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Cited by 140Alzheimer's disease research and treatmentsNeuroinflammation and Neurodegeneration MechanismsSingle-cell and spatial transcriptomics

Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease

Open access
Serrano-Pozo, Alberto, Li, Huan, Li, Zhaozhi, Muñoz-Castro, Clara, Jaisa-aad, Methasit, Healey, Molly A., Welikovitch, Lindsay A., Jayakumar, Rojashree +19 more·2024·Nature Neuroscience
DOI 10.1038/s41593-024-01791-4PMC PMC11614739

Published version of a preprint

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Abstract

Abstract Astrocytes play a critical role in brain homeostasis and normal functions but their changes along the spatiotemporal progression of Alzheimer’s disease (AD) neuropathology remain largely unknown. Here we performed single-nucleus RNA-sequencing on brain regions along the stereotypical progression of AD pathology from donors ranging the entire normal aging-AD continuum comprising 628,943 astrocyte nuclei from 32 donors across 5 brain regions. We discovered temporal gene-expression-trajectories with gene sets differentially activated at various disease stages. Surprisingly, a gene set enriched in proteostasis and energy metabolism, was upregulated in late-stage but unexpectedly returned to baseline levels in end-stage, suggesting exhaustion of response in “burnt-out” astrocytes. The spatial gene-expression-trajectories revealed that astrocytic genes of tripartite synapses are dysregulated in parallel to the stereotypical progression of tangle pathology across regions. We identified astrocyte heterogeneity across brain regions with a continuum from homeostatic to reactive cells through “intermediate” transitional states. These findings suggest complex astrocytic dysfunction in AD neurodegeneration.

AI snapshot

Written from the paper’s full text.

TL;DR

Single-nucleus RNA sequencing of 628,943 astrocyte nuclei from five brain regions across 32 donors spanning normal aging to severe Alzheimer’s disease maps spatial and temporal astrocyte transcriptomic changes. The study identifies homeostatic, intermediate, reactive, trophic factor-rich, and exhausted astrocyte subclusters, with late-stage response exhaustion at Braak stage VI.

Key findings

  • The dataset comprised 628,943 astrocyte nuclei from five regions (EC, ITG, PFC, V2, V1) in 32 donors, with >100,000 nuclei per region and ≈6,000 average reads and ≈2,500 average genes detected per nucleus.
  • In eight normal-aging control donors, EC and V1 had the most differentially expressed genes versus other regions (EC: 137 up, 152 down; V1: 93 up, 122 down); only 18 of 137 EC-upregulated and 37 of 152 EC-downregulated genes correlated with pTau/tau ratio, supporting an allocortex-specific signature distinct from a pTau signature.
  • Spatial analysis identified 504 DEGs between adjacent AD-network nodes grouped into six spatial gene sets; temporal analysis identified 798 DEGs between adjacent pathology stages grouped into six temporal gene sets. Homeostatic, intermediate, and reactive astrocyte proportions changed along the spatial axis, whereas astMet and astTinf changed along the temporal axis; astTinf declined along pathology stages, while astMet increased in late stage and returned toward baseline in end stage, suggesting exhaustion.
  • Clustering revealed nine astrocyte subclusters, including astH0, astIM, astR0/R1/R2, astMet, astTinf, and two likely doublet clusters (astNeu, astMic); reactive astrocytes represented less than 25% of nuclei. Pseudotime and CellRank supported astH0→astIM→astR transitions and off-pathway terminal astMet/astTinf states; comparison with nine public datasets found astTinf in all but one, but sizable astMet only in SEA-AD, with no significant astMet frequency change across Braak stages in those datasets.

Methods

  • Frozen postmortem brain specimens from 32 donors were processed with fluorescence-activated nuclei sorting to deplete NeuN-positive neurons and OLIG2-positive oligodendrocytes, followed by 10x Genomics snRNA-seq of five cortical regions; donors were grouped into four pathology stages using CERAD neuritic plaque score, Braak NFT stage, 3D6 Aβ immunohistochemistry, and pTau/tau ELISA.
  • Bioinformatics included Cell Ranger alignment, Seurat integration, differential expression, spectral clustering into spatial and temporal gene sets, Harmony-based astrocyte subclustering, monocle3 pseudotime, velocyto/scVelo/CellRank RNA velocity, and label transfer to nine public snRNA-seq datasets.
  • Validation used immunohistochemistry and multiplex fluorescence for AQP4, GJA1, and reactive markers around Thioflavin-S plaques, plus RNAScope in situ hybridization for MAPT and HSPB1/ALDH1L1.

Limitations

  • The paper states that no randomization was performed, no statistical methods were used to predetermine sample sizes, and data collection/analysis were not blinded to neuropathological diagnosis.
  • The paper notes higher interdonor variability in temporal gene sets, possibly reflecting differences in stage duration across donors, and that the astMet exhaustion phenomenon was unique to this dataset and not significant across Braak stages in the nine public datasets.
  • Evident from the text: the cross-sectional autopsy design cannot directly establish temporal ordering or causality, pathology stages are assumed to be temporally ordered, and per-stage donor numbers are small (8 donors per stage in Table 1), with some region-stage combinations missing (for example, n = 22 EC versus n = 32 V1 samples in Fig. 6a).

