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The neuronal chromatin landscape in brains from individuals with schizophrenia is linked to early fetal development

Nature Neuroscience (2025)Cite this article

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Abstract

Noncoding variants increase neuropsychiatric disease risk, but our understanding of their cell-type-specific role remains incomplete. We conducted large-scale chromatin accessibility profiling of neurons and non-neurons from 2 neocortical regions in 1,393 libraries. We observed substantial differences in neuronal chromatin accessibility between schizophrenia (SCZ) cases and controls, with upregulated open chromatin regions (OCRs) in neurons associated with SCZ risk loci. A comparison of SCZ-associated OCRs with fetal brain-specific OCRs revealed a strong correlation between upregulated changes in SCZ chromatin and openness in fetal cortical brains, linking disease-related chromatin alterations to neurodevelopment. Here we show that a prominent neuronal trans-regulatory domain containing upregulated OCRs consolidates key neurodevelopmental chromatin signatures and is enriched for immature glutamatergic neurons. These findings link altered adult cortical chromatin states to early developmental mechanisms in SCZ. This study provides a comprehensive cell-type-resolved chromatin accessibility resource for the human cortex and offers insights into the regulatory architecture underlying SCZ risk.

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Fig. 1: Population-scale chromatin accessibility analysis in the human brain.
Fig. 2: SCZ OCRs and inferred SCZ trajectory in PFC neurons.
Fig. 3: cis-regulatory landscape and TRDs from hierarchical clustering of neuronal SCZ CRDs from the PFC.
Fig. 4: Analysis of cell-type specificity of neuronal PFC SCZ OCRs in fetal cortical scATAC-seq data.
Fig. 5: PFC TRD6 can stratify SCZ, BD and MDD cases and controls in the MVP cohort.

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Data availability

Raw FASTQ files are available at NIMH Data Archive (https://nda.nih.gov/edit_collection.html?id=5063), under Collection ID 5063 (CommonMind Consortium), see dataset ID 72038 (CMC FANS-sorted ATAC-seq). Access to NDA requires data use agreement approval. Controlled access is required to protect participant confidentiality and comply with informed consent and NIH data-sharing policies. Researchers may request access by submitting a Data Use Agreement through the NDA portal, specifying the Collection and Dataset IDs. Requests are reviewed by NDA and decisions are typically issued within ten business days. Browsable UCSC genome browser tracks of our processed ATAC-seq data are available as a resource at https://genome.ucsc.edu/s/girdhk01/CMC_ATAC. OCR coordinates, differential OCRs, CRDs and differential CRDs are available at the Synapse repository at syn52264219. Access to synapse requires data use agreement approval. These are Tier 1 Synapse datasets and can be accessed without restriction by any registered Synapse user after agreeing to the Synapse Terms of Use. External validation sets used in the study are ATAC-seq fetal-specific peaks that can be found at https://www.synapse.org/#!Synapse:syn52267265 and CTCF ChIP-seq on human neural cell (GEO GSE127577). TruSeq3-PE.fa file was downloaded from the adapter folder under the trimmotic repository via GitHub at https://github.com/timflutre/trimmomatic/blob/master/adapters/TruSeq3-PE.fa. Supplementary Information is available for this study at https://www.synapse.org/#!Synapse:syn52264219. Correspondence and requests for materials should be addressed to K.G and P.R. Reprints and permissions information are available at www.nature.com/reprints. Source data are provided with this paper.

Code availability

All publicly available software used is noted in Methods. Full decorate code can be found via Zenodo at https://doi.org/10.5281/zenodo.17048920 (ref. 69).

