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Human early-onset dementia caused by DAP12 deficiency reveals a unique signature of dysregulated microglia

Nature Immunology volume 24, pages 545–557 (2023)Cite this article

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A Publisher Correction to this article was published on 20 February 2023

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Abstract

The TREM2–DAP12 receptor complex sustains microglia functions. Heterozygous hypofunctional TREM2 variants impair microglia, accelerating late-onset Alzheimer’s disease. Homozygous inactivating variants of TREM2 or TYROBP-encoding DAP12 cause Nasu–Hakola disease (NHD), an early-onset dementia characterized by cerebral atrophy, myelin loss and gliosis. Mechanisms underpinning NHD are unknown. Here, single-nucleus RNA-sequencing analysis of brain specimens from DAP12-deficient NHD individuals revealed a unique microglia signature indicating heightened RUNX1, STAT3 and transforming growth factor-β signaling pathways that mediate repair responses to injuries. This profile correlated with a wound healing signature in astrocytes and impaired myelination in oligodendrocytes, while pericyte profiles indicated vascular abnormalities. Conversely, single-nuclei signatures in mice lacking DAP12 signaling reflected very mild microglial defects that did not recapitulate NHD. We envision that DAP12 signaling in microglia attenuates wound healing pathways that, if left unchecked, interfere with microglial physiological functions, causing pathology in human. The identification of a dysregulated NHD microglia signature sparks potential therapeutic strategies aimed at resetting microglia signaling pathways.

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Fig. 1: NHD microglia show a unique signature.
Fig. 2: The NHD microglia signature in part overlaps with the IL-10-primed macrophage signature.
Fig. 3: The NHD pericyte signature indicates vascular abnormalities.
Fig. 4: NHD astrocyte signatures reflect a wound healing response.
Fig. 5: The microglia profile of aged KΔ75 mice is distinct from that of NHD.
Fig. 6: KΔ75 mice exhibit mild oligodendrocyte and astrocyte defects.

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Data availability

snRNA-seq differential expression gene lists with statistics are available in Supplementary Tables 3 and 6. All requests for human snRNA-seq data are promptly reviewed by the Brain Research Institute at Niigata University and Mihara Memorial Hospital (Isesaki, Japan) to verify if the request is subject to any intellectual property or confidentiality obligations. Human-related data not included in the paper were generated as part of clinical trials and may be subject to patient confidentiality. Any data and materials that can be shared will be released via a material transfer agreement. Raw and processed mouse and human snRNA-seq data have been deposited to the Gene Expression Omnibus (GEO) database under accession number GSE190015. Processed data, UMAP coordinates and annotations for the human NHD snRNA-seq have also been made freely available to download and visualize at the University of California Santa Cruz Cell Browser (https://nhd-brain.cells.ucsc.edu). scRNA-seq and microarray data on macrophage polarization were downloaded from GEO under accession numbers GSE199378 and GSE61298, respectively. Please contact the corresponding authors for additional information. Source data for Figs. 2, 4, 5 and 6 are provided with the paper.

Code availability

All software used in this study is published and cited either in the main text or Methods. No custom code was used for data processing or analysis. All the code used in the analysis for NHD snRNA-seq data can be found at https://github.com/yingyue-zhou/NHD_snRNA.

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Acknowledgements

We thank E. Vivier (Aix Marseille Université) and W. M. Yokoyama (Washington University in St. Louis) for providing the KΔ75 mice, R. Cho (Cell Signaling Technology) for kindly providing STAT3 and pSTAT3 antibodies, L. L. Lanier (University of California at San Francisco) for providing DAP12 antibody, V. Peng and M. Terekhova for advice on bioinformatic analyses, S. Brioschi for great scientific discussions and M. Tano for technical help. M. Tada was supported by the Japan Society for the Promotion of Science (JSPS, KAKENHI, 22H02995). A.K. was supported by the Strategic Research Program for Brain Sciences from the Japan Agency for Medical Research and Development (AMED, JP21wm0425019) and the Collaborative Research Project of the Brain Research Institute, Niigata University, Japan. M. Takao was supported by AMED (JP21wm0425019). M.C. was supported by the NIH (RF1 AG051485, R21 AG077244, P01 AG078106 and RF1 AG059082) Cure Alzheimer’s Fund, Fred and Ginger Haberle Charitable Fund at East Texas Communities Foundation and Centene.