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/s41593-024-01791-4

Cites

75 of 75 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

59 of 70 cited sources checked · 25 supported · 4 flagged · accuracy not yet measured

  • Premisecitation

    Less is known about the transcriptomic heterogeneity of astrocytes across different cortical areas in the aging human brain.

    “but less is known about the transcriptomic heterogeneity of astrocytes across different cortical areas in the aging human brain.”
    Quote in the paperSubstantial claim9 of 9 sources checked
    • cites [8] Endo, F. et al. Molecular basis of astrocyte diversity and morphology across the CNS in health and disease. Science 378, eadc9020 (2022). source

      The Strategy and Bioinformatic evaluation of astrocyte diversity sections describe transcriptomic comparisons across adult mouse CNS regions, including cortical areas. Our copy does not state whether transcriptomic heterogeneity across cortical areas in the aging human brain is less well understood; searches for human aging and cortical heterogeneity found no passage addressing that knowledge gap. (LLM, conf=0.75)

      Experimental — accuracy not yet measured
    • cites [25] Morel, L. et al. Molecular and functional properties of regional astrocytes in the adult brain. J. Neurosci. 37, 8706–8717 (2017). source

      The Introduction (page not provided) says earlier in vivo astrocyte gene profiling largely focused on the cortex or developing ages, and that regional human-brain datasets were not astrocyte-specific. This supports a general knowledge gap, but the paper studies adult mice and does not establish the claim specifically for different cortical areas in the aging human brain. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [26] John Lin, C. C. et al. Identification of diverse astrocyte populations and their malignant analogs. Nat. Neurosci. 20, 396–405 (2017). source

      The Discussion (page unavailable) says astrocyte diversity in the adult brain remained poorly understood, supporting the general knowledge-gap claim. But the study characterizes adult mouse brain regions, not different cortical areas in the aging human brain; its human evidence is limited to a comparison with human astrocyte gene signatures. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [27] Chai, H. et al. Neural circuit-specialized astrocytes: transcriptomic, proteomic, morphological, and functional evidence. Neuron 95, 531–549 (2017). source

      The Introduction says astrocyte diversity remains incompletely tested, while noting emerging evidence in aging and disease. The Results examine transcriptomic differences between the striatum and hippocampus of adult mice; the paper does not establish the specific knowledge gap concerning different cortical areas in the aging human brain. Page numbers are unavailable in our copy. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
    • cites [28] Clarke, L. E. et al. Normal aging induces A1-like astrocyte reactivity. Proc. Natl Acad. Sci. USA 115, E1896–E1905 (2018). source

      The Discussion (A1-Like Reactive Astrocytes Appear with Normal Brain Aging; page unavailable) says the study did not characterize astrocytes in detail throughout all cortical regions and calls for further work. This supports a knowledge gap across cortical areas, but the study examined mice, not the aging human brain, and its cortical-region caveat concerns reactivity rather than transcriptomic heterogeneity specifically. (LLM, conf=0.83)

      Experimental — accuracy not yet measured
    • cites [29] Zeisel, A. et al. Molecular architecture of the mouse nervous system. Cell 174, 999–1014 (2018). source

      The Results section, “Astroependymal Cells Are Diverse and Spatially Patterned” (page not provided), describes limited historical understanding of astrocyte diversity and identifies regionally distinct astrocytes in mice. It does not assess how much is known about transcriptomic differences across cortical areas in the aging human brain. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
    • cites [30] Boisvert, M. M., Erikson, G. A., Shokhirev, M. N. & Allen, N. J. The aging astrocyte transcriptome from multiple regions of the mouse brain. Cell Rep. 22, 269–285 (2018). source

      The Introduction describes limited prior work on astrocyte changes in aging, and the Results section “Adult Cortical Astrocytes Show Region-Dependent Gene Expression” documents transcriptomic differences across mouse cortical areas. The paper studies mice and does not specifically assess how much is known about those differences across cortical areas in the aging human brain. (LLM, conf=0.80)

      Experimental — accuracy not yet measured
    • cites [31] Batiuk, M. Y. et al. Identification of region-specific astrocyte subtypes at single cell resolution. Nat. Commun. 11, 1220 (2020). source

      The Results report transcriptomic heterogeneity between and within regions of the adult mouse brain, and the Introduction notes evidence for region-specific astrocyte subtypes in human tissue. Neither passage establishes how much is known about differences across cortical areas in the aging human brain; the paper's own single-cell analysis is in mice. (LLM, conf=0.77)

      Experimental — accuracy not yet measured
    • cites [32] Allen, W. E., Blosser, T. R., Sullivan, Z. A., Dulac, C. & Zhuang, X. Molecular and spatial signatures of mouse brain aging at single-cell resolution. Cell 186, 194–208 (2023). source

      The Results report spatial differences in aging-related astrocyte gene expression, but the measurements are from mouse brain regions, not human cortical areas. The Discussion proposes future spatial transcriptomic measurements in humans, suggesting a broader knowledge gap; it does not specifically establish what is known about astrocyte heterogeneity across human cortical areas. No page numbers are available in our copy. (LLM, conf=0.77)

      Experimental — accuracy not yet measured
  • Interpretationown data

    The pTau/tau ratio pattern is consistent with the stereotypical hierarchical accumulation of NFTs along neural networks.

