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Profiling gene expression in the human dentate gyrus granule cell layer reveals insights into schizophrenia and its genetic risk

Nature Neuroscience volume 23, pages 510–519 (2020)Cite this article

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Abstract

Specific cell populations may have unique contributions to schizophrenia but may be missed in studies of homogenate tissue. Here laser capture microdissection followed by RNA sequencing (LCM-seq) was used to transcriptomically profile the granule cell layer of the dentate gyrus (DG-GCL) in human hippocampus and contrast these data to those obtained from bulk hippocampal homogenate. We identified widespread cell-type-enriched aging and genetic effects in the DG-GCL that were either absent or directionally discordant in bulk hippocampus data. Of the ~9 million expression quantitative trait loci identified in the DG-GCL, 15% were not detected in bulk hippocampus, including 15 schizophrenia risk variants. We created transcriptome-wide association study genetic weights from the DG-GCL, which identified many schizophrenia-associated genetic signals not found in transcriptome-wide association studies from bulk hippocampus, including GRM3 and CACNA1C. These results highlight the improved biological resolution provided by targeted sampling strategies like LCM and complement homogenate and single-nucleus approaches in human brain.

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Fig. 1: LCM-seq confirms expected strong cell type enrichment in DG-GCL.
Fig. 2: Cell-type-specific changes in gene expression associated with aging.
Fig. 3: Extensive DG-GCL-enriched eQTLs.
Fig. 4: Schizophrenia risk eQTLs reveal feature associations in DG-GCL not seen in homogenate hippocampus.

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Data availability

Raw sequencing reads are available through SRA accession code SRP241159 and BioProject accession code PRJNA600414. Processed data are available at our website: http://research.libd.org/dg_hippo_paper/data.html.

Code availability

Code is available at https://github.com/lieberinstitute/dg_hippo_paper, archived via Zenodo at https://doi.org/10.5281/zenodo.3605718.

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Acknowledgements

We would like to express our gratitude to our colleagues whose tireless efforts have led to the donation of postmortem tissue to advance these studies: the Office of the Chief Medical Examiner of the District of Columbia, the Office of the Chief Medical Examiner for Northern Virginia, Fairfax, Virginia, and the Office of the Chief Medical Examiner of the State of Maryland, Baltimore, Maryland. We also would like to acknowledge the contributions of L.B. Bigelow for his diagnostic expertise. Finally, we are indebted to the generosity of the families of the decedents, who donated the brain tissue used in these studies.

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  1. These authors contributed equally: A. E. Jaffe, D. J. Hoeppner.

Authors and Affiliations

  1. Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA

    Andrew E. Jaffe, Daniel J. Hoeppner, Lou Blanpain, Joy Ukaigwe, Emily E. Burke, Leonardo Collado-Torres, Ran Tao, Kristen R. Maynard, Matthew N. Tran, Keri Martinowich, Amy Deep-Soboslay, Joo Heon Shin, Joel E. Kleinman, Daniel R. Weinberger & Thomas M. Hyde

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

    Andrew E. Jaffe

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

    Andrew E. Jaffe

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

    Andrew E. Jaffe & Daniel R. Weinberger

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

    Andrew E. Jaffe, Keri Martinowich & Daniel R. Weinberger

  6. Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Andrew E. Jaffe, Keri Martinowich, Joel E. Kleinman, Daniel R. Weinberger & Thomas M. Hyde

  7. Neuroscience, La Jolla Laboratory, Astellas Research Institute of America, San Diego, CA, USA

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

  8. Virtual Venture Unit, Psychiatry, Drug Discovery Research, Astellas Pharma, Tsukuba, Japan

    Daniel J. Hoeppner & Mitsuyuki Matsumoto

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

    Daniel R. Weinberger & Thomas M. Hyde

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Contributions

A.E.J. performed data processing and analysis and wrote the manuscript. D.J.H., R.T., K.T., M.N.T., K.R.M., K.M., J.H.S., A.D.S. and J.E.K. performed data collection and generation. T.S., E.E.B. and L.C.T. performed data analysis. L.B. and J.U. performed data generation and analysis. D.R.W. performed data interpretation and contributed to the writing of the manuscript. M.M. and T.M.H. supervised data collection and generation and contributed to writing the manuscript.

