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Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease

An Author Correction to this article was published on 14 May 2020

This article has been updated

Abstract

Glia have been implicated in Alzheimer’s disease (AD) pathogenesis. Variants of the microglia receptor triggering receptor expressed on myeloid cells 2 (TREM2) increase AD risk, and activation of disease-associated microglia (DAM) is dependent on TREM2 in mouse models of AD. We surveyed gene-expression changes associated with AD pathology and TREM2 in 5XFAD mice and in human AD by single-nucleus RNA sequencing. We confirmed the presence of Trem2-dependent DAM and identified a previously undiscovered Serpina3n+C4b+ reactive oligodendrocyte population in mice. Interestingly, remarkably different glial phenotypes were evident in human AD. Microglia signature was reminiscent of IRF8-driven reactive microglia in peripheral-nerve injury. Oligodendrocyte signatures suggested impaired axonal myelination and metabolic adaptation to neuronal degeneration. Astrocyte profiles indicated weakened metabolic coordination with neurons. Notably, the reactive phenotype of microglia was less evident in TREM2-R47H and TREM2-R62H carriers than in non-carriers, demonstrating a TREM2 requirement in both mouse and human AD, despite the marked species-specific differences.

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Fig. 1: snRNA-seq distinguishes major brain-cell types and shows microgliosis in the 5XFAD brains.
Fig. 2: Characterization of the microglia cluster.
Fig. 3: Identification of a novel oligodendrocyte Aβ-reactive state defined by C4b and Serpina3n expression.
Fig. 4: Human AD brain exhibits a microglia signature distinct from that in mice.
Fig. 5: snRNA-seq identifies human AD-associated astrocyte and oligodendrocyte signatures corroborated by NanoString gene-expression analysis.
Fig. 6: TREM2-R62H and TREM2-R47H carriers exhibit reduced microglia reactive signature.

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Data availability

snRNA-seq gene lists with statistics and NanoString nCounter gene lists are available in Supplementary Tables 1, 4 and 5. Mouse snRNA-seq data that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) database with accession number GSE140511. Human snRNA-seq data that support the findings of this study are available via the AD Knowledge Portal (https://adknowledgeportal.org) under study snRNAseqAD_TREM2 and are also accessible through https://doi.org/10.7303/syn21125841. The AD Knowledge Portal is a platform for accessing data, analyses and tools generated by the Accelerating Medicines Partnership (AMP-AD) Target Discovery Program and other National Institute on Aging (NIA)-supported programs to enable open-science practices and accelerate translational learning. Data are available for general research use according to the requirements for data access and data attribution at https://adknowledgeportal.synapse.org/DataAccess/Instructions. Additional ROSMAP data can be requested at https://www.radc.rush.edu/.

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Acknowledgements

We would like to thank K. Murphy and T. Murphy for generously providing us Irf8-overexpression constructs and Irf8–/– mice. We thank S. Kumar for the help with IF on human PPFE samples, and B. Zinselmeyer and B. Saunders for their help with confocal images. We thank B. Schmidt for helpful discussions. We thank I. Kawaki and the Collaborative Research Project of the BRI, Niigata University. A. Kakita is supported by the Strategic Research Program for Brain Sciences from Japan Agency for Medical Research and Development, AMED. This work was supported by the NIH (RF1 AG051485, R21 AG059176, and RF1 AG059082 to M. Colonna, RF1 AG047644 and R01 NS090934 to D.M.H., R15 GM119070 to M.R.N.), the Cure Alzheimer’s Fund (to M. Colonna and D.M.H.) and the JPB Foundation (to D.M.H).

