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Peer-reviewedCC BYNature

Single-nucleus transcriptome-wide association study of human brain disorders

  • Sanan Venkatesh1,2,3,4,5
  • Roman Kosoy1,2,3,4
  • Zhenyi Wu1,2,3,4,5
  • Marios Anyfantakis1,2,3,4,5
  • Christian Dillard1,2,3,4
  • N. M. Prashant1,2,3,4
  • David Burstein1,6,2,3,4,5
  • Deepika Dayal Mathur1,6,2,3,4,5
  • Chris Chatzinakos7,8
  • Bukola Ajanaku1,2,3,4
  • Fotis Tsetsos1,6,2,3,4
  • Biao Zeng1,2,3,4
66 more authors
  • Sonali Gupta1,2,3,4
  • Rachel Bercovitch1,2,3,4
  • Aram Hong1,2,3,4
  • Clara Casey1,2,3,4
  • Marcela Alvia1,2,3,4
  • Zhiping Shao1,2,3,4
  • Stathis Argyriou1,2,3,4
  • Karen Therrien1,2,3,4
  • Athan Z. Li9,10
  • Chenfeng He11,10
  • Chirag Gupta12,10
  • Christian Porras1,2,3,4
  • Colleen A. McClung13
  • Collin Spencer1,2,3,4
  • Daifeng Wang11,9,10
  • David Alan Bennett14
  • Fotis Tsetsos1,6,2,3,4
  • Gennadi Ryan9,15
  • Hui Yang1,2,3,4
  • Jaroslav Bendl1,2,3,4,5
  • Jennifer Monteiro Fortes1,2,3,4
  • Jerome J. Choi16,10
  • Kalpana Hanthanan Arachchilage11,10
  • Lars J. Jensen12
  • Lisa Laverne Barnes17,18
  • Logan C. Dumitrescu19,20
  • Lyra Sheu1,2,3,4
  • Madeline R. Scott13
  • Marios Anyfantakis1,2,3,4,5
  • Maxim Signaevsky3,4
  • Mikaela Koutrouli1,2,3,4,12
  • Milos Pjanic1,2,3,4
  • Monika Ahirwar21,15
  • Nicolas Y. Masse1,2,3,4
  • Noah Cohen Kalafut9,10
  • Pavan Kumar Auluck22
  • Pavel Katsel3
  • Pengfei Dong1,2,3,4
  • Pramod B. Chandrashekar11,10
  • Sanan Venkatesh1,2,3,4,5
  • Saniya Khullar11,10
  • Sarah R. Murphy1,2,3,4
  • Sayali Anil Alatkar9,10
  • Seon Kinrot1,2,3,4
  • Steven M. Finkbeiner21,23,24,25,15
  • Steven P. Kleopoulos1,2,3,4
  • Tereza Clarence1,2,3,4
  • Timothy J. Hohman19,20

60 listed; 78 in total.

25 affiliations
  1. 1Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
  2. 2Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
  3. 3Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
  4. 4Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
  5. 5Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
  6. 6Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
  7. 7Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
  8. 8Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY, USA
  9. 9Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA
  10. 10Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
  11. 11Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
  12. 12Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
  13. 13Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
  14. 14Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
  15. 15Taube/Koret Center for Neurodegenerative Disease Research, Gladstone Institutes, San Francisco, CA, USA
  16. 16Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, USA
  17. 17Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
  18. 18Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
  19. 19Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
  20. 20Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
  21. 21Center for Systems and Therapeutics, Gladstone Institutes, San Francisco, CA, USA
  22. 22Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
  23. 23Department of Neurology, University of California San Francisco, San Francisco, CA, USA
  24. 24Department of Physiology, University of California San Francisco, San Francisco, CA, USA
  25. 25Neuroscience and Biomedical Sciences Graduate Programs, University of California San Francisco, San Francisco, CA, USA
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Abstract

Common brain disorders impose a substantial health burden, but localizing their genetic risk in the brain remains challenging 1 . Although genome-wide association studies have identified numerous loci associated with neuropsychiatric and neurodegenerative disorders, many of these loci lie in non-coding regions that influence gene expression in specific cell types 2–5 . Traditional bulk brain transcriptomic analyses, which often focus on European ancestry cohorts, average over cellular diversity, obscuring genetic risk-related changes in gene expression. Here we use single-nucleus gene expression profiles from the dorsolateral prefrontal cortex in the multi-ancestry PsychAD cohort to develop transcriptomic imputation models of genetically regulated expression across major brain cell types. Applying these models to neuropsychiatric and neurodegenerative disorders reveals thousands of gene–trait associations that are undetectable in bulk tissue analyses and resolves many signals to discrete neuronal, glial and immune cell populations. Cross-ancestry analyses in the Million Veteran Program confirm these associations, reveal pleiotropic effects of cell-type-specific predicted expression and demonstrate that trait-related dysregulation is conserved across ancestries, enabling mapping of causal genes and pathways. Together, these findings provide a cell-type-resolved and ancestry-aware atlas of genetically regulated expression in the human prefrontal cortex and illustrate how single-nucleus transcriptomics can sharpen gene discovery and therapeutic target prioritization for complex brain disorders.

