{"id":"doi:10.1016/j.neuroimage.2017.12.060","kind":"article","title":"Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex","authors":["Romero-Garcia R","Whitaker KJ","Váša F","Seidlitz J","Shinn M","Fonagy P","Dolan RJ","Jones PB","Goodyer IM","Bullmore ET","Vértes PE"],"author_count":11,"year":2018,"published":"2017-12-21","venue":"NeuroImage","cited_by":197,"doi":"10.1016/j.neuroimage.2017.12.060","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.neuroimage.2017.12.060","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.neuroimage.2017.12.060","updated":null,"pmid":"29274746","pmcid":"PMC5883331","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC5883331/pdf","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.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex\" by Romero-Garcia R, Whitaker KJ, Váša F et al., https://doi.org/10.1016/j.neuroimage.2017.12.060, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"connectomics","name":"Connectomics & Brain Mapping","domain_slug":"neuroscience"}],"cited_in_dossiers":[]}