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Acknowledgements

We thank the patients and families who donated material for these studies. Brain tissue for the study was obtained through the NIH Neurobiobank from the following brain bank collections: The Mount Sinai/JJ Peters VA Medical Center NIH Brain and Tissue Repository, Brain Tissue Donation Program at the University of Pittsburgh and the HBCC within the National Institute of Mental Health’s Intramural Research Program (NIMH-IRP). We thank the computational resources and staff expertise provided by the Scientific Computing at the Icahn School of Medicine at Mount Sinai. We thank members of the Roussos Lab for helpful discussion. This research is based on data from the MVP, Office of Research and Development, and Veterans Health Administration and was supported by award VA Merit I01BX004189. This publication does not represent the views of the Department of Veteran Affairs or the US Government. We thank the participants of the MVP, the scientists, clinicians and supportive staff involved in the construction of this biobank, and the scientific computing staff for the expertise that they provided. This study was supported by the National Institute of Mental Health (NIH grant nos. RF1-MH128970 to P.R., R01-MH110921 to P.R., U01-MH116442 to P.R., R01-MH125246 to P.R., R01-MH109897 to P.R. and 75N95019C00049 to V.H.); the National Institute on Aging (NIH grant nos. R01-AG050986 to P.R., R01-AG067025 to P.R. and R01-AG065582 to P.R.); by Veterans Affairs Merit (grant nos. I01BX002395 and I01BX004189 to P.R.). The HBCC is supported through project ZIC-MH002903. This work was supported in part through the computational and data resources and staff expertise provided by Scientific Computing and Data at the Icahn School of Medicine at Mount Sinai and supported by the Clinical and Translational Science Awards (CTSA) grant UL1TR004419 from the National Center for Advancing Translational Sciences. Research reported in this publication was also supported by the Office of Research Infrastructure of the National Institutes of Health under award nos. S10OD026880 and S10OD030463. This research was supported (in part) by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered works of the US Government. However, the findings and conclusions presented in this study are those of the author(s) and do not necessarily reflect the views of the NIH or the US Department of Health and Human Services.

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Author notes

  1. These authors contributed equally: Kiran Girdhar, Jaroslav Bendl.

Authors and Affiliations

  1. Center for Disease Neurogenomics, New York, NY, USA

    Kiran Girdhar, Jaroslav Bendl, Karen Therrien, Sanan Venkatesh, Rachel Bercovitch, Deepika Mathur, Pengfei Dong, Samir Rahman, Steven P. Kleopoulos, Ruth Misir, Sarah M. Reach, Georgios Voloudakis, Gabriel E. Hoffman, John F. Fullard & Panos Roussos

  2. Friedman Brain Institute, New York, NY, USA

    Kiran Girdhar, Jaroslav Bendl, Karen Therrien, Sanan Venkatesh, Rachel Bercovitch, Deepika Mathur, Pengfei Dong, Samir Rahman, Steven P. Kleopoulos, Ruth Misir, Sarah M. Reach, Vahram Haroutunian, Georgios Voloudakis, Gabriel E. Hoffman, John F. Fullard & Panos Roussos

  3. Department of Psychiatry, New York, NY, USA

    Kiran Girdhar, Jaroslav Bendl, Karen Therrien, Sanan Venkatesh, Rachel Bercovitch, Deepika Mathur, Pengfei Dong, Samir Rahman, Steven P. Kleopoulos, Ruth Misir, Sarah M. Reach, Vahram Haroutunian, Georgios Voloudakis, Gabriel E. Hoffman, John F. Fullard & Panos Roussos

  4. Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Kiran Girdhar, Jaroslav Bendl, Karen Therrien, Sanan Venkatesh, Deepika Mathur, Pengfei Dong, Samir Rahman, Steven P. Kleopoulos, Ruth Misir, Sarah M. Reach, Georgios Voloudakis, Gabriel E. Hoffman, John F. Fullard & Panos Roussos

  5. Phenome Health, Seattle, WA, USA

    Andrew Baumgartner

  6. Mental Illness Research Education and Clinical Center, New York, NY, USA

    Karen Therrien, Sanan Venkatesh, Rachel Bercovitch, Vahram Haroutunian, Georgios Voloudakis, Gabriel E. Hoffman & Panos Roussos

  7. Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, New York, NY, USA

    Karen Therrien, Sanan Venkatesh, Rachel Bercovitch, Georgios Voloudakis, Gabriel E. Hoffman & Panos Roussos

  8. Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA

    Pavan K. Auluck & Stefano Marenco

  9. Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    David A. Lewis

  10. Institute for Systems Biology, Seattle, WA, USA

    Cory C. Funk

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  1. Kiran Girdhar
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  2. Jaroslav Bendl
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Contributions

Conception and study design: P.R. Data generation: S.P.K., R.M., S.M.R., S.R. and J.F.F. Data processing and analysis: K.G., J.B., A.B., C.C.F., K.T., R.B., S.V., D.M., P.D., G.V. and G.E.H. Provision of brain tissue and resources: V.H., P.K.A., S.M. and D.A.L. Writing of the paper: K.G., J.B., J.F.F. and P.R., with input from all authors.

Corresponding authors

Correspondence to Kiran Girdhar or Panos Roussos.

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Nature Neuroscience thanks Inge Holtman and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Girdhar, K., Bendl, J., Baumgartner, A. et al. The neuronal chromatin landscape in brains from individuals with schizophrenia is linked to early fetal development. Nat Neurosci (2025). https://doi.org/10.1038/s41593-025-02081-3

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