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Cited by 258Neuroinflammation and Neurodegeneration MechanismsAlzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.

APOE and TREM2 regulate amyloid-responsive microglia in Alzheimer’s disease

Open access
Nguyen, Aivi T., Wang, Kui, Hu, Gang, Wang, Xuran, Miao, Zhen, Azevedo, Joshua A., Suh, EunRan, Van Deerlin, Vivianna M., Choi, David, Roeder, Kathryn, Li, Mingyao, Lee, Edward B.·2020·Acta Neuropathologica
DOI 10.1007/s00401-020-02200-3PMC PMC7520051
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Abstract

Beta-amyloid deposition is a defining feature of Alzheimer's disease (AD). How genetic risk factors, like APOE and TREM2, intersect with cellular responses to beta-amyloid in human tissues is not fully understood. Using single-nucleus RNA sequencing of postmortem human brain with varied APOE and TREM2 genotypes and neuropathology, we identified distinct microglia subpopulations, including a subpopulation of CD163-positive amyloid-responsive microglia (ARM) that are depleted in cases with APOE and TREM2 risk variants. We validated our single-nucleus RNA sequencing findings in an expanded cohort of AD cases, demonstrating that APOE and TREM2 risk variants are associated with a significant reduction in CD163-positive amyloid-responsive microglia. Our results showcase the diverse microglial response in AD and underscore how genetic risk factors influence cellular responses to underlying pathologies.

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Fig. 1 (a) Schematic of the analysis pipeline. (b) The left figure is a t-distributed stochastic neighbor embedding (t-SNE) projection of all cells (n=122,606 from 15 brains) after quality control filtering (Table S2 and S3): Microglia(Mic); Excitatory neuron(Ex); Inhibitory neuron(In); Astrocytes(Ast); Oligodendroctyes (Oli); Oligodendrocyte progenitor cells (Opc); Endothelial (End). The right figure is a t-SNE plot colored by 15 samples. (c) Expression feature plots of known cell type-specific marker genes. (d) The proportions of neurons (excitatory and inhibitory neurons), astrocytes, and microglia across cases without or with AD neurofibrillary degeneration
Fig. 1 (a) Schematic of the analysis pipeline. (b) The left figure is a t-distributed stochastic neighbor embedding (t-SNE) projection of all cells (n=122,606 from 15 brains) after quality control filtering (Table S2 and S3): Microglia(Mic); Excitatory neuron(Ex); Inhibitory neuron(In); Astrocytes(Ast); Oligodendroctyes (Oli); Oligodendrocyte progenitor cells (Opc); Endothelial (End). The right figure is a t-SNE plot colored by 15 samples. (c) Expression feature plots of known cell type-specific marker genes. (d) The proportions of neurons (excitatory and inhibitory neurons), astrocytes, and microglia across cases without or with AD neurofibrillary degenerationCC BY · PubMed Central
Fig. 2 Microglia subclusters are unique by pathologic characterization, differentially expressed genes, genotype, or co-expression network analysis. (a) t-SNE projections of microglia subpopulations additionally colored by cell type, AT score, TREM2 R47H genotype, and APOE genotype. (b) Differentially expressed genes (DEGs) between subpopulations: motile vs homeostatic, ARM vs homeostatic, and dystrophic vs homeostatic. The genes in red are upregulated and those in blue are downregulated. Gene markers of interest per subcluster are highlighted with boxes. (c) Co-expression modules for each microglia subtype depicting gene-gene co-expression networks, colored by the strength of the gene-gene connection ranging from none (white) to strong (red). Intervening Sankey plots depict the flow of gene clusters from one subtype to the next, wherein the width demonstrates the magnitude of flow. Only major flows with more than 12 genes are plotted. (d) Bar plots of the differing microglia subpopulations (homeostatic, dystrophic, motile and ARM) in TREM2 WT cases with varying amyloid and tau pathology (AT scores A−T−, A+T−, and A+T+; n=2, 4, and 5 respectively; Fisher’s exact test performed for each pair-wise comparison) or (e) separated by APOE alleles, matched for pathology (n=2 for E3/E3 and n=6 for E3/E4; Fisher’s exact test performed for ARM proportion calculation). (f) Cell type proportions in TREM2 R47H variant cases only, subdivided by pathologic classification (Fisher’s exact test performed for ARM proportion calculation compared to TREM2 WT A+T+ cases). Note that only one case with the TREM2 R47H variant and an A+T− score was available.
Fig. 2 Microglia subclusters are unique by pathologic characterization, differentially expressed genes, genotype, or co-expression network analysis. (a) t-SNE projections of microglia subpopulations additionally colored by cell type, AT score, TREM2 R47H genotype, and APOE genotype. (b) Differentially expressed genes (DEGs) between subpopulations: motile vs homeostatic, ARM vs homeostatic, and dystrophic vs homeostatic. The genes in red are upregulated and those in blue are downregulated. Gene markers of interest per subcluster are highlighted with boxes. (c) Co-expression modules for each microglia subtype depicting gene-gene co-expression networks, colored by the strength of the gene-gene connection ranging from none (white) to strong (red). Intervening Sankey plots depict the flow of gene clusters from one subtype to the next, wherein the width demonstrates the magnitude of flow. Only major flows with more than 12 genes are plotted. (d) Bar plots of the differing microglia subpopulations (homeostatic, dystrophic, motile and ARM) in TREM2 WT cases with varying amyloid and tau pathology (AT scores A−T−, A+T−, and A+T+; n=2, 4, and 5 respectively; Fisher’s exact test performed for each pair-wise comparison) or (e) separated by APOE alleles, matched for pathology (n=2 for E3/E3 and n=6 for E3/E4; Fisher’s exact test performed for ARM proportion calculation). (f) Cell type proportions in TREM2 R47H variant cases only, subdivided by pathologic classification (Fisher’s exact test performed for ARM proportion calculation compared to TREM2 WT A+T+ cases). Note that only one case with the TREM2 R47H variant and an A+T− score was available.CC BY · PubMed Central
Fig. 3. (a) Uniform Manifold Approximation and Projection (UMAP) visualization of the microglia cell trajectory colored by subclusters, estimated pseudotime, AT score, TREM2 R47H and APOE genotype. (b) Heatmap of putative AD risk genes across microglia subpopulations (left) and AT score (right).
Fig. 3. (a) Uniform Manifold Approximation and Projection (UMAP) visualization of the microglia cell trajectory colored by subclusters, estimated pseudotime, AT score, TREM2 R47H and APOE genotype. (b) Heatmap of putative AD risk genes across microglia subpopulations (left) and AT score (right).CC BY · PubMed Central
Fig.4. CD163+ ARM are associated with amyloid plaques and show decreased expression with TREM2 R47H and APOE E4 allele. (a) Pan-microglial marker Iba1 stains microglia with a small cell body and highly ramified, branched processes in an adult brain without amyloid or tau pathology, and (b) homeostatic marker CX3CR1 highlights similar features in microglia, although astrocytes were also stained. In AD brains, (c) motile marker FGD4 highlights microglia with bipolar processes and hypertrophic cell bodies, (d) ARM marker CD163 shows clustered, amoeboid microglia, and (e) FTL highlights dystrophic microglia with hypertrophic cell bodies and beaded processes. (f) Iba1 staining shows clustered, amoeboid microglia and intervening evenly-dispersed microglia in neocortex of AD brain, while (g) CD163 highlights only clustered microglia. (h) CD163+ ARM (brown) co-localize with beta-amyloid plaques (pink) in AD brain. (i) CD163:amyloid ratios are decreased in cases with the TREM2 R47H variant and APOE E4 allele. (j) Multiple linear regression model shows a significantly decreased CD163:amyloid ratio in (k) TREM2 WT cases with the APOE E4 allele versus E3/E3. When matched for APOE allele, cases with the TREM2 R47H variant showed a consistently decreased ARM:amyloid ratio in (l) APOE E3/E3 cases and (m) APOE E3/E4 cases. ***p < 0.001. Images (a-g) white balanced; scale bar, 10 μm.
Fig.4. CD163+ ARM are associated with amyloid plaques and show decreased expression with TREM2 R47H and APOE E4 allele. (a) Pan-microglial marker Iba1 stains microglia with a small cell body and highly ramified, branched processes in an adult brain without amyloid or tau pathology, and (b) homeostatic marker CX3CR1 highlights similar features in microglia, although astrocytes were also stained. In AD brains, (c) motile marker FGD4 highlights microglia with bipolar processes and hypertrophic cell bodies, (d) ARM marker CD163 shows clustered, amoeboid microglia, and (e) FTL highlights dystrophic microglia with hypertrophic cell bodies and beaded processes. (f) Iba1 staining shows clustered, amoeboid microglia and intervening evenly-dispersed microglia in neocortex of AD brain, while (g) CD163 highlights only clustered microglia. (h) CD163+ ARM (brown) co-localize with beta-amyloid plaques (pink) in AD brain. (i) CD163:amyloid ratios are decreased in cases with the TREM2 R47H variant and APOE E4 allele. (j) Multiple linear regression model shows a significantly decreased CD163:amyloid ratio in (k) TREM2 WT cases with the APOE E4 allele versus E3/E3. When matched for APOE allele, cases with the TREM2 R47H variant showed a consistently decreased ARM:amyloid ratio in (l) APOE E3/E3 cases and (m) APOE E3/E4 cases. ***p < 0.001. Images (a-g) white balanced; scale bar, 10 μm.CC BY · PubMed Central

