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Genetic identification of brain cell types underlying schizophrenia
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Abstract
With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.
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“Here, we found widespread enrichments across central nervous system neurons with limited to no signal in glial cells and peripheral nervous system neurons (Table S10, Figure S17).”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [33]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“The atlas will also help us understand the function of specific genes—for example, those implicated in disease (Skene et al., 2018).”
From Molecular Architecture of the Mouse Nervous System (2018) · cites this paper as Skene et al., 2018
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“A similar result was observed using a mouse single-cell dataset14”
From New insights into the genetic etiology of Alzheimer’s disease and related dementias (2022) · cites this paper as [14]
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“In mouse single-cell RNA-seq data16, we found similar patterns of enrichments in genes with high expression in excitatory glutamatergic pyramidal neurons from the cortex and hippocampus (Figure 4b), and inhibitory cortical interneurons.”
From Mapping genomic loci implicates genes and synaptic biology in schizophrenia (2022) · cites this paper as [16]
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“Briefly, brain-cell-type expression data were drawn from single-cell RNA-seq data from mouse brains.”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [53]
In the citing paper
“We also identified a significant gene-set (P = 3.87 × 10-5) containing somatosensory pyramidal neurons using brain cell-type data from Skene, et al. 15 (Table 3).”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [15]
In the citing paper
“Common variation in SCZ maps onto specific groups of cells including pyramidal neurons and medium spiny neurons31.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [31]
In the citing paper
“At present, many psychiatric GWAS are under-powered to accomplish these intentions (Skene et al., 2018).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Skene et al., 2018
In the citing paper
“This inhibitory neuron-related module is not enriched for common or rare genetic disease-associated variation, although other studies have found enrichment for SCZ GWAS signal among interneuron markers defined in other ways (63).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [63]
In the citing paper
“In contrast to AD in which multiple glial cells are implicated, previous work has indicated neurons as the central cell-type harboring genetic risk for the majority of psychiatric disorders3,22,46,58–61.”
From Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders (2021) · cites this paper as [61]
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Cites
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Self-citationBiological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Self-citationMAGMA: Generalized Gene-Set Analysis of GWAS Data
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004219 · Cited by 3,653
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
Zeisel, A., Muñoz-Manchado, A. B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. (2015) · Science · doi:10.1126/science.aaa1934 · Cited by 3,124
Self-citationA subcellular map of the human proteome
Thul, P. J., Åkesson, L., Wiking, M., Mahdessian, D., Geladaki, A., Ait Blal, H., Alm, T., Asplund, A., Björk, L., Breckels, L. M., et al. (2017) · Science · doi:10.1126/science.aal3321 · Cited by 2,813
USING THE CORRECT STATISTICAL TEST FOR THE EQUALITY OF REGRESSION COEFFICIENTS