    “consistent with the stereotypical hierarchical accumulation of NFTs along neural networks20,21”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites [20] Braak, H. & Braak, E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991). source
    • cites [21] Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H. & Del Tredici, K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404 (2006). source

      The staging system section describes a predictable sequence of neurofibrillary lesions across six stages, supporting the claim of stereotypical, hierarchical accumulation. It does not establish that accumulation occurs along neural networks; it describes the anatomical distribution of lesions instead. The pTau/tau ratio is the citing authors’ framing, not a finding attributed to this source by the cited sentence. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
  • Premisecitation

    Downregulation of SLC1A2 is predicted to increase the excitability of glutamatergic neurons.

    “downregulation of SLC1A2 is predicted to increase the excitability of glutamatergic neurons38”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [38] Ortinski, P. I. et al. Selective induction of astrocytic gliosis generates deficits in neuronal inhibition. Nat. Neurosci. 13, 584–591 (2010). source

      The Results section, “Virus-induced astrocytosis alters network excitability” (page unavailable), reports hippocampal network hyperexcitability following reactive gliosis. But it attributes that effect to impaired inhibition associated with reduced glutamine synthetase, not to SLC1A2 downregulation. The paper does not establish the claimed SLC1A2-to-excitability link. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
  • Premisecitation

    An increase in SLC1A2 expression in EC astrocytes has been associated with resilience to AD pathology.

    “an increase in SLC1A2 expression in EC astrocytes has been associated with resilience to AD pathology37”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [37] Kobayashi, E. et al. Activated forms of astrocytes with higher GLT-1 expression are associated with cognitive normal subjects with Alzheimer pathology in human brain. Sci. Rep. 8, 1712 (2018). source
  • Interpretationreasoning

    Aβ and pTau have a synergistic effect on the astrocyte transcriptome.

    “further suggesting a synergistic effect of Aβ and pTau on the astrocyte transcriptome5”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [5] Jiwaji, Z. et al. Reactive astrocytes acquire neuroprotective as well as deleterious signatures in response to Tau and Aβ pathology. Nat. Commun. 13, 135 (2022). source

      The Results section, “A core signature of astrocytic genes regulated by both Tau and Aß pathology” (Fig. 3A; page not provided), reports overlapping astrocyte gene-expression changes in separate tauopathy and amyloidopathy mouse models. It does not establish that Aß and phosphorylated tau act synergistically on the astrocyte transcriptome. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
  • May combine two claims. 55
  • Classified as probably not a substantial claim. 32
  • The quote only partly states this claim. 1

  • May combine two claims.

    Study design and conductown data

    The snRNA-seq dataset contains over 100,000 astrocyte nuclei in each brain region with ≈6,000 average total reads and ≈2,500 average total genes detected, which is orders of magnitude higher than previous studies.

    “resulting in over 100,000 astrocyte nuclei in each brain region with ≈6,000 average total number of reads and ≈2,500 average total number of genes detected, which is orders of magnitude higher than previous studies9–15”
    Quote in the paperSubstantial claim6 of 7 sources checked
    • cites [9] Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019). source

      The citing sentence uses Mathys et al. as a previous study for comparison, not as the source of its own dataset’s figures. In “Single-nucleus RNA-seq profiling of prefrontal cortex in human subjects with AD pathology” (page unavailable), Mathys et al. report 80,660 nuclei in total, so their study provides a smaller dataset for comparison. Our copy does not establish the claimed orders-of-magnitude comparison for astrocyte counts, reads, or genes detected. (LLM, conf=0.79)

      Experimental — accuracy not yet measured
    • cites [10] Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019). source
    • cites [11] Zhou, Y. 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). source

      Extended Data Fig. 7 reports 9,019 astrocyte nuclei out of 66,311 total human nuclei, contrary to over 100,000 astrocyte nuclei in each brain region. The Online Methods report median UMIs and genes per nucleus, not the claimed average reads and genes. (LLM, conf=0.90)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • cites [12] Leng, K. et al. Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease. Nat. Neurosci. 24, 276–287 (2021). source

      The Results (page unavailable) report 42,528 nuclei from the entorhinal cortex and 63,608 from the superior frontal gyrus in total—not over 100,000 astrocyte nuclei in each region. The same passage describes transcript coverage as similar or superior to earlier AD datasets, not orders of magnitude higher; it does not establish the quoted read and gene averages. (LLM, conf=0.90)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • cites [13] Lau, S. F., Cao, H., Fu, A. K. Y. & Ip, N. Y. Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease. Proc. Natl Acad. Sci. USA 117, 25800–25809 (2020). source