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  1. Kelly R. Miller

    Present address: Deepcell, Menlo Park, CA, USA

Authors and Affiliations

  1. Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA

    Yingyue Zhou, Zhangying Cai, Prabhakar S. Andhey, Amanda Swain, Susan Gilfillan, Maxim N. Artyomov & Marco Colonna

  2. Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan

    Mari Tada & Akiyoshi Kakita

  3. 10x Genomics, Pleasanton, CA, USA

    Kelly R. Miller

  4. Department of Clinical Laboratory and Internal Medicine, National Center of Neurology and Psychiatry (NCNP), National Center Hospital, Tokyo, Japan

    Masaki Takao

  5. Department of Brain Bank, Mihara Memorial Hospital, Isesaki, Japan

    Masaki Takao

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Contributions

Y.Z. and M.C. designed the study and interpreted the results. Y.Z. performed computational analyses. M. Tada performed IHC and IF staining in human sections. Y.Z. and Z.C. performed validation experiments. Y.Z. and A.S. prepared single-nuclei suspension samples. K.R.M. helped with single-cell technology. S.G. bred all mice. M. Tada, M. Takao and A.K. provided human postmortem brain samples and clinical advice. P.S.A. and M.N.A. provided guidance for computational analyses. Y.Z. and M.C. wrote the manuscript with feedback from all authors.

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Correspondence to Marco Colonna.

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M.C. is a member of the Vigil Neuro scientific advisory board (SAB), is a consultant for Cell Signaling Technology, has received research grants from Vigil Neuro during the conduct of the study and has a patent to TREM2 pending. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Cluster characterization of NHD and control samples.

a, UMAP plots of NHD and control samples before (left) and after (right) batch correction by Harmony. n = 66,324 total nuclei; n = 11 healthy individuals and n = 3 individuals with NHD. b, Bar graphs of total nuclei number, median of number of genes and median of number of UMIs of each sample sequenced. c, Heatmap showing cell type markers. d, Nuclei frequency of all cell types in each sample.

Extended Data Fig. 2 Characterization of NHD microglia subclusters.

a, Pathways enriched in genes upregulated in NHD microglia compared to controls, using GSEA analysis (left, q value by FDR adjustment) or Metascape analysis (right, P value by hypergeometric distribution). b, PCA plot of NHD and control microglia demarcated by sex. c, Average expression of top DEGs [log2(Fold Change) > 0.5, FDR-adjusted P < 0.05, two-part, generalized linear model] upregulated in NHD microglia plotted against age at death. Trend line calculated for control samples only.

Extended Data Fig. 3 NHD microglia signature overlaps with IL-10-induced macrophage signature.

a, UMAP plot of human monocyte-derived macrophages stimulated with cocktails of LPS + IFNγ, IL-4 + IL-13 or IL-10 from GSE199378, designated by treatment. b, Venn diagram showing little overlap among signatures of polarized macrophages. c-e, Violin plot showing gene set scores (by UCell) of the designated macrophage polarization signatures (top 100 genes upregulated under each condition) in the macrophage polarization dataset; c, LPS + IFNγ polarization, n = 8,232 nuclei; d, IL-4 + IL-13 polarization, n = 6,741 nuclei; e, IL-10 polarization, n = 6,890 nuclei. Box center lines, bounds of box, and whiskers indicate median, first and third quartiles, and minima and maxima within 1.5X IQR, respectively. P value by two-sided Wilcoxon Rank Sum test. f-h, GSEA plots showing enrichment of NHD microglia signature in signatures of polarized macrophages stimulated by LPS and IFNγ (f), IL-4 (g) and IL-10 (h) from GSE6129828. P values by permutation. NES, normalized enrichment score. i, Histogram of phospho-STAT3 (pSTAT3) staining of bone marrow derived macrophages (BMDMs) from WT and DAP12 KΔ75 mice, stimulated with 0 ng/ml or 20 ng/ml IL-10 for 15 min after starvation overnight. Data are representative of two independent experiments. j, Quantification of pSTAT3 mean fluorescence intensity (MFI) in i. P value by two-way ANOVA. Data are presented as mean ± s.e.m. n = 3 independent cell culture wells per genotype per experiment; n = two independent experiments. k, Histogram of total STAT3 staining in BMDM from WT and DAP12 KΔ75 mice, treated as in i. Data are representative of two independent experiments. l, Quantification of STAT3 mean fluorescence intensity in k. P value by two-way ANOVA. Data are presented as mean ± s.e.m. n = 3 independent cell culture wells per genotype per experiment; n = two independent experiments. m, Gating strategy for BMDMs from WT and KΔ75 mice. Numbers indicate the percentage of cells within the gate.

