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A single-nuclei paired multiomic analysis of the human midbrain reveals age- and Parkinson’s disease–associated glial changes

Nature Aging volume 4, pages 364–378 (2024)Cite this article

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Abstract

Age is the primary risk factor for Parkinson’s disease (PD), but how aging changes the expression and regulatory landscape of the brain remains unclear. Here we present a single-nuclei multiomic study profiling shared gene expression and chromatin accessibility of young, aged and PD postmortem midbrain samples. Combined multiomic analysis along a pseudopathogenesis trajectory reveals that all glial cell types are affected by age, but microglia and oligodendrocytes are further altered in PD. We present evidence for a disease-associated oligodendrocyte subtype and identify genes lost over the aging and disease process, including CARNS1, that may predispose healthy cells to develop a disease-associated phenotype. Surprisingly, we found that chromatin accessibility changed little over aging or PD within the same cell types. Peak–gene association patterns, however, are substantially altered during aging and PD, identifying cell-type-specific chromosomal loci that contain PD-associated single-nucleotide polymorphisms. Our study suggests a previously undescribed role for oligodendrocytes in aging and PD.

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Fig. 1: Multiomic analysis of human midbrain.
Fig. 2: Analysis of peak–gene connections in the human midbrain.
Fig. 3: Enrichment of PD-associated SNPs in highly accessible open chromatin regions.
Fig. 4: Establishment of pseudopathogenesis trajectory in ODCs.
Fig. 5: Establishment of cPP trajectory in MG.
Fig. 6: Analysis of disease-associated ODCs.
Fig. 7: RNA-FISH of human midbrain samples.

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Data availability

Processed data for the samples presented in this study are available in the Gene Expression Omnibus database under accession number GSE193688. Raw data are available through the dbGaP portal under accession number phs002819.v1.p1. snRNA-seq and ATAC-seq reads were mapped to GRCh38 human reference (https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001405.26/).

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Acknowledgements

The authors gratefully acknowledge the National Institutes of Health (NIH) NeuroBioBank for providing all postmortem brain samples. They also thank A. Knott for language editing. This study was supported by NIH 1R01-NS100919 and 1R01-NS101461 (to Y.-S.K), by startup funds from the Centre de recherche de l’Hôpital Maisonneuve-Rosemont, Université de Montréal (to Y.T), by Fonds de recherche du Québec–Santé (to Y.T) and by a transition grant from the Cole Foundation (to Y.T). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Author notes

  1. These authors contributed equally: Levi Adams, Min Kyung Song.

Authors and Affiliations

  1. RWJMS Institute for Neurological Therapeutics, Rutgers-Robert Wood Johnson Medical School, Piscataway, NJ, USA

    Levi Adams, Min Kyung Song & Yoon-Seong Kim

  2. Department of Biology, Bates College, Lewiston, ME, USA

    Levi Adams

  3. College of Nursing Science, Kyung Hee University, Seoul, Republic of Korea

    Min Kyung Song

  4. Department of Medicine, Maisonneuve-Rosemont Hospital Research Center (CRHMR), University of Montreal, Quebec, QC, Canada

    Samantha Yuen & Yoshiaki Tanaka

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Contributions

L.A. and Y.-S.K. designed the study. Nuclear isolation and library preparation were performed by L.A. and M.S. Computational analysis was performed by Y.T., S.Y. and L.A. L.A., Y.-S.K. and Y.T. wrote the manuscript. All authors contributed to the review and revision of the manuscript.

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Correspondence to Yoshiaki Tanaka or Yoon-Seong Kim.

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Y.T. works as a consultant in Colossal Biosciences. The other authors declare no competing interests.

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Nature Aging thanks Qin Ma and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Multiomic analysis of human midbrain.

a, UMAP visualization of single nuclei by RNA (left) and ATAC (right) profiles. Nuclei are colored by 23 joint clusters. b, Heatmap showing Spearman correlation of average RNA expression (left) and ATAC peaks profiles (right) by cell types for each individual. Top and second color bars represent groups of donors and cell types, respectively. c, Enrichment of motifs in each annotated cell type.

Extended Data Fig. 2 Changes in peak-gene connections in young, aged, and PD for NEAT1 and RASGRF1.

a,b, Venn diagram of the number of associated peaks with NEAT1 (a) and RASGRF1 (b) for young, aged, and PD midbrain. c,d, Heatmap showing enrichment of TF binding motifs in associated peaks with NEAT1 (c) and RASGRF1 (d). e, Comparison of peak-gene association detected in our samples with H3K27ac HiChIP data from the human midbrain (Morabito et al.19) near the FKBP5 locus.

