Correlated gene expression supports synchronous activity in brain networks
Open accessAbstract
Cooperating brain regions express similar genes: When the brain is at rest, a number of distinct areas are functionally connected. They tend to be organized in networks. Richiardi et al. compared brain imaging and gene expression data to build computational models of these networks. These functional networks are underpinned by the correlated expression of a core set of 161 genes. In this set, genes coding for ion channels and other synaptic functions such as neurotransmitter release dominate. Science , this issue p. 1241
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Studies integrating neuroimaging with transcriptomic data have shown that large-scale imaging features align with spatial gene-expression patterns, providing molecular context for interpreting neuroimaging findings in health and disease.
“Studies integrating neuroimaging with transcriptomic data have shown that large‐scale imaging features align with spatial gene‐expression patterns, providing molecular context for interpreting neuroimaging findings in health and disease. 82 , 83”
From Diffusion MRI reveals amyloid plaque–associated cellular signatures through spatial transcriptomic integration (2026) · cites this paper as [82]
The Abstract (page unavailable) reports that resting-state fMRI networks can be recapitulated from correlated gene expression, supporting the claimed alignment and molecular context. It also notes disease associations for the identified genes, but the imaging analyses used healthy participants; it does not demonstrate that the alignment holds for neuroimaging findings in disease. (LLM, conf=0.83)
Experimental — accuracy not yet measuredInterregional functional connectivity arises from anatomical projection strengths, correlated gene expression, and synaptic receptor densities.
“Interregional FC arises from anatomical projection strengths (Messe et al., 2014; Shen et al., 2012), correlated gene expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b)”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Richiardi et al., 2015
Macroscale FC is modulated by interareal correlated gene expression, areal densities of excitatory and inhibitory receptors, and other microscale architectural features that vary across brain structures.
“macroscale FC is known to be modulated by interareal correlated gene expression, areal densities of excitatory and inhibitory receptors, and other features of microscale architecture that vary across brain structures (Richiardi et al., 2015; Scholtens et al., 2014; Turk et al., 2016; van den Heuvel et al., 2016b)”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Richiardi et al., 2015
Probing cellular and molecular markers across the whole human brain at high-throughput is exceptionally difficult and cannot be done under strict experimental conditions.
“probing cellular and molecular markers across the whole human brain at high-throughput is exceptionally difficult (Richiardi et al., 2015) and cannot be done under strict experimental conditions.”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Richiardi et al., 2015
136 genes whose polymorphisms significantly affect resting-state functional connectivity in a large sample of healthy adolescents have both higher correlation of expression with functional connectivity (μ=0.12, p<2.2e-192) and higher DS (ΔCTX=0.40, p<1.2e-325) in human cortex, though they constitute only a minority (15%) of the highest cortical 5th percentile DS genes.
“Further, we found that 136 genes whose polymorphisms significantly affect resting-state functional connectivity in a large sample of healthy adolescents28 have both higher correlation of expression with functional connectivity (μ=0.12, p<2.2e-192) and higher DS (ΔCTX=0.40, p<1.2e-325) in human cortex (red points, Fig. 7d), though they constitute only a minority (15%) of the highest cortical 5th p”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [28]
Functional brain networks determined using resting-state fMRI can be recapitulated using correlated gene expression in postmortem brain tissue.
“Recent work has revealed that functional brain networks determined using resting-state functional magnetic resonance imaging (fMRI) can be recapitulated using correlated gene expression in postmortem brain tissue28.”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [28]
There is a significant correlation between the transcriptional patterning in the neocortex and functional connectivity (as manifested by the partial correlation functional connectivity matrix), obtained with an independent imaging dataset (HCP).
“As before28, we report here a significant correlation between the transcriptional patterning in the neocortex and functional connectivity (as manifested by the partial correlation functional connectivity matrix), and we obtain this result with an independent imaging dataset (HCP).”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [28]
The canonical transcriptional architecture of the human brain may in some respects be considered a genetic analog to group average anatomical or functional architecture revealed by MRI.
“The canonical transcriptional architecture of the human brain may in some respects be considered a genetic analog to group average anatomical or functional architecture revealed by MRI40, 41, 42.”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [42]
These categories are consistent with a role for these genes in neuronal connectivity and function.