Extended Data Fig. 4 The NHD endothelial cell signature shows altered function.

a, Volcano plot depicting genes differentially expressed (log2(Fold Change) > 0.25, FDR-adjusted P < 0.05, two-part, generalized linear model) in NHD versus control endothelial cells. b, Box plots showing average individual expression levels for selected DEGs in endothelial cells. Box center lines, bounds of box, and whiskers indicate median, first and third quartiles, and minima and maxima within 1.5X IQR, respectively. P values by two-sided Wilcoxon Rank Sum test. n = 11 healthy individuals and n = 3 individuals with NHD. c, Heatmap showing average gene expression of top DEGs in endothelial cells per sample.

Extended Data Fig. 5 Comparison of NHD astrocyte and oligodendrocyte signatures with those in other neurodegenerative diseases.

a, b, Venn diagram revealing overlapping genes commonly upregulated in NHD astrocytes and two human AD datasets (a), and in NHD astrocytes and AIMS (astrocytes inflamed in MS) (b). c, Dot plot showing marker genes for each oligodendrocyte subcluster. d, Volcano plot depicting genes differentially expressed in NHD and control oligodendrocytes (log2(fold change) > 0.25, FDR-adjusted P < 0.05, two-part, generalized linear model). e, Box plots showing average of individual levels of expression for selected genes upregulated in NHD oligodendrocytes. Box center lines, bounds of box, and whiskers indicate median, first and third quartiles, and minima and maxima within 1.5X IQR, respectively. P values by two-sided Wilcoxon rank-sum test. n = 11 healthy individuals and n = 3 individuals with NHD. f, Heatmap showing average gene expression of top DEGs (log2(fold change) > 0.25, FDR-adjusted P < 0.05, two-part, generalized linear model) in oligodendrocytes from each sample. g, Pathways enriched in genes upregulated in NHD oligodendrocytes. P values calculated based on the cumulative hypergeometric distribution. h, i, Venn diagram revealing genes differentially expressed in NHD oligodendrocytes as well as in two human MS datasets. h, upregulated genes. i, downregulated genes.

Extended Data Fig. 6 NHD neurons present signatures of diminished activity.

a, UMAP plot of neuron sub-clustering. n = 36,336 total neuronal nuclei; n = 11 healthy individuals and n = 3 individuals with NHD. Ex, excitatory neurons; In, inhibitory neurons. b, Nuclei frequency of neuronal subclusters in each sample. c, Number of upregulated (up) and downregulated (down) genes differentially expressed in (log2(fold change) > 0.5, FDR-adjusted P < 0.05, two-part, generalized linear model) NHD and controls in each neuronal subcluster. d,e, Pathways enriched in genes downregulated in NHD in excitatory neurons (d) or inhibitory neurons (e). P values calculated based on the cumulative hypergeometric distribution. f, Violin plots showing percentage of reads that map to ribosomal genes split by disease condition. Differences between NHD and controls in all subclusters are significant by two-sided Wilcoxon Rank Sum test. Each dot represents the mean ± s.d. A full list of P values and number of nuclei is given in Supplementary Table 2. g, Heatmap showing average expression of genes in synaptic vesicle endocytosis pathway per condition per cluster.

Extended Data Fig. 7 Cluster characterization of 2-year-old KΔ75 and WT cortical samples.

a, Bar graphs of total nuclei number, median of number of genes and median of number of UMIs of each sample sequenced. b, UMAP plot of 2-year-old KΔ75 and WT cortical samples grouped by clusters, which were manually assigned to each cell type. n = 60,851 total nuclei; n = 4 animals per genotype. c, UMAP plots showing expression of cluster markers. d, Nuclei distribution of all samples in each cluster. e, UMAP plot of all nuclei from KΔ75 and WT samples. n = 26,492 WT nuclei and n = 34,359 KΔ75 nuclei; n = 4 animals per genotype.