Extended Data Fig. 3 Different distribution of PD-associated SNPs within ATAC peaks across cell types.

a, Number of PD-related SNPs is shown on the ideogram in each cell type. (blue, 1; purple, 2; green, 3; orange, 5; red, 7 SNPs) b, Differential peak-gene associations in astrocytes across PD patients and healthy young and aged donors. Whereas the ATAC peak on the BST1 locus is commonly detected in PD patients and healthy donors, the peak-gene associations are different between PD patients and healthy donors. This ATAC peak contains three PD-related SNPs.

Extended Data Fig. 4 cPP analysis of ODC.

a-c, Dot plot displaying enrichment of gene expression modules for functionally distinct subpopulations for ODC (a), MG (b), and AS (c) clusters in the human midbrain. d, Example genes that have a correlated increase (HSP90AA1) and decrease (CTNNA3) of expression with cPP trajectory. e, Plot of expression of NEAT1 and RASGRF1 across cPP trajectory. NEAT1 expression is correlated with increasing cPP score; RASGRF1 expression is inversely correlated with cPP score (NEAT1: Spearman correlation = 0.314, p < 2.2e-16, RASGRF1: Spearman correlation = −0.110, p < 2.2e-16). Black line indicates loess-smoothed curve, and the gray outline represents 95% CI. f, UMAP of RBFOX1 and OPALIN and their coexpressed genes are mutually exclusive in ODC. g, Expression plot of RBFOX1 and OPALIN across cPP trajectory. n = 15,192 (Young), 11,973 (Aged), and 18,415 (PD). h, Dot plot of gene expression for RBFOX1 and OPALIN in each donor cohort.

Extended Data Fig. 5 Establishment of pseudopathogenesis trajectory in AS.

a, UMAP plot of AS nuclei colored by subclusters b, UMAP plot of AS nuclei colored by young, aged, and PD donor. c, UMAP plot of AS nuclei colored by cPP. d, cPP scores of individual AS nuclei from young, aged, and PD midbrain are significantly changed over aging but not a disease state. (One-way ANOVA with Tukey’s post-hoc analysis, p-value for Y/A = 0.002, p-value for Y/P = 5.28e-4, p-value for A/P = 0.24). p-values are represented as ** p < 0.01 and *** p < 0.001. e, Heatmap showing AS genes correlated with cPP trajectory. X-axis represents individual cells sorted by cPP. Y-axis of heatmap represents positively (upper)- and negatively (bottom)-correlated genes. Representative genes and significant GO terms are shown in the right panel (Spearman correlation > 0.1 or < −0.1).n = 999 (Young), 397 (Aged), and 1,032 (PD). The bottom, center, and top of the box represent 25, 50, and 75 percentile. Whiskers represent 1.5 × IQR. f, Gene expression modules across AS cPP trajectory. Top panel shows individual nuclei AS along with cPP scores and donor group. X-axis shows the cPP score. Y-axis is the combined expression level for all genes in the expression module. Black line indicates loess-smoothed curve, and the gray outline represents 95% CI.

Extended Data Fig. 6 Aging- and disease-specific analysis.

a, Violin plot of cPP score of every individual ODC nuclei by donor. b, Bar graph showing the percentage of nuclei in donor cohort from healthy, intermediate, and disease groups. c, UMAP showing healthy, intermediate, and disease subsets from publicly available snRNA-seq data (Smajić et al, 2022) from the human PD and aged control midbrain after pseudopathogenesis analysis. d, Dot plots of genes from the same dataset (Smajić et al, 2022) showing similar expression patterns among healthy, intermediate, and disease subsets as our multiomic dataset. Circle size represents relative gene expression to healthy subsets. e,f, Representative peak-gene connection plots for peaks containing PD-associated SNPs that have decreased (e) or increased (f) gene connections in disease-associated ODC compared to healthy ones. Motif information was obtained from the JASPAR Transcription Factors track in the UCSC genome browser. SNPs associated with each peak are shown below.

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Adams, L., Song, M.K., Yuen, S. et al. A single-nuclei paired multiomic analysis of the human midbrain reveals age- and Parkinson’s disease–associated glial changes. Nat Aging 4, 364–378 (2024). https://doi.org/10.1038/s43587-024-00583-6

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