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Cite

BibTeXRIS
BibTeX
@article{venkatesh2026singlenucleus,
  title = {{Single-nucleus transcriptome-wide association study of human brain disorders}},
  author = {Sanan Venkatesh and Roman Kosoy and Zhenyi Wu and Marios Anyfantakis and Christian Dillard and N. M. Prashant and David Burstein and Deepika Dayal Mathur and Chris Chatzinakos and Bukola Ajanaku and Fotis Tsetsos and Biao Zeng and Sonali Gupta and Rachel Bercovitch and Aram Hong and Clara Casey and Marcela Alvia and Zhiping Shao and Stathis Argyriou and Karen Therrien and Athan Z. Li and Chenfeng He and Chirag Gupta and Christian Porras and Colleen A. McClung and Collin Spencer and Daifeng Wang and David Alan Bennett and Fotis Tsetsos and Gennadi Ryan and Hui Yang and Jaroslav Bendl and Jennifer Monteiro Fortes and Jerome J. Choi and Kalpana Hanthanan Arachchilage and Lars J. Jensen and Lisa Laverne Barnes and Logan C. Dumitrescu and Lyra Sheu and Madeline R. Scott and Marios Anyfantakis and Maxim Signaevsky and Mikaela Koutrouli and Milos Pjanic and Monika Ahirwar and Nicolas Y. Masse and Noah Cohen Kalafut and Pavan Kumar Auluck and Pavel Katsel and Pengfei Dong and Pramod B. Chandrashekar and Sanan Venkatesh and Saniya Khullar and Sarah R. Murphy and Sayali Anil Alatkar and Seon Kinrot and Steven M. Finkbeiner and Steven P. Kleopoulos and Tereza Clarence and Timothy J. Hohman},
  journal = {Nature},
  year = {2026},
  month = sep,
  doi = {10.1038/s41586-026-10836-6},
  url = {https://doi.org/10.1038/s41586-026-10836-6},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Single-nucleus transcriptome-wide association study of human brain disorders
AU  - Sanan Venkatesh
AU  - Roman Kosoy
AU  - Zhenyi Wu
AU  - Marios Anyfantakis
AU  - Christian Dillard
AU  - N. M. Prashant
AU  - David Burstein
AU  - Deepika Dayal Mathur
AU  - Chris Chatzinakos
AU  - Bukola Ajanaku
AU  - Fotis Tsetsos
AU  - Biao Zeng
AU  - Sonali Gupta
AU  - Rachel Bercovitch
AU  - Aram Hong
AU  - Clara Casey
AU  - Marcela Alvia
AU  - Zhiping Shao
AU  - Stathis Argyriou
AU  - Karen Therrien
AU  - Athan Z. Li
AU  - Chenfeng He
AU  - Chirag Gupta
AU  - Christian Porras
AU  - Colleen A. McClung
AU  - Collin Spencer
AU  - Daifeng Wang
AU  - David Alan Bennett
AU  - Fotis Tsetsos
AU  - Gennadi Ryan
AU  - Hui Yang
AU  - Jaroslav Bendl
AU  - Jennifer Monteiro Fortes
AU  - Jerome J. Choi
AU  - Kalpana Hanthanan Arachchilage
AU  - Lars J. Jensen
AU  - Lisa Laverne Barnes
AU  - Logan C. Dumitrescu
AU  - Lyra Sheu
AU  - Madeline R. Scott
AU  - Marios Anyfantakis
AU  - Maxim Signaevsky
AU  - Mikaela Koutrouli
AU  - Milos Pjanic
AU  - Monika Ahirwar
AU  - Nicolas Y. Masse
AU  - Noah Cohen Kalafut
AU  - Pavan Kumar Auluck
AU  - Pavel Katsel
AU  - Pengfei Dong
AU  - Pramod B. Chandrashekar
AU  - Sanan Venkatesh
AU  - Saniya Khullar
AU  - Sarah R. Murphy
AU  - Sayali Anil Alatkar
AU  - Seon Kinrot
AU  - Steven M. Finkbeiner
AU  - Steven P. Kleopoulos
AU  - Tereza Clarence
AU  - Timothy J. Hohman
PY  - 2026
DA  - 2026/09/23
JO  - Nature
DO  - 10.1038/s41586-026-10836-6
UR  - https://doi.org/10.1038/s41586-026-10836-6
AB  - Common brain disorders impose a substantial health burden, but localizing their genetic risk in the brain remains challenging 1 . Although genome-wide association studies have identified numerous loci associated with neuropsychiatric and neurodegenerative disorders, many of these loci lie in non-coding regions that influence gene expression in specific cell types 2–5 . Traditional bulk brain transcriptomic analyses, which often focus on European ancestry cohorts, average over cellular diversity, obscuring genetic risk-related changes in gene expression. Here we use single-nucleus gene expression profiles from the dorsolateral prefrontal cortex in the multi-ancestry PsychAD cohort to develop transcriptomic imputation models of genetically regulated expression across major brain cell types. Applying these models to neuropsychiatric and neurodegenerative disorders reveals thousands of gene–trait associations that are undetectable in bulk tissue analyses and resolves many signals to discrete neuronal, glial and immune cell populations. Cross-ancestry analyses in the Million Veteran Program confirm these associations, reveal pleiotropic effects of cell-type-specific predicted expression and demonstrate that trait-related dysregulation is conserved across ancestries, enabling mapping of causal genes and pathways. Together, these findings provide a cell-type-resolved and ancestry-aware atlas of genetically regulated expression in the human prefrontal cortex and illustrate how single-nucleus transcriptomics can sharpen gene discovery and therapeutic target prioritization for complex brain disorders.
SN  - 0028-0836
SN  - 1476-4687
ER  -