Corresponding authors

Correspondence to Andrew E. Jaffe, Mitsuyuki Matsumoto or Thomas M. Hyde.

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Competing interests

D.J.H., T.S., K.T. and M.M. are employees and stockholders of Astellas Pharma. No other authors have competing interests.

Additional information

Peer review information Nature Neuroscience thanks Nenad Sestan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 LCM of granule cell layer from human postmortem dentate gyrus.

a, Cresyl violet stain before and (B) after -LCM. The difference indicates the captured granule cell layer.

Extended Data Fig. 2 Quality control metrics across the DG-GCL and bulk hippocampus.

a, mitochondrial chromosome mapping rate, b, overall mapping rate, c, exonic mapping (also known as gene assignment rate) and d, RNA Integrity number (RIN) compared between Hippocampus and DG-GCL. Colors indicate two different RiboZero library preparation kits: RiboZero Gold and RiboZero HMR (Human-Mouse-Rat).

Extended Data Fig. 3 Principal component analyses (PCA) of various subsets of data.

a, PCA on 224 subjects with data on both HIPPO (red) and DG-GCL (blue). Grey lines connect data from the same donors. b, PCA on 596 subjects used in age, eQTL and diagnosis analyses. c, PCA on 263 DG-GCL samples (blue circles) with HIPPO samples (red squares) projected into component space. d, PCA on the 333 HIPPO samples (red circles) with 263 DG-GCL samples (blue squares) projected into this component space.

Extended Data Fig. 4 Transcript-level overlap of eQTL signal.

Venn diagram displays how eFeatures are mapped to Gencode-annotated transcripts.

Extended Data Fig. 5 Additional DG-GCL eQTL characterizations.

eQTL directional consistency collections between eQTL statistics calculated in HIPPO and DG-GCL, stratified by a, feature type, and then categories related to the b, number of eSNPs and c, statistical significance. d, Local cis heritability differences comparing DG-GCL and DLPFC (which complements Fig. 3b, c).

Extended Data Fig. 6 DG-GCL eQTLs among schizophrenia risk SNPs.

a, Feature-level support for PGC-associated index SNPs in DG-GCL dataset and (B) the number of significant index SNPs as eQTLs (at FDR < 5%) in three brain datasets.

Extended Data Fig. 7 Cross-dataset TWAS analyses.

a, TWAS Z scores across three datasets are highly correlated. Correlations were highest between DLPFC and HIPPO (ρ = 0.64), followed by DG-GCL and HIPPO (ρ = 0.53) then DG-GCL and DLPFC (ρ = 0.50). Overlap of TWAS gene-level associations across three datasets at b, FDR < 5% significance and c, Bonferroni < 10% significance.

Extended Data Fig. 8 Case-control differential expression analyses.

a, Comparisons of log2 fold change effect sizes across diagnoses in the DG-GCL dataset. Comparison of the schizophrenia b, log2 fold changes and c, T-statistics for DG-GCL versus bulk Hippocampus. Color indicates FDR < 0.05 significance indicated in the legend. d, TWAS versus differential expression for schizophrenia effects among 12256 expressed genes with positive heritability (N = 12256) shows no association.

Extended Data Fig. 9 tSNE plot of hippocampus snRNA-seq data.

Shown is a tSNE plot of snRNA-seq data from 4,127 nuclei from bulk hippocampus, colored by data-driven cell types.

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Jaffe, A.E., Hoeppner, D.J., Saito, T. et al. Profiling gene expression in the human dentate gyrus granule cell layer reveals insights into schizophrenia and its genetic risk. Nat Neurosci 23, 510–519 (2020). https://doi.org/10.1038/s41593-020-0604-z

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