      In Results, “Single-Nucleus Transcriptome Profiling of the Prefrontal Cortex in AD” (page unavailable), the paper reports 169,496 nuclei in total from prefrontal cortex samples, with astrocytes comprising 11.9% of those nuclei—not over 100,000 astrocyte nuclei in each brain region. It also says the mean numbers of transcripts and genes detected per nucleus were comparable to a previous study, contrary to the claimed orders-of-magnitude increase. The quoted averages of approximately 6,000 reads and 2,500 genes are not established by these passages. (LLM, conf=0.90)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • cites [14] Sadick, J. S. et al. Astrocytes and oligodendrocytes undergo subtype-specific transcriptional changes in Alzheimer’s disease. Neuron 110, 1788–1805 (2022). source

      The Results section reports that Sadick et al. captured 41,340 astrocyte nuclei across their final donor cohort, supporting its use as a comparison with a larger dataset. It does not establish that more than 100,000 nuclei per brain region is orders of magnitude higher than its dataset. The STAR METHODS section gives median counts and detected features for all nuclei, not the citing sentence’s average reads and genes for astrocytes. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [15] Smith, A. M. et al. Diverse human astrocyte and microglial transcriptional responses to Alzheimer’s pathology. Acta Neuropathol. 143, 75–91 (2022). source

      The Introduction and Results (page numbers not provided) report 52,706 astrocyte nuclei in total, not over 100,000 in each brain region. The Results give averages of 8,775 UMIs and 3,166 distinct genes per astrocyte nucleus, rather than the claimed approximately 6,000 reads and 2,500 genes. (LLM, conf=0.90)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • Rests on an assumption: Single-nucleus RNA sequencing of astrocyte nuclei accurately reflects the astrocyte transcriptome.

  • Classified as probably not a substantial claim.

    Premisecitation

    Astrocyte morphology changes near Aβ plaques and pTau NFTs.

    “Because astrocyte morphology changes near Aβ plaques and pTau NFTs23,24”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [23] Serrano-Pozo, A. et al. Reactive glia not only associates with plaques but also parallels tangles in Alzheimer’s disease. Am. J. Pathol. 179, 1373–1384 (2011). source

      The Spatial Relationships section (page unavailable) reports increased density of reactive astrocytes near dense-core plaques and NFTs. It does not report a change in astrocyte morphology near those lesions; the measured change was in reactive-cell density. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [24] Perez-Nievas, B. G. & Serrano-Pozo, A. Deciphering the astrocyte reaction in Alzheimer’s disease. Front Aging Neurosci. 10, 114 (2018). source

  • Classified as probably not a substantial claim.

    Premisecitation

    The five brain regions are hierarchically vulnerable to neurofibrillary degeneration in the order EC > ITG > PFC > V2 > V1.

    “we rank ordered the five brain regions based on their known vulnerability to neurofibrillary degeneration20,21 (that is, EC > ITG > PFC > V2 > V1)”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [20] Braak, H. & Braak, E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991). source
    • cites [21] Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H. & Del Tredici, K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404 (2006). source

  • Classified as probably not a substantial claim.

    Premisecitation

    Reactive astrogliosis may contribute to neurodegeneration through both gains of toxic functions and loss of normal functions.

    “the emerging view from experimental data is that reactive astrogliosis may contribute to neurodegeneration through both gains of toxic functions and loss of normal functions1.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [1] Escartin, C. et al. Reactive astrocyte nomenclature, definitions, and future directions. Nat. Neurosci. 24, 312–325 (2021). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Previous transcriptomic studies comparing AD mouse models have reported similarities and differences in astrocyte responses to Aβ plaques versus pTau NFTs.

    “Previous transcriptomic studies comparing AD mouse models have reported similarities and differences in astrocyte responses to Aβ plaques versus pTau NFTs5,7,33.”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites [5] Jiwaji, Z. et al. Reactive astrocytes acquire neuroprotective as well as deleterious signatures in response to Tau and Aβ pathology. Nat. Commun. 13, 135 (2022). source
    • cites [7] Wu, T. et al. Complement C3 is activated in human AD brain and is required for neurodegeneration in mouse models of amyloidosis and tauopathy. Cell Rep. 28, 2111–2123 (2019). source
    • cites [33] De Bastiani, M. A. et al. Hippocampal GFAP-positive astrocyte responses to amyloid and tau pathologies. Brain Behav. Immun. 110, 175–184 (2023). source

      The Introduction and results describe a transcriptomic comparison of hippocampal GFAP-positive astrocytes from PS2APP amyloidosis and Tau P301S mouse models, finding a small overlap of differentially expressed genes and distinct responses. The Discussion also reports inflammation-related changes in both models. The paper frames the comparison as Aβ versus tau pathology; the cited passages do not establish responses specifically to Aβ plaques versus phosphorylated-tau neurofibrillary tangles. (LLM, conf=0.82)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim.

    Premisecitation

    The primary visual cortex (V1) bears NFTs only in Braak NFT stage VI.