Author information

Authors and Affiliations

Authors

Contributions

Y.Z., W.M.S., M.N.A. and M. Colonna designed the study and interpreted the results. Y.Z, W.M.S., A.S. and T.K.U. processed the mouse brains to generate single nuclei. Y.Z. and A.S. processed human postmortem tissues to generate single nuclei. P.S.A., W.M.S. and K.Z. performed computational analyses, and Y.Z. and W.M.S. analyzed the results. Y.Z. and W.M.S. performed and analyzed IF on mouse samples. Y.Z. performed IF on human samples. T.L. and S.A.B. performed proteomics and phospho-proteomics studies. K.R.M. performed NanoString analysis. P.L.P. and M. Cominelli performed IHC. Y.Z., S. Grover and M.R.N. performed the Aβ aggregation assay. Y.Z., W.M.S. and M. Cella performed cell-stimulation experiments. S. Gilfillan bred all the mice. A.M., T.I., M.S. and A.K. provided human postmortem brain samples from BRI cohort. D.A.B. and J.A.S. provided human postmortem brain samples from the Rush cohort. J.U. and D.M.H. provided human post-mortem brain samples from ADRC cohort. M.N.A. provided guidance for computational analysis. Y.Z., W.M.S. and M. Colonna wrote the manuscript with feedback from all authors.

Corresponding authors

Correspondence to Maxim N. Artyomov or Marco Colonna.

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Competing interests

M. Colonna receives research support from Pfizer, Amgen, Alector and Ono.

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Peer review information Kate Gao was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 Cluster characterization of 7-month-old mouse cohort.

a, Alignment of Trem2 reads from all mice sequenced to the Trem2 reference genome shows knockout of Trem2 gene in Trem2–/– and Trem2–/– 5XFAD mice. No reads from Trem2–/– and Trem2–/– 5XFAD mice align to Trem2 exon 2. Alignment of reads from Trem2-deficient mice to Trem2 exon 1 reflects early transcriptional termination due to deletion of exons 3 and 4 in the design of Trem2-knockout construct. The presence of exon1 reads correspond to the use of 5′ sequencing in this cohort. Numbers on the left represent the total number of Trem2 reads from each sample. b, tSNE plots of snRNA-seq of 7-month-old mouse brain showing cell-type-specific markers identifying each cluster. n = 73,419 total nuclei. c, Bar graphs showing median of the number of genes, median of the number of UMIs and the total number of nuclei of each sample sequenced.

Extended Data Fig. 2 Cluster characterization of 15-month-old mouse cohort.

a, t-SNE plot showing 13 distinguished clusters, 0–12, with cell-type identities determined by expression of specific markers. Cluster 12 had very low frequency and did not have a clear marker profile and was thus omitted from analysis. b, Heat map showing specific markers identifying each cluster in a. Color scheme shows row max and row min. c, Pie chart showing the frequency of each cluster across all genotypes. Neuronal clusters are shown in blue hues and non-neuronal clusters are shown in red hues. d, Relative frequency of clusters in different samples, normalized to overall frequency in c, shown for cortex and hippocampus. Clusters 2 and 11 (neuronal) were exclusive to hippocampus, while clusters 0 and 6 (neuronal) were exclusive to cortex. Cluster 4 (neuronal) was enriched in Trem2–/– 5XFAD cortex. e, Number of unique molecular identifiers (UMIs), indicative of captured reads, superimposed on the t-SNE plot from a. Cluster 4 has a lower average number of UMIs compared to other neurons. f, t-SNE plot showing expression of Pam, a representative gene enriched in cluster 4. n = 38,230 total nuclei pooled from 3 mouse brains per genotype (a,e,f).

Extended Data Fig. 3 Characterization of the microglia cluster in the 15-month-old mouse cohort.

a, t-SNE plot showing the microglia cluster (cluster 10 from Extended Data Fig. 2), expressing microglia genes, such as C1qa, Fcrls and Tyrobp. b, Volcano plots showing DEGs (fold change > 1.5, two-part hurdle model, adjusted P < 0.05, Bonferroni correction) of 5XFAD versus WT (effect of Aβ) and 5XFAD versus Trem2–/– 5XFAD (dependence of Trem2) in microglia. c, t-SNE plot of re-clustered microglia (from cluster 10) identifying 4 sub-clusters. d, Bar graphs showing the relative frequency of sub-cluster 3 in each sample. Sub-cluster 3 is only present in the 5XFAD sample. e, Violin plots showing the expression of DAM genes, Cst7, Gpnmb and Spp1, enriched in sub-cluster 3. Violin plots are presented with floating box showing median (middle line) and quartiles (top and bottom). Minima and maxima are shown as the bottom and top of the violin plots. n = 266 WT, 92 Trem2–/–, 171 WT 5XFAD and 88 Trem2–/– 5XFAD microglial nuclei, pooled from 3 mouse brains per genotype (a,b,c,e).