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Research works printed but not linked: 2

  1. del Rio-Hortega P (1919) El Tercer Elemento de los Centros Nerviosos. IV. Poder Fagocitario y Movilidad de la Microglía. Bol Soc Esp Biol VIII 1919:154–171
  2. Kristiansen M, Graversen JH, Jacobsen C et al (2001) Identification of the haemoglobin scavenger receptor. Nature 409(6817):198–201. https://doi.org/10.1038/35051594 · DOI · Paper page

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Metadata

Authors
Nguyen, A. T., Wang, K., Hu, G., Wang, X., Miao, Z., Azevedo, J. A., Suh, E., Van Deerlin, V. M., Choi, D., Roeder, K., Li, M., & Lee, E. B.
Affiliations
  • University of Pennsylvania (US)
  • Nankai University (CN)
  • Carnegie Mellon University (US)
Corresponding author
  • Li, Mingyao
  • Lee, Edward B.
ORCID
Venue
Acta Neuropathologica
Publisher
Springer Science and Business Media LLC
Published
2020-08-25
Volume
140
Issue
4
Pages
477-493
ISSN
  • 0001-6322 (ISSN-L)
  • 1432-0533
DOI
10.1007/s00401-020-02200-3
PMC
PMC7520051
OpenAlex
W3080402156
Cited by
241
References
79
Citations by year
2026: 33 · 2025: 39 · 2024: 67 · 2023: 43 · 2022: 32 · 2021: 23 · 2020: 2
FWCI
9.51
Type
journal article
Language
en
Update notices
correction (2023-08-17)
Open access
Licence
Locations
  • Acta Neuropathologica (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion, cc-by)
  • PubMed Central (acceptedVersion, cc-by)
Funders
  • National Institutes of Health (R01NS095793, R56AG063344, P30AG010124, T32AG000255, R01GM108600, R01GM125301, R37MH05788)
  • University of Pennsylvania Institute on Aging Pilot Grant (Pilot Grant)
Topics
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Keywords
Alzheimer's disease, apolipoprotein E, TREM2, amyloid-beta, microglial subpopulations, CD163, genetic risk variants, single-nucleus RNA sequencing, postmortem brain
MeSH terms
Alzheimer Disease, Apolipoproteins E, Humans, Membrane Glycoproteins, Receptors, Immunologic, Amyloid beta-Peptides, Microglia

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