Rafael 
Whitaker, Kirstie J 
Váša, František 
Shinn, Maxwell 

Abstract

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks.

Description

Keywords

Allen Human Brain Atlas, Cortical thickness, Gene expression, Structural brain network, Transcriptomic brain network, Adolescent, Adult, Algorithms, Cerebral Cortex, Connectome, Female, Humans, Magnetic Resonance Imaging, Male, Nerve Net, Transcriptome, Young Adult

Journal Title

Neuroimage

Conference Name

Journal ISSN

1053-8119
1095-9572

Volume Title

171

Publisher

Elsevier BV
Sponsorship
Wellcome Trust (095844/Z/11/Z)
Medical Research Council (MR/K020706/1)