Extended Data Fig. 4 Oligodendrocytes acquire an Aβ-dependent signature and do not cluster around plaques in the 5XFAD model.

a, Box plots showing average gene expression across oligodendrocyte nuclei isolated from each mouse in the 7-month-old cohort. Floating bars show the min and max and black line shows the mean. Each dot represents one mouse. n = 3 biologically independent mice per genotype. b, Violin plots showing expression of C4b, Serpina3n and H2-D1 in all oligodendrocytes from the 15-month-old cohort. Violin plots are presented with floating boxes showing median (middle line) and quartiles (top and bottom). Minima and maxima are shown as the bottom and top of the violin plots. n = 617 WT, 298 Trem2–/–, 160 WT 5XFAD and 308 Trem2–/– 5XFAD oligodendrocytes, pooled from 3 mouse brains per genotype. c, RT–qPCR from human oligodendrocyte cell line (HOG) treated with Aβ oligomers or fibrils at the indicated concentrations for 18 h showing Aβ directly induces C4. n = 3 biologically independent cell cultures. d, RT–qPCR from HOG treated with soluble factors (GPNMB or alpha-2-macroglobulin) for 24 h or a cocktail of cytokines (IL-1β, IL-6, TNF-α, IFN-α, IFN-γ) for 8 h showing induced C4. n = 3 biologically independent cell cultures. e, Representative immunofluorescence images of Olig2 and plaque staining in 5-month-old WT 5XFAD and Trem2–/– 5XFAD cortices. n = 6 mice per genotype. Scale bar, 50 μm. f, Quantification of density of Olig2+ nuclei within 15 μm or 30 μm shell around plaque surfaces in the cortex in e, n = 6 mice per genotype. g, Quantification of total number of CA2+ oligodendrocytes in all 4 genotypes at 7 months of age. n = 3 mice per genotype. h, Representative immunofluorescence images of Serpina3n staining in 7-month-old mice of all genotypes showing colocalization of Serpina3n with oligodendrocyte marker CA2. White arrow heads indicate colocalization. n = 3 mice per genotype. Scale bar, 15 μm. i, Automated quantification of Serpina3n intensity in CA2+ oligodendrocytes in h. n = 3 mice per genotype. j, Representative confocal images showing colocalization of Serpina3n with GFAP+ astrocytes in 15-month-old 5XFAD mice. n = 3 mice per genotype. CC, corpus callosum. Scale bar, 50 μm. Inset, enlarged image detail. k, Representative confocal images showing colocalization of Serpina3n with X04+ plaques in 15-month-old 5XFAD mice. IV, V and VI indicate corresponding cortical layers. n = 3 mice per genotype. Scale bar, 60 μm. l, Thioflavin T fluorescence of Aβ42 aggregation with the addition of combinations of proteins at indicated concentrations in microplate shaking assay. n = 5 independent wells for the aggregation reactions; data represent two independent experiments. P value by one-way ANOVA, Tukey’s multiple comparisons test (a,g,i) or unpaired t-test, two-tailed (c). All data are presented as mean ± s.e.m.

Extended Data Fig. 5 Heat maps of fold changes of DEGs in OPC, astrocyte and neuron clusters in the 7-month-old mouse cohort.

Cluster-by-cluster analysis of differential gene expression. Heat maps showing the top 30 (or less) DEGs (fold change > 1.5, two-part hurdle model, adjusted P value < 0.05, Bonferroni correction), ordered by adjusted P value, and results are presented for comparisons of 5XFAD versus WT. Numbers indicate log2(fold change). Analyses are presented for the following clusters: a, cluster 8 (OPC), n = 485 5XFAD and 705 WT nuclei; b, cluster 6 (astrocytes), n = 490 5XFAD and 1,088 WT nuclei; c, cluster 0 (excitatory neurons), n = 3,302 5XFAD and 4,396 WT nuclei; d, cluster 3 (excitatory neurons), n = 1,941 5XFAD and 3,038 WT nuclei; e, cluster 5 (excitatory neurons), n = 1,530 5XFAD and 1,912 WT nuclei; f, cluster 1 (inhibitory neurons), n = 2,606 5XFAD and 3,315 WT nuclei; and g, cluster 4 (inhibitory neurons), n = 1,672 5XFAD and 2,660 WT nuclei. n = 3 biologically independent mouse brain samples per genotype. The lists of genes are in Supplementary Table 1.

Extended Data Fig. 6 Proteomic analysis recapitulates major findings from snRNA-seq analysis.

a, Left, Heat map of relative abundance of the most significantly upregulated proteins from proteomics in CV 5XFAD compared with CV mice, ranked by fold change. Total protein analysis was conducted on brain tissues from 10-month-old CV, R47H, Trem2–/– (KO), CV 5XFAD, R47H 5XFAD and KO 5XFAD mice. Right, Heat map showing average expression of corresponding gene in each cluster in snRNA-seq of every mouse from 7-month-old cohort. Each column represents one individual mouse. Within a cluster, mice from left to right: WT1–3, Trem2–/–1–3, WT 5XFAD1–3, Trem2–/– 5XFAD1–3. b, Relative abundance of selected proteins upregulated in different cell types. c, IPA analysis showing pathways upregulated in CV-5XFAD compared with CV mice in proteomics. n = 312 genes, Fisher’s exact test. d, Left, Heat map of relative abundance of proteins with the most significantly upregulated phospho-peptides from phospho-proteomics in CV 5XFAD compared with CV mice, ranked by fold change. Right, Heat map showing average expression of corresponding gene in each cluster in snRNA-seq of every mouse from 7-month-old cohort. Each column represents one individual mouse. Within a cluster, mice from left to right: WT1–3, Trem2–/–1–3, WT 5XFAD1–3, Trem2–/– 5XFAD1–3. e, IPA analysis showing pathways upregulated in CV-5XFAD compared to CV mice in phospho-proteomics. n = 270 genes, Fisher’s exact test.

Extended Data Fig. 7 Characterization of human snRNA-seq.

a, Total number of nuclei, median of number of UMIs and median of number of genes of each human sample sequenced. C, control; AD, AD (CV); P, AD (R62H). b, t-SNE plots of human snRNA-seq showing cell-type-specific markers identifying each cluster. n = 66,311 total nuclei. c, Violin plots showing expression of known cell type markers that define each cluster. Total number of nuclei in each cluster: 16,156 in Oli0, 13,322 in Oli1, 12,806 in Ex0, 1,869 in Ex1, 4,256 in In, 9,019 in Astro, 3,986 in Micro, 3,243 in OPC, 841 in Endo. Violin plots are centered around the median and shape represents cell distribution. d, Bar graph presenting frequency of nuclei in each neuronal sub-cluster across all neuronal nuclei, comparing AD (CV), AD (R62H) versus control samples. e, t-SNE plot showing expression of NEFL in neuronal clusters, especially in cluster Ex1. n = 66,311 total nuclei.

Extended Data Fig. 8 AD-associated human signatures are distinct from those in the Aβ mouse model.

