ArticleNeuroImage2018
Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.
Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers, 3 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
105 citing papers in PubMed, 3 syntheses or guidelines pooled it, 231 citations in OpenAlex.
- Network Centrality and Modularity of Structural Covariance Networks in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study.Brain connectivity · 2023Pooled it
- Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder: Results From the ENIGMA-PGC Posttraumatic Stress Disorder Consortium.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2022Pooled it
- Structural covariance networks in schizophrenia: A systematic review Part II.Schizophrenia research · 2022Pooled it
- Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes.Proceedings of the National Academy of Sciences of the United States of America · 2019Trial
- Individual-level metabolic connectivity captures cortical morphology and their coupling strengthens in the ageing brain.European journal of nuclear medicine and molecular imaging · 2026Article
- Longitudinal connectomics-based tractometry for characterizing white matter reorganization following brain tumor surgery: a proof-of-concept case series.Journal of neuro-oncology · 2026Article
- Optimizing brain functional-structural architecture with cTBS to reduce relapse in alcohol use disorder: a randomized controlled trial.Molecular psychiatry · 2026Article
- Opportunities and pitfalls of data contextualization in neuroimaging.Nature reviews. Neuroscience · 2026Review
- Decoupling of neurophysiological activity from structure mirrors global microarchitectural and neuromodulatory trends.Communications biology · 2026Article
- Brain functional-structural gradient coupling reflects development, behavior and genetic influences.Nature communications · 2026Article
- Individual-level metabolic connectivity captures cortical morphology and their coupling strengthens with age.bioRxiv : the preprint server for biology · 2026Article
- Digital twin brain reveals state-specific stimulation targets for abnormal brain dynamics in tinnitus.BMC medicine · 2026Article
- The biological role of local and global fMRI BOLD signal variability in multiscale human brain organization.Nature communications · 2026Article
- Aberrant network topology of cortical-subcortical circuits in schizophrenia and bipolar disorder: a graph theory study.Frontiers in psychiatry · 2026Article
- Five energy metabolism pathways show distinct regional distributions and lifespan trajectories in the human brain.PLoS biology · 2026Article
- Characterizing Spatial Associations Between GluCEST MRI and Neurotransmitter Receptor Density in the Human Cortex.Human brain mapping · 2025Article
- Neurobiological subtypes of adolescent depression: a multimodal integration of morphometric similarity network and spatial transcriptomics.Molecular psychiatry · 2025Article
- Brain Myelin Covariance Networks: Gradients, Cognition, and Higher-Order Landscape.Behavioral sciences (Basel, Switzerland) · 2025Article
- Network spreading and local biological vulnerability in amyotrophic lateral sclerosis.Communications biology · 2025Article
- Mapping cerebral blood perfusion and its links to multi-scale brain organization across the human lifespan.PLoS biology · 2025Article
45 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.