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Analysis of the caudate nucleus transcriptome in individuals with schizophrenia highlights effects of antipsychotics and new risk genes

Nature Neuroscience volume 25, pages 1559–1568 (2022)Cite this article

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Abstract

Most studies of gene expression in the brains of individuals with schizophrenia have focused on cortical regions, but subcortical nuclei such as the striatum are prominently implicated in the disease, and current antipsychotic drugs target the striatum’s dense dopaminergic innervation. Here, we performed a comprehensive analysis of the genetic and transcriptional landscape of schizophrenia in the postmortem caudate nucleus of the striatum of 443 individuals (245 neurotypical individuals, 154 individuals with schizophrenia and 44 individuals with bipolar disorder), 210 from African and 233 from European ancestries. Integrating expression quantitative trait loci analysis, Mendelian randomization with the latest schizophrenia genome-wide association study, transcriptome-wide association study and differential expression analysis, we identified many genes associated with schizophrenia risk, including potentially the dopamine D2 receptor short isoform. We found that antipsychotic medication has an extensive influence on caudate gene expression. We constructed caudate nucleus gene expression networks that highlight interactions involving schizophrenia risk. These analyses provide a resource for the study of schizophrenia and insights into risk mechanisms and potential therapeutic targets.

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Fig. 1: Overview of computational analysis.
Fig. 2: Genetic regulation of expression in the caudate nucleus.
Fig. 3: Integration of eQTL and schizophrenia GWAS in caudate identifies new genes associated with schizophrenia risk.
Fig. 4: Widespread upregulation of neuronal signaling and downregulation of neural differentiation and development in the schizophrenia caudate nucleus.
Fig. 5: Inferring a caudate nucleus gene coexpression network with deep neural networks.

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Data availability

Processed data (Supplementary Data 1–13 and additional data files) and accession codes to raw RNA-Seq FASTQ files and genotypes used in this study are available from https://erwinpaquolalab.libd.org/caudate_eqtl/. Additional data files include Brainseq_caudate_4features_mash_associations.tar.gz (full set of transancestry caudate eQTL mash model results) and Brainseq_LIBD_brainregions_allpairs_genes.txt.gz (full set of brain region interaction eQTL mash model results).

Code availability

Code and jupyter notebooks are available through GitHub at https://github.com/LieberInstitute/BrainSeqPhase3Caudate.

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Acknowledgements

We thank the Offices of the Chief Medical Examiner of Washington, DC, Northern Virginia, and Maryland for the provision of brain tissue used in this study. We also thank L.B. Bigelow and members of the LIBD Neuropathology Section for their work in assembling and curating the clinical and demographic information and organizing the Human Brain Tissue Repository of the Lieber Institute. Finally, we thank the families that have donated this tissue to advance our understanding of psychiatric disorders. This work is supported by the LIBD, the BrainSeq Consortium, the NIH T32 fellowship (T32MH015330) to K.J.M.B, NIH R01 (MH123183) to L.A.H and L.C.-T. and an NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation to J.A.E.

Author information

Authors and Affiliations

  1. Lieber Institute for Brain Development, Baltimore, MD, USA

    Kynon J. M. Benjamin, Qiang Chen, Andrew E. Jaffe, Joshua M. Stolz, Leonardo Collado-Torres, Louise A. Huuki-Myers, Emily E. Burke, Ria Arora, Arthur S. Feltrin, André Rocha Barbosa, Eugenia Radulescu, Giulio Pergola, Joo Heon Shin, William S. Ulrich, Amy Deep-Soboslay, Ran Tao, Joo Heon Shin, Andrew E. Jaffe, Rujuta Narurkar, Richard E. Straub, Thomas M. Hyde, Joel E. Kleinman, Daniel R. Weinberger, Thomas M. Hyde, Joel E. Kleinman, Jennifer A. Erwin, Daniel R. Weinberger & Apuã C. M. Paquola