a, Heatmaps showing fold change of top DEGs (log2(fold change) > 0.5, two-part hurdle model, adjusted P < 0.05, Bonferroni correction) between AD (CV) and control in all clusters. Left, Genes upregulated in AD. Right, Genes downregulated in AD. Numbers indicate log2(fold change). n = 11 subjects with AD (CV) and 11 controls. b, Violin plots showing expression of mouse DAM genes in 7- and 15-month-old mouse snRNA-seq and their homologs in human snRNA-seq within the microglia cluster. Violin plots are presented with floating boxes showing median (middle line) and quartiles (top and bottom). Minima and maxima are shown as the bottom and top of the violin plots. 7-month-old mouse, n = 3 biologically independent mouse brains per genotype, 524 WT, 582 Trem2–/–, 1,123 WT 5XFAD and 604 Trem2–/– 5XFAD microglial nuclei; 15-month-old mouse, n = 266 WT, 92 Trem2–/–, 171 WT 5XFAD and 88 Trem2–/– 5XFAD microglial nuclei, pooled from 3 mouse brains per genotype; human, n = 11 controls, 1,547 nuclei; 11 subjects with AD, 919 nuclei. c, t-SNE plots showing the cell type of origin of selected DAM genes in the human brain. CST7 was not detectable in any cluster. GPNMB and LPL were expressed in OPCs. Color scheme shows expression. n = 66,311 total nuclei. d, Gating strategy for viral transduced BMDMs. WT BMDMs were transduced with virus containing empty pESV-ires-eGFP vector or Irf8-overexpressing (OE) pESV-Irf8-ires-eGFP vector. Successfully transduced cells were identified by GFP+ gate. e, Gating strategy for WT and Irf8–/– BMDMs. f, Heatmap representing the average gene expression of top microglia DEGs in microglia sub-clusters in AD versus control samples. Microglia subclusters are indicated in the top left t-SNE plot. Color scheme shows row max and row min. g, t-SNE projection of all nuclei in AD versus control samples showing the lack of a sub-population of astrocytes in AD. Red circle indicates the population. Colors correspond to individual clusters. n = 66,311 total nuclei. h, t-SNE plots showing the average z-scores of downregulated genes in astrocytes. Red circle indicates the disappearing population enriched for downregulated genes. n = 65 downregulated genes in astrocytes listed in Supplementary Table 4 were used as inputs. i, t-SNE plots of oligodendrocyte sub-clusters showing average z-scores of DEGs in oligodendrocytes. Top, Upregulated genes are enriched in Oligo0 and Oligo3 (indicated in Fig.5). Bottom, Downregulated genes are enriched in Oligo1 and Oligo2. Oligodendrocyte subclusters are indicated in the top left t-SNE plot. n = 20 up- and 23 downregulated genes in oligodendrocytes listed in Supplementary Table 4 were used as inputs.

Extended Data Fig. 9 Human AD-associated oligodendrocyte and microglia signatures identified by snRNA-seq match public datasets from aging and early-onset AD populations.

Cluster markers of Micro0, Micro1, Olig0 and Oligo1 (listed in Supplementary Table 4) were used as inputs for GSEA analysis against public datasets on aging (a, GSE53890) and people with early-onset AD (b, GSE39420). Genes enriched in Micro0 and Oligo0 correspond to genes previously identified as upregulated in human aging and people with early-onset AD. Genes enriched in Micro1 and Oligo1 correlate with downregulation in aging and early-onset AD. n = 146 genes for Micro0, 178 genes for Micro1, 59 genes for Oligo0 and 233 genes for Oligo1 were used as inputs. P value by permutation test.

Extended Data Fig. 10 NanoString nCounter analysis of two cohorts of subjects with AD corroborates findings in snRNA-seq.

a, Diagram of NanoString pipeline. b, t-SNE plots of human brain showing the cell type of origin of top DEGs identified in NanoString analysis of Rush cohort. Color scheme shows expression. n = 66,311 total nuclei shown. c, Volcano plot showing DEGs of AD versus control from the BRI cohort. n = 10 controls and 10 subjects with AD. P value by multivariate linear regression with Benjamini–Yekutieli adjustment. d, Pathway analysis showing the same pathways are differentially regulated in AD brains from Rush (left) and BRI (right). e, t-SNE plots showing expression of IL10RA and HPGDS in human microglia. n = 66,311 total nuclei shown.

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Zhou, Y., Song, W.M., Andhey, P.S. et al. Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease. Nat Med 26, 131–142 (2020). https://doi.org/10.1038/s41591-019-0695-9

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