    “by definition, the primary visual cortex (V1 region) bears NFTs only in Braak NFT stage VI20,21”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [20] Braak, H. & Braak, E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991). source
    • cites [21] Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H. & Del Tredici, K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404 (2006). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Astrocytes are critical for maintaining brain homeostasis.

    “Astrocytes are critical for maintaining brain homeostasis2”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [2] Verkhratsky, A. & Nedergaard, M. Physiology of astroglia. Physiol. Rev. 98, 239–389 (2018). source

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    AD neuropathological changes (ADNC) are accompanied by a dramatic loss of synapses and neurons, as well as prominent morphological and functional changes of glial cells, collectively termed reactive gliosis.

    “These AD neuropathological changes (ADNC) are accompanied by a dramatic loss of synapses and neurons, as well as prominent morphological and functional changes of glial cells, collectively termed reactive gliosis1.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [1] Escartin, C. et al. Reactive astrocyte nomenclature, definitions, and future directions. Nat. Neurosci. 24, 312–325 (2021). source

      The paper’s “Morphology revisited” section describes changes in astrocyte branches in AD mouse models, and “From morphology to functional studies” describes altered reactive-astrocyte functions in AD models. Its discussion of gliosis also supports the general terminology. The cited passages do not establish the claimed dramatic loss of synapses and neurons accompanying AD neuropathological changes; pages are not available in our copy. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    All but one study had astTinf, and only the largest study (SEA-AD) had a sizable representation of the exhausted astMet subcluster.

    “Although all but one study10 had astTinf, only the largest study—the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD)17, performed in the middle temporal gyrus—had a sizable representation of the exhausted astMet subcluster.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [10] Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019). source
    • cites [17] Gabitto, M. I. et al. Integrated multimodal cell atlas of Alzheimeras disease. Nat. Neuro. https://doi.org/10.1038/s41593-024-01774-5 (2024). source

      The Results section identifies SEA-AD as an MTG atlas, and Fig. 4b depicts it as larger than the publicly available datasets. But the copy does not identify astTinf or astMet, or establish that only SEA-AD had a sizable astMet subcluster (searched: astTinf, astMet, exhausted astrocyte subcluster). (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Previous bulk transcriptomic analyses have highlighted energy metabolism deficits as a feature of AD and other neurodegenerative diseases.

    “previous bulk transcriptomic analyses have highlighted energy metabolism deficits as a feature of AD and other neurodegenerative diseases43,44”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [43] Noori, A., Mezlini, A. M., Hyman, B. T., Serrano-Pozo, A. & Das, S. Systematic review and meta-analysis of human transcriptomics reveals neuroinflammation, deficient energy metabolism, and proteostasis failure across neurodegeneration. Neurobiol. Dis. 149, 105225 (2021). source
    • cites [44] Noori, A., Mezlini, A. M., Hyman, B. T., Serrano-Pozo, A. & Das, S. Differential gene expression data from the human central nervous system across Alzheimer’s disease, Lewy body diseases, and the amyotrophic lateral sclerosis and frontotemporal dementia spectrum. Data Brief. 35, 106863 (2021). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Astrocytes have been reported to contribute to the (18F)FDG-PET signal via EAAT2/GLT-1, encoded by SLC1A2.

    “astrocytes have been reported to contribute to the (18F)fluoro-deoxy-glucose (FDG)–positron emission tomography (PET) signal via the glutamate transporter EAAT2/GLT-1, encoded by SLC1A2 (ref. 45)”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [45] Zimmer, E. R. et al. [18F]FDG PET signal is driven by astroglial glutamate transport. Nat. Neurosci. 20, 393–395 (2017). source

      The paper’s Abstract (page unavailable) reports that astrocytic glutamate transport via GLT-1 contributes to the [18F]FDG PET signal. Our copy does not identify GLT-1 as EAAT2 or state that it is encoded by SLC1A2, so those identifiers are not supported by this source. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Higher plasma GFAP levels have been associated with higher (18F)FDG-PET signals in early AD.

    “higher plasma GFAP levels have been associated with higher (18F)FDG–PET signals in early AD46”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [46] Salvadó, G. et al. Reactive astrogliosis is associated with higher cerebral glucose consumption in the early Alzheimer’s continuum. Eur. J. Nucl. Med. Mol. Imaging 49, 4567–4579 (2022). source

  • Classified as probably not a substantial claim.

    Premisecitation

    RORB had previously been identified by snRNA-seq as a marker gene for excitatory EC neurons that are vulnerable to NFTs and neurodegeneration in AD.

    “RORB had previously been identified by snRNA-seq as a marker gene for excitatory EC neurons that are vulnerable to NFTs and neurodegeneration in AD12”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [12] Leng, K. et al. Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease. Nat. Neurosci. 24, 276–287 (2021). source

  • May combine two claims.

    Premisecitation

    The distinguishing feature between Braak NFT stages V and VI is not just the presence of NFTs in V1, motor and sensory cortical areas, but more severe neurofibrillary degeneration and atrophy throughout the cortical mantle.