  2. Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Kynon J. M. Benjamin, Qiang Chen, Andrew E. Jaffe, Joel E. Kleinman, Jennifer A. Erwin & Daniel R. Weinberger

  3. Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Kynon J. M. Benjamin, Joo Heon Shin, Thomas M. Hyde, Jennifer A. Erwin, Daniel R. Weinberger & Apuã C. M. Paquola

  4. Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Andrew E. Jaffe, Thomas M. Hyde, Jennifer A. Erwin & Daniel R. Weinberger

  5. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Andrew E. Jaffe & Daniel R. Weinberger

  6. Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Andrew E. Jaffe

  7. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Andrew E. Jaffe

  8. Neumora Therapeutics, Watertown, MA, USA

    Andrew E. Jaffe

  9. Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA

    Leonardo Collado-Torres

  10. Center for Mathematics, Computation and Cognition, Federal University of ABC, Santo André, Brazil

    Arthur S. Feltrin

  11. Inter-Institutional Graduate Program on Bioinformatics, University of São Paulo, São Paulo, Brazil

    André Rocha Barbosa

  12. Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil

    André Rocha Barbosa

  13. Astellas Pharma, Northbrook, IL, USA

    Mitsuyuki Matsumoto, Takeshi Saito, Katsunori Tajinda & Daniel J. Hoeppner

  14. Eli Lilly and Company, Global, Indianapolis, IN, USA

    David A. Collier & Bradley B. Miller

  15. UCB Pharma, Slough, UK

    Karim Malki

  16. Janssen Research & Development LLC, Raritan, NJ, USA

    Maura Furey, Derrek Hibar & Hartmuth Kolb

  17. Johnson and Johnson, Global, New Brunswick, NJ, USA

    Maura Furey, Derrek Hibar & Hartmuth Kolb

  18. H. Lundbeck A/S, Copenhagen, Denmark

    Michael Didriksen & Lasse Folkersen

  19. F. Hoffmann-La Roche, Global, Basel, Switzerland

    Tony Kam-Thong & Dheeraj Malhotra

Authors
  1. Kynon J. M. Benjamin
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  21. Apuã C. M. Paquola
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Consortia

the BrainSeq Consortium

  • Mitsuyuki Matsumoto
  • , Takeshi Saito
  • , Katsunori Tajinda
  • , Daniel J. Hoeppner
  • , David A. Collier
  • , Karim Malki
  • , Bradley B. Miller
  • , Maura Furey
  • , Derrek Hibar
  • , Hartmuth Kolb
  • , Michael Didriksen
  • , Lasse Folkersen
  • , Tony Kam-Thong
  • , Dheeraj Malhotra
  • , Joo Heon Shin
  • , Andrew E. Jaffe
  • , Rujuta Narurkar
  • , Richard E. Straub
  • , Amy Deep-Soboslay
  • , Thomas M. Hyde
  • , Joel E. Kleinman
  •  & Daniel R. Weinberger

Contributions

K.J.M.B., J.A.E., D.R.W. and A.C.M.P. designed the study. K.J.M.B.and A.C.M.P. performed main data analysis and interpretation and led the writing of the manuscript. Q.C. performed SMR analysis and interpretation. J.H.S. and R.T. performed RNA sequencing data generation (RNA extraction, library preparation and sequencing) and QC analyses. A.E.J., L.C.-T., J.M.S. and E.E.B. performed data processing of RNA sequencing and genotypes. L.A.H.-M. and L.C.-T. performed cell type deconvolution analysis and interpretation. K.J.M.B., A.S.F., A.R.B., E.R., G.P. and A.C.M.P. performed gene network analysis and interpretation. R.A. contributed to differential expression analysis and interpretation. A.C.M.P. conceived and developed GNVAE. W.S.U. created the user-friendly database and website for eQTL visualization. A.E.J., L.C.-T. and the BrainSeq Consortium provided feedback on the manuscript and contributed to the interpretation of results. A.D.-S. obtained consent from and clinically characterized human brain donors. T.M.H. and J.E.K. obtained consent from donors, curated medical data, collected, characterized and dissected human brain tissue and contributed to the design of the study. K.J.M.B., J.A.E., D.R.W. and A.C.M.P. wrote the manuscript. J.A.E., D.R.W. and A.C.M.P. supervised the study.

Corresponding authors

Correspondence to Jennifer A. Erwin, Daniel R. Weinberger or Apuã C. M. Paquola.

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Competing interests

The following BrainSeq Consortium members have competing interests. M.M., T.S., K.T. and D.J.H. are employees of Astellas Pharma. D.A.C. and B.B.M. are employees of Eli Lilly and Company. K.M. is an employee of UCB Pharma and past employee of Eli Lilly and Company. M.F., D.H. and H.K. are employees of Janssen Research & Development LLC and Johnson and Johnson. M.D. and L.F. are employees of H. Lundbeck A/S. T.K.-T. and D.M. are employees of F. Hoffmann-La Roche. The primary role of these BrainSeq Consortium members was study conceptualization, project administration and funding acquisition. The remaining authors declare no competing interests.

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Supplementary information

Supplementary Information

Legends for Supplementary Data 1–13, Supplementary Figs. 1–32 and Tables 1–8.

Reporting Summary

Supplementary Data 1

Excel file with quality control metrics (RIN, percent alignment and rRNA mapping rate) across BrainSeq brain regions with total RNA RNA-sequencing (caudate, DLPFC and hippocampus), CommonMind DLPFC and GTEx brain regions.

Supplementary Data 2

Compressed tar-zipped directory containing compressed text files for mash model results for the brain region interaction meta-analysis for all eFeatures (gene, transcript, exon and junction) containing mash results of strong signals (top variants).

Supplementary Data 3

Compressed tar-zipped directory containing fastENLOC results for schizophrenia GWAS (PGC2 + CLOZUK and PGC3).

Supplementary Data 4

Compressed tar-zipped directory containing compressed text files with SMR significant results (SMR FDR < 0.05 and HEIDI P > 0.01) for genes, transcripts, exons and junctions. Additionally, GTEx caudate replication results are in this compressed directory.

Supplementary Data 5

Compressed text file of TWAS results in EA for the caudate nucleus with the latest schizophrenia GWAS (PGC3) across all features.

Supplementary Data 6

Text file of caudate TWAS genes overlapping PGC3-prioritized genes.

Supplementary Data 7

Text file of TWAS genes summarized across caudate nucleus, DLPFC and hippocampus in EA using PGC2 + CLOZUK schizophrenia GWAS.

Supplementary Data 8

Compressed text file of differential expression results for the caudate nucleus of schizophrenia versus neurotypical individuals across all features.

Supplementary Data 9

Excel file of discordant differential expressed genes for schizophrenia comparing the caudate nucleus with DLPFC and hippocampus.

Supplementary Data 10

Text file of demographic information for caudate nucleus samples.

Supplementary Data 11

Compressed text file of differential expression results for the caudate nucleus of schizophrenia with and without antipsychotics present at time of death versus neurotypical individuals across all features (gene, transcript, exon and junction)

Supplementary Data 12

Compressed tar-zipped directory containing GNVAE output: table of latent variables for all genes, module membership tables, GO enrichment analysis tables and GO word clouds.

Supplementary Data 13

Compressed tar-zipped directory containing WGCNA output: eigengenes, module membership tables and GO enrichment analysis tables.

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Benjamin, K.J.M., Chen, Q., Jaffe, A.E. et al. Analysis of the caudate nucleus transcriptome in individuals with schizophrenia highlights effects of antipsychotics and new risk genes. Nat Neurosci 25, 1559–1568 (2022). https://doi.org/10.1038/s41593-022-01182-7

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