“These categories are consistent with a role for these genes in neuronal connectivity and function as suggested in other studies28.”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [28]
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- Authors
- Richiardi, J., Altmann, A., Milazzo, A.-C., Chang, C., Chakravarty, M. M., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Bromberg, U., Büchel, C., Conrod, P., Fauth-Bühler, M., Flor, H., Frouin, V., Gallinat, J., Garavan, H., Gowland, P., Heinz, A., Lemaître, H., Mann, K. F., Martinot, J.-L., Nees, F., Paus, T., Pausova, Z., Rietschel, M., Robbins, T. W., Smolka, M. N., Spanagel, R., Ströhle, A., Schumann, G., Hawrylycz, M., Poline, J.-B., Greicius, M. D., IMAGEN consortium, Albrecht, L., Andrew, C., Arroyo, M., Artiges, E., Aydin, S., Bach, C., Banaschewski, T., Barbot, A., Barker, G., Boddaert, N., Bokde, A., Bricaud, Z., Bromberg, U., Bruehl, R., Büchel, C., Cachia, A., Cattrell, A., Conrod, P., Constant, P., Dalley, J., Decideur, B., Desrivieres, S., Fadai, T., Flor, H., Frouin, V., Gallinat, J., Garavan, H., Briand, F. G., Gowland, P., Heinrichs, B., Heinz, A., Heym, N., Hübner, T., Ireland, J., Ittermann, B., Jia, T., Lathrop, M., Lanzerath, D., Lawrence, C., Lemaitre, H., Lüdemann, K., Macare, C., Mallik, C., Mangin, J.-F., Mann, K., Martinot, J. L., Mennigen, E., Mesquita de Carvahlo, F., Mignon, X., Miranda, R., Müller, K., Nees, F., Nymberg, C., Paillere, M.-L., Paus, T., Pausova, Z., Poline, J.-B., Poustka, L., Rapp, M., Robert, G., Reuter, J., Rietschel, M., Ripke, S., Robbins, T., Rodehacke, S., Rogers, J., Romanowski, A., Ruggeri, B., Schmäl, C., Schmidt, D., Schneider, S., Schumann, M., Schubert, F., Schwartz, Y., Smolka, M., Sommer, W., Spanagel, R., Speiser, C., Spranger, T., Stedman, A., Steiner, S., Stephens, D., Strache, N., Ströhle, A., Struve, M., Subramaniam, N., Topper, L., Whelan, R., Williams, S., Yacubian, J., Zilbovicius, M., Wong, C. P., Lubbe, S., Martinez-Medina, L., Fernandes, A., & Tahmasebi, A.
- Affiliations
- University of Geneva (CH)
- Functional Imaging in Neuropsychiatric Disorders Laboratory, Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
- VA Palo Alto Health Care System (US)
- National Institutes of Health (US)
- Douglas Mental Health University Institute (CA)
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK.
- Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging and Psychiatry,” University Paris Sud, Orsay, France.
- Rotman Research Institute, University of Toronto, Toronto, Canada.
- Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Cambridge, UK.
- Department of Psychiatry and Psychotherapy, and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.
- Allen Institute for Brain Science (US)
- Stanford University (US)
- University Medical Center Hamburg-Eppendorf (DE)
- King's College London (GB)
- Corresponding author
- Richiardi, Jonas
- Greicius, Michael D.
- ORCID
- Richiardi, Jonas
- Chang, Catie
- Chakravarty, M. Mallar
- Hawrylycz, Mike
- Greicius, Michael D.
- Albrecht, Lisa
- Boddaert, Nathalie
- Cachia, Arnaud
- Constant, Patrick
- Dalley, Jeffrey
- Heinrichs, Bert
- Heym, Nadja
- Ittermann, Bernd
- Jia, Tianye
- Lathrop, Mark
- Lanzerath, Dirk
- Lawrence, Claire
- Mangin, Jean-François
- Mennigen, Eva
- Nymberg, Charlotte
- Poustka, Luise
- Rapp, Michael
- Ruggeri, Barbara
- Schneider, Sophia
- Schwartz, Yannick
- Sommer, Wolfgang
- Spranger, Tade
- Struve, Maren
- Whelan, Robert
- Lubbe, Steven
- Tahmasebi, Amir
- Venue
- Science
- Published
- 2015-06-12
- Volume
- 348
- Issue
- 6240
- Pages
- 1241-1244
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC4829082
- OpenAlex
- W1498123445
- Cited by
- 625
- References
- 50
- Citations by year
- 2026: 34 · 2025: 54 · 2024: 56 · 2023: 55 · 2022: 55 · 2021: 70 · 2020: 63 · 2019: 61 · 2018: 60 · 2017: 61 · 2016: 42 · 2015: 13
- FWCI
- 35.30
- Type
- journal article
- Language
- en
- Open access
- green
- kclpure.kcl.ac.uk
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- Repository@Nottingham (University of Nottingham) (acceptedVersion, other-oa)
- Archive ouverte UNIGE (University of Geneva) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
- Papyrus : Institutional Repository (Université de Montréal) (submittedVersion)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (RO1NS073498)
- U.S. National Institutes of Health (RO1 MH085772-01A1)
- NIH (U54 EB020403)
- Wellcome Trust
- DFG (FOR 1617, EXC 257, SM 80/7-1, SM 80/7-2, SFB 940/1)
- Medical Research Council
- National Institute for Health Research
- BMBF (01GS08152, 01EV0711, eMED SysAlc01ZX1311A)
- Fondation pour la Recherche Médicale
- Feldman Family Foundation
- Eranet-Neuron (AF12-NEUR0008-01 - WM2NA)
- MILDECA
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- resting-state functional connectivity, functional brain networks, correlated gene expression, ion channels, genetic polymorphism, axonal connectivity, synaptic function, postmortem brain, adolescents, mice
- MeSH terms
- Adolescent, Adult, Animals, Brain, Female, Humans, Ion Channels, Magnetic Resonance Imaging, Male, Nerve Net, Neural Pathways, Polymorphism, Genetic, Rest, Synapses, Gene Expression, Mice, Young Adult, Transcriptome
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