    “the distinguishing feature between Braak NFT stages V and VI is not just the presence of NFTs in the primary visual (V1), motor and sensory cortical areas, but more severe neurofibrillary degeneration21 and atrophy throughout the cortical mantle51”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [21] Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H. & Del Tredici, K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 112, 389–404 (2006). source
    • cites [51] La Joie, R. et al. Prospective longitudinal atrophy in Alzheimer’s disease correlates with the intensity and topography of baseline tau-PET. Sci. Transl. Med. 12, eaau5732 (2020). source

      The Results report cortical atrophy in patients with early-stage Alzheimer’s disease, and the Discussion reports an association between global cortical tau-PET signal and global cortical atrophy (pages unavailable). The paper does not compare Braak NFT stages V and VI or establish that more severe atrophy throughout the cortical mantle distinguishes them. Citation 51 is attached to the atrophy portion of the sentence, not the separate claim about neurofibrillary degeneration. (LLM, conf=0.79)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The study's sample sizes are similar to those reported in previous publications.

    “our sample sizes are similar to those reported in previous publications9–17”
    Quote in the paperNot a substantial claim8 of 9 sources checked
    • cites [9] Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019). source
    • cites [10] Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019). source
    • cites [11] Zhou, Y. 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). source
    • cites [12] Leng, K. et al. Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease. Nat. Neurosci. 24, 276–287 (2021). source
    • cites [13] Lau, S. F., Cao, H., Fu, A. K. Y. & Ip, N. Y. Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer’s disease. Proc. Natl Acad. Sci. USA 117, 25800–25809 (2020). source
    • cites [14] Sadick, J. S. et al. Astrocytes and oligodendrocytes undergo subtype-specific transcriptional changes in Alzheimer’s disease. Neuron 110, 1788–1805 (2022). source
    • cites [15] Smith, A. M. et al. Diverse human astrocyte and microglial transcriptional responses to Alzheimer’s pathology. Acta Neuropathol. 143, 75–91 (2022). source
    • cites [16] Dai, D. L., Li, M. & Lee, E. B. Human Alzheimer’s disease reactive astrocytes exhibit a loss of homeostastic gene expression. Acta Neuropathol. Commun. 11, 127 (2023). source
    • cites [17] Gabitto, M. I. et al. Integrated multimodal cell atlas of Alzheimeras disease. Nat. Neuro. https://doi.org/10.1038/s41593-024-01774-5 (2024). source

  • May combine two claims.

    Findingown data

    Gene set 1 was positively correlated with the pTau/tau ratio, whereas gene set 2 was negatively correlated with the pTau/tau ratio.

    “Interestingly, the gene set decreasing linearly from EC to V1 (gene set 1) was positively correlated with the pTau/tau ratio, whereas the one increasing from EC to V1 (gene set 2) was negatively correlated with the pTau/tau ratio”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The local Aβ plaque load and pTau/tau ratio measured in adjacent tissue samples reflect the local ADNC burden experienced by the astrocytes sequenced from the same brain region.

  • May combine two claims.

    Findingown data

    The last two spatial gene sets had relatively constant expression in EC, ITG and PFC, but either decreased (gene set 5) or increased (gene set 6) from PFC to V2 and V1.

    “The last two spatial gene sets exhibited relatively constant expression levels in EC, ITG and PFC, but either decreased (gene set 5) or increased (gene set 6) from the PFC to V2 and V1.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In V1 versus all other brain regions, CLU, GFAP and MAOB were upregulated, whereas AQP4 and GJA1 were downregulated.

    “Conversely, CLU, GFAP and MAOB were upregulated, whereas AQP4 and GJA1 were downregulated in V1 versus all other brain regions.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Single-nucleus RNA sequencing of astrocyte nuclei accurately reflects the astrocyte transcriptome.

  • May combine two claims.

    Findingown data

    In EC relative to other brain regions, APOE, APP, AQP4 and GJA1 were upregulated, whereas ALDH1L1, LRP1B, MAPT and SLC1A2 were downregulated.

    “Among other genes of interest, APOE, APP, AQP4 and GJA1 were upregulated, whereas ALDH1L1, LRP1B, microtubule-associated protein tau (MAPT) and SLC1A2 were downregulated in EC relative to the other brain regions.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Single-nucleus RNA sequencing of astrocyte nuclei accurately reflects the astrocyte transcriptome.

  • May combine two claims.

    Findingown data

    Only 18 of the 137 EC-upregulated genes were positively correlated with the pTau/tau ratio, and only 37 of 152 EC-downregulated genes were negatively correlated with the pTau/tau ratio.

    “Only 18 of the 137 EC-upregulated genes were positively correlated with the pTau/tau ratio (notably including cytoskeletal genes such as MAP2 and the master transcription factor regulating cholesterol metabolism, SREBF1), whereas only 37 of 152 EC-downregulated genes were negatively correlated with the pTau/tau ratio (including extracellular matrix/glycosaminoglycan metabolism genes, such as LARGE”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Single-nucleus RNA sequencing of astrocyte nuclei accurately reflects the astrocyte transcriptome.

  • May combine two claims.

    Findingown data

    The eight control donors had essentially no 3D6-positive Aβ plaques across the five brain regions and very low pTau/tau ratios except for the EC.