Paternoster, R., Brame, R. W., Mazerolle, P., & Piquero, A. R. (1998) · Criminology · doi:10.1111/j.1745-9125.1998.tb01268.x · Cited by 2,755
Partitioning heritability by functional annotation using genome-wide association summary statistics
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Rossi, F., Sportelli, L., Kikidis, G. C., Grassi, G., Camillo, F. D., Bertolino, A., Blasi, G., Borcuk, C., Fusco, D., Hyde, T. M., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02646-3 · Cited by 1
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Liu, S., Won, H., Clarke, D., Matoba, N., Khullar, S., Mu, Y., Wang, D., & Gerstein, M. (2022) · Figshare · doi:10.6084/m9.figshare.21622722
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Liu, S., Won, H., Clarke, D., Matoba, N., Khullar, S., Mu, Y., Wang, D., & Gerstein, M. (2022) · Figshare · doi:10.6084/m9.figshare.21622725
Yotova, A. Y. (2024) · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · doi:10.21248/gups.85791
Townsend, H. A., Rosenberger, K. J., Vanderlinden, L. A., Inamo, J., & Zhang, F. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.17.599349
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Weller, A. E., Ferraro, T. N., Doyle, G. A. R., Reiner, B. C., Berrettini, W. H., & Crist, R. C. (2024) · Genes & Genomics · doi:10.1007/s13258-024-01545-3
Currant, H., Arthofer, C., Ferreira, T. C., Douaud, G., Hill, B., Venkatesh, S. S., Baya, N. A., Palmer, D. S., Reibe, S., Moltke-Prehn, A., et al. (2024) · medRxiv · doi:10.1101/2024.08.01.24311295
The neuroanatomical organization of the hypothalamus is driven by spatial and topological efficiency
Smith, N. R., Ameen, S., Miller, S. N., Kasper, J. M., Schwarz, J. M., Hommel, J. D., & Borzou, A. (2024) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2024.1417346 · Cited by 1
Schmitt, A., Popovic, D., Raabe, F. J., Papiol, S., Martins‐de‐Souza, D., & Falkai, P. (2024) · Springer eBooks · doi:10.1007/978-3-030-51366-5_46
Richards, A. L., Fenner, E., Clifton, N. E., Cameron, D., Tume, C. E., Bray, N. J., Legge, S. E., Walters, J., Holmans, P., O’Donovan, M. C., et al. (2025) · medRxiv · doi:10.1101/2025.02.13.25322048
Self-citationFjodorova, M., Prapaiwongs, P., Petter, O., Morella, I., Li, Z., Hall, J. H., Vinh, N., Davies, S., Green, J., Hall, J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.26.640425
Feng, Y., Ji, X., Huang, P., & Yang, S. (2025) · Research Square · doi:10.21203/rs.3.rs-6316036/v1
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Slay, O. K. (2024) · Sheffield Hallam University · doi:10.7190/shu-thesis-00693
Garg, V., Beyene, S., Tanzillo, A. F., Tucker, A., Johantges, A. C., Abebe, D. T., Zhang, Y., & Petros, T. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.28.667082 · Cited by 1
Risperidone regulates the expression of schizophrenia-related genes in the murine forebrainPreprint
Ziemiańska, M., Zięba, M., Radlicka-Borysewska, A., Szumiec, Ł., Gołda, S., Borczyk, M., Piechota, M., Korostyński, M., & Parkitna, J. (2025) · bioRxiv · doi:10.1101/2025.08.18.670814
Marker-free drift correction for 3D RNA imaging via spatiotemporal clustering and imputation
Song, Q., Li, Q., Cao, D., Cai, L., Wu, W., Yang, J., Zhang, Y., & Huang, Z. (2025) · Optics Express · doi:10.1364/oe.570766
Choudhary, A., Sharma, O., Ezer, R. B., Tripathi, U., Rosh, I., Stern, T., Birch, J. D., Nunes, A., Falkovich, G., Alda, M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.28.672780
Chen, R., Siciliano, B., Wang, Q., Xu, C., Wei, Q., Yang, H., Sutcliffe, J. S., Jiang, Y. W., Ji, Y., Liu, C., et al. (2025) · Advanced Science · doi:10.1002/advs.202508519
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Chin, R., Zhang, X.-H., Anderson, K. M., Yendiki, A., & Holmes, A. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.02.673734 · Cited by 1
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Zhan, Y., & Liu, C. (2025) · Neuroscience Bulletin · doi:10.1007/s12264-025-01512-2
Yu, X.-H., Cao, R., Yang, Y., Cao, H., Deng, F., & Lei, S. (2022) · Molecular Genetics and Genomics · doi:10.1007/s00438-025-02304-z
Laighneach, A., Morris, D. W., Patlola, S. R., Improta, M., Desbonnet, L., Donohoe, G. J., Kelly, J. P., & McKernan, D. P. (2025) · PLoS ONE · doi:10.1371/journal.pone.0334451
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Malwade, S., Samudyata, S., Lekander, J. G., Langeder, A., Weinberger, K., Koskuvi, M., Oliveira, A. O., Lehtonen, Š., Arroyo‐García, L. E., Corvin, A. P., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.24.684395
Sun, F., Hui, S., Gong, B., Gu, J., & Huang, P. (2025) · PLoS ONE · doi:10.1371/journal.pone.0336109
A novel key player in cognitive striatal processes: the Pthlh interneuronsPreprint
Díez-Salguero, M., Harder, L., Herr, M., Llorca-Torralba, M., Berrocoso, E., Hjerling‐Leffler, J., & Muñoz‐Manchado, A. B. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.02.691591
Self-citationNovoa, J., Pazos, F., & Chagoyen, M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.09.693155
Parker, N., Furher, J., Nguyen, D. T., Fominykh, V., Jaholkowski, P. P., Akkouh, I. A., O’Connell, K. S., Hagen, E., Bahrahmi, S., Årsland, D., et al. (2025) · medRxiv · doi:10.64898/2025.12.16.25342384 · Cited by 1
Metadata
- Authors
- Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Skene, N. G., Bryois, J., Bakken, T. E., Breen, G., Crowley, J. J., Gaspar, H. A., Giusti-Rodriguez, P., Hodge, R. D., Miller, J. A., Muñoz-Manchado, A. B., O’Donovan, M. C., Owen, M. J., Pardiñas, A. F., Ryge, J., Walters, J. T. R., Linnarsson, S., Lein, E. S., Sullivan, P. F., & Hjerling-Leffler, J.
- Affiliations
- Karolinska Institutet (SE)
- Allen Institute for Brain Science (US)
- National Health Service (GB)
- University of North Carolina at Chapel Hill (US)
- Cardiff University (GB)
- École Polytechnique Fédérale de Lausanne (CH)
- Corresponding author
- Sullivan, Patrick F.
- ORCID
- Skene, Nathan G.
- Bryois, Julien
- Bakken, Trygve E.
- Breen, Gerome
- Crowley, James J.
- Gaspar, Héléna A.
- Giusti-Rodriguez, Paola
- Hodge, Rebecca D.
- Miller, Jeremy A.
- O’Donovan, Michael C.
- Owen, Michael J.
- Pardiñas, Antonio F.
- Ryge, Jesper
- Walters, James T. R.
- Linnarsson, Sten
- Lein, Ed S.
- Sullivan, Patrick F.
- Hjerling-Leffler, Jens
- Venue
- Nature Genetics
- Published
- 2018-05-21
- Volume
- 50
- Issue
- 6
- Pages
- 825-833
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC6477180
- OpenAlex
- W2952673268
- Cited by
- 651
- References
- 68
- Citations by year
- 2026: 65 · 2025: 78 · 2024: 75 · 2023: 70 · 2022: 93 · 2021: 74 · 2020: 88 · 2019: 68 · 2018: 36
- FWCI
- 52.16
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- RODIN (Universidad de Cádiz) (submittedVersion, cc-by-nc-nd)
- Spiral (Imperial College London) (submittedVersion)
- UNC Libraries
- Funders
- National Science Foundation
- Wellcome Trust (108726, /Z/15/Z, 108726/Z/15/Z)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Hjärnfonden
- Vetenskapsrådet (U01-MH-109528, 2014-03863, D0886501)
- Medical Research Council (MR/L011794/1, MR/P005748/1, MR/L010305/1)
- National Institute of Mental Health (U01MH109514, U01MH109528, U01MH109536, MH109532, MH109528, U01MH109532)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- schizophrenia, brain cell types, single-cell RNA sequencing, genome-wide association study, common genetic variants, medium spiny neurons, interneurons, FMRP, synaptic function, genetic risk
- MeSH terms
- Animals, Brain, Humans, Neurons, Schizophrenia, Genetic Predisposition to Disease, Genomics, Mice, Genome-Wide Association Study
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