Extended Data Fig. 8 KΔ75 microglia sub-clustering in detail.

a, UMAP plot showing expression of Tyrobp in myeloid clusters. b, Venn diagram highlighting similarities between IFN-R and the interferon responsive signature from ref. 45. Overlapping genes are shown in the box. c, Scatter plot depicting differential cell type abundance calculated by MASC. Data are represented as the MASC OR of a nucleus being in that cluster for WT versus KΔ75 (with 95% CI), against the -log(P value) of the association. Center of bar corresponds to OR. Red labeled cluster was significant with FDR-adjusted P value < 0.05 using Benjamini-Hochberg correction. A full list of P values and number of nuclei is provided in Supplementary Table 5. d, Donut plots showing nuclei contribution from each sample to each myeloid subcluster. Numbers represent the percentage of nuclei from each sample within the designated subcluster. e, Volcano plot showing DEGs (log2(fold change) > 0.5, adjusted P < 0.05, two-sided Wilcoxon Rank Sum test, Bonferroni correction) within the HM cluster from KΔ75 and WT mice. f, Heatmap showing average gene expression of top DEGs from e in HM cluster. g, Pathways enriched in genes downregulated in KΔ75 HM vs. WT HM. q values calculated based on Benjamini-Hochberg.

Extended Data Fig. 9 KΔ75 oligodendrocyte and astrocyte sub-clustering in detail.

a, UMAP plots showing cluster marker expression in each oligodendrocyte sub-cluster. b, Violin plots showing expression of reactive oligodendrocyte genes in each sub-cluster. c, Violin plots showing expression of reactive oligodendrocyte genes in the ROL clusters from KΔ75 and WT mice. d, Violin plots showing the DOL signature score (by UCell) in each oligodendrocyte sub-cluster. DOL signature was extracted from ref. 50. Box center lines, bounds of box, and whiskers indicate median, first and third quartiles, and minima and maxima within 1.5X IQR, respectively. P values by two-sided Wilcoxon Rank Sum test. n = 8,398 MFOL, 1,643 OPC, 754 MOL, 74 COP and 51 ROL nuclei. e, Violin plots showing DOL signature score (by UCell) in ROL from KΔ75 and WT mice. f, Representative IF images of MBP (red) in corpus callosum of 2-year-old WT and KΔ75 mice. Scale bar, 30 μm. g, Quantification of MBP intensity in f. P value by two-tailed unpaired t test. Bars at mean. n = 4 WT and n = 3 KΔ75 mice. h, UMAP plot showing expression of Vim and Gfap in astrocyte subcultures. i, Violin plots showing expression of reactive astrocyte genes in each sub-cluster. j, Pathways enriched in astrocyte cluster 8 marker genes. q-values calculated based on Benjamini-Hochberg. k, UMAP plot showing expression of Crym in astrocyte subclusters.

Extended Data Fig. 10 Transcriptional profiles of KΔ75 and WT neurons are similar.

a, UMAP plot of neuron sub-clustering. n = 40,657 total neuronal nuclei; n = 4 animals per genotype. b, UMAP plot showing expression of Slc17a7 and Gad1. c, UMAP plot of neuron subclustering grouped by excitatory neurons (Ex_neuron) and inhibitory neurons (In_neuron). d, Number of upregulated (up) and downregulated (down) DEGs (log2(fold change) > 0.5, adjusted P < 0.05, non-parametric two-sided Wilcoxon rank sum test, Bonferroni correction) in excitatory and inhibitory neurons in KΔ75 versus WT mice. e, Model of NHD pathogenesis. A genetic defect in DAP12 or TREM2 leads to imbalance between TREM2/DAP12 signaling pathway and pathways driven by STAT3, RUNX1 and TGFβ in microglia. This imbalance results in demyelination through unknown mechanisms, which may include dysregulated phagocytosis and secretion of cytokines. Accumulation of myelin and cellular debris leads to progressive and extensive tissue damage that includes astrocytosis, oligodendrocyte malfunction and dysfunctional vasculature, which further activates microglia. In addition, perivascular macrophages may directly alter vascular function, leading to its dysregulation. Created with BioRender.com.

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Zhou, Y., Tada, M., Cai, Z. et al. Human early-onset dementia caused by DAP12 deficiency reveals a unique signature of dysregulated microglia. Nat Immunol 24, 545–557 (2023). https://doi.org/10.1038/s41590-022-01403-y

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