    “Our eight control donors provided a unique opportunity to examine regional differences in the astrocyte transcriptome in the normal aging brain because these donors had essentially no 3D6-positive Aβ plaques across the five brain regions and very low pTau/tau ratios except for the EC”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Two spatial gene sets changed monotonically along the network, either decreasing from EC to V1 (gene set 1) or increasing from EC to V1 (gene set 2).

    “Two spatial gene sets changed their expression level monotonically along the network, either decreasing from EC to V1 (gene set 1) or increasing from EC to V1 (gene set 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The pTau/tau ratio was highest in EC and followed the pattern EC > ITG > PFC > V2 > V1 across all stages.

    “By contrast, the pTau/tau ratio was highest in EC and demonstrated the expected pattern EC > ITG > PFC > V2 > V1 across all stages”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Gene set 3 was enriched in synapse-associated, cell-cell communication, and cytoskeletal genes distinct from those associated with pTau/tau ratio.

    “This gene set was enriched in synapse-associated (DISC1, GRIA4, GRID2 and SYNDIG1), cell–cell communication (APBB1IP, EFNA5, EPHA6 and SPP1) and cytoskeletal (SYNM and FMN1) genes that were distinct from those associated with the pTau/tau ratio (Fig. 3c).”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    The upregulated late gene program comprised genes involved in proteostasis/heat stress, protein translation, energy metabolism, mitochondrial electron transport chain, antioxidant defense, neuroinflammation including interferon response, cell-cell communication, lipid metabolism, cytoskeleton, extracellular matrix, synaptic function, and intracellular transport/trafficking.

    “The upregulated late gene program comprised genes involved in proteostasis/response to heat stress (AHSA1, BAG3, CCT4, CRYAB, DNAJA1, DNAJB1, DNAJB6, HSP90AA1, HSP90AB1, HSPA1A, HSPA1B, HSPA4, HSPA4L, HSPA8, HSPA9, HSPB1, HSPD1, HSPE1, HSPH1, MIB1, OTUD7B, SQSTM1, ST13, UBB, UBC, UBE2B and UBE2E2), protein translation (EEF1A1, EIF1, EIF2S2, RPL37A, RPL38, RPLP2, RPS21, RPS24 and RPS28), energy”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Two small clusters (astNeu and astMic) had genes typical of neurons and microglia and were considered hybrids or doublets despite low estimated doublet scores.

    “Two small clusters had genes typically found in other cell types, specifically neurons (astNeu) and microglia (astMic), and were considered hybrids or doublets (although their estimated doublet score was very low).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Gene set 4 (n = 120) lacks correlation with either Aβ or pTau levels, has highest expression levels in EC and V1, and is composed of genes related to cytoskeleton, lipid metabolism, calcium homeostasis, extracellular matrix, heat-shock proteins and antioxidant defense.

    “another sizable gene set (gene set 4, n = 120), characterized by its lack of correlation with either Aβ or pTau levels and highest expression levels in the EC and V1, was composed of genes related to the cytoskeleton (including GFAP), lipid metabolism (including APOE and CLU), calcium homeostasis, extracellular matrix, heat-shock proteins and antioxidant defense (for example, metallothioneins)”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    These 798 DEGs were grouped into six temporal gene sets with distinct temporal trajectories and variable strength of association with local Aβ and pTau levels.

    “These 798 DEGs were grouped into six different temporal gene sets with distinct temporal trajectories and variable strength of association with the local Aβ and pTau levels (Fig. 4 and Supplementary Data 5).”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The four pathology stages, based on cross-sectional CERAD NP scores and Braak NFT stages, represent the temporal progression of ADNC within a brain region.

  • May combine two claims.

    Findingown data

    Temporal gene set 6 had low expression at early and intermediate stages, peaked at late stage, and decreased at end stage without returning to baseline.

    “Finally, gene set 6 had low expression at early and intermediate stages, peaked at the late stage and decreased at the end stage without returning to baseline”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The four pathology stages, based on cross-sectional CERAD NP scores and Braak NFT stages, represent the temporal progression of ADNC within a brain region.

  • May combine two claims.

    Findingown data

    The proportion of homeostatic, intermediate and reactive astrocytes changed only along the spatial axis, whereas two other subclusters changed along the temporal axis.

    “The proportion of homeostatic, intermediate and reactive astrocytes changed only along the spatial axis, whereas two other subclusters changed along the temporal axis.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Temporal gene set 1 included trophic factors and their receptors, extracellular matrix, cytoskeleton, metal binding, antioxidant, pro-oxidant enzymes, neuroinflammation, calcium homeostasis, and phagocytosis genes.

    “This gene set included many trophic factors and their receptors (ANGPTL4, APC, EGLN3, FGF2, GFRA1, HGF, IGF1R, NRP1, NTRK3, TGFB2, TGFBR3 and VEGFA), extracellular matrix (GPC4, MATN2, SERPINA3, SERPINE2 and SPOCK1), cytoskeleton (ACTN1, FIGN, MACF1, MAPRE2, MAST4 and MYH9) and some metal binding (CP, FTL and MT2A), antioxidant (MGST1 and MSRA) but also pro-oxidant enzymes (MAOB), neuroin”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Temporal gene set 2 included trophic and survival factors, extracellular matrix, cytoskeleton, neuroinflammation, lipid metabolism, glycosaminoglycan metabolism, synapse-associated, and GPCR-mediated signaling genes.

    “This early gene program included trophic and survival factors (FGF1, FGF14, HIF1A and NRP2), extracellular matrix (GPC6, KAZN, LAMA4 and TNC), cytoskeleton (ABI1, CLIP1, MYO1E and VCL) and neuroinflammation (CHI3L1, IFI16, IL1R1, IL6R and RCAN1) genes, which differ from those predominant in the early ADNC stage. It also encompassed genes involved in lipid metabolism (ACSL3, ELOVL5, ELOVL6, LDLR, L”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    Some astrocyte subclusters are associated with age, with very small effect sizes (β = −0.008 to 0.004).

    “While some of the subclusters were associated with age, the effect sizes were very small (β = −0.008 to 0.004).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In AD cortex, reactive astrocyte markers show a gradient of expression from thioflavin-S-positive dense-core Aβ plaques to peri-plaque halo (≤50 μm) to distant areas (>50 μm), whereas no such gradient is observed around sham plaques in control cortex.

    “a spatial quantitative analysis centered in thioflavin-S-positive dense-core Aβ plaques demonstrated a gradient of expression of the reactive markers from the plaque to the peri-plaque halo (≤50 μm) to areas distant (>50 μm) from plaques in the AD cortex, whereas no effect of sham plaques was observed in control cortex”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    astMet is significantly associated with sex (higher frequency in female donors, P < 0.005), with a small effect size (β = 0.046).

    “only astMet was significantly associated with sex (higher frequency in female donors, P < 0.005), but the effect size was small (β = 0.046).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Gene set 4 was negatively correlated with both Aβ plaque burden and pTau/tau ratio, but statistical significance was lost after controlling for brain region.

    “While this gene set was negatively correlated with both Aβ plaque burden and pTau/tau ratio, the statistical significance was lost after controlling for brain region.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    HSPB1 expression in V2 astrocytes is highest in stage 3 and very low in stage 4.

    “confirmed the highest expression in stage 3 and very low expression in stage 4”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The proportion of homeostatic astH0 astrocytes is significantly reduced in EC versus all other regions but does not change with pathology stages.

    “the proportion of homeostatic astH0 astrocytes was significantly reduced in EC versus all other regions but did not change with pathology stages”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    astR1 and astR2 are enriched in GFAP, S100B, HSF1-mediated stress response, extracellular matrix, and oxidative stress genes, but differ in some marker genes.

    “astR1 and astR2 were enriched in GFAP, S100B, HSF1-mediated stress response (CRYAB, HSPA1B, HSPB8 and UBC), extracellular matrix (CD44, COL21A1, GPC6, LAMA4, SERPINA3, TNC and VCAN) and oxidative stress (MAOB), but differed in some other marker genes”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    astMet exhibits positive enrichment in temporal gene set 3 and negative enrichment of temporal gene set 4.

    “astMet exhibited a positive enrichment in temporal gene set 3 (characterized by upregulation of proteostasis, mitochondrial electron transport chain and metallothioneins in pathology stage 3 and normalization in pathology stage 4) and a negative enrichment of temporal gene set 4”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    astMet frequency is significantly increased in pathology stage 3 relative to stages 1 and 2, with a subsequent decrease in stage 4.

    “the significantly increased frequency of astMet in pathology stage 3 relative to pathology stages 1 and 2, with a subsequent decrease in pathology stage 4”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Gene set 5 was enriched in EC-low and V1-low genes, and gene set 6 was enriched in V1-high genes.

    “The gene set with relatively stable expression in EC through PFC and lower expression in V2 and V1 (gene set 5) was enriched in EC-low and V1-low genes, and the gene set with stable levels in EC through PFC but increase in V2 and V1 (gene set 6) was expectedly enriched in V1-high genes (Fig. 3b).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    An EC-specific astrocyte signature includes upregulation of APP and APOE and downregulation of SLC1A2 and MAPT relative to other cortical regions.

    “we identified an EC-specific astrocyte signature, which included changes in genes relevant to AD pathophysiology such as an upregulation of APP and APOE and a downregulation of SLC1A2 (encoding the glutamate transporter EAAT2, a.k.a. GLT-1) and MAPT (encoding the microtubule-associated protein tau) relative to other cortical regions”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Gene set 5 was positively correlated with both pTau/tau ratio and Aβ plaque burden, whereas gene set 6 was negatively correlated with both measures.

    “Finally, spatial gene set 5 was positively correlated with both pTau/tau ratio and Aβ plaque burden, whereas gene set 6 was negatively correlated with both measures”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The local Aβ plaque load and pTau/tau ratio measured in adjacent tissue samples reflect the local ADNC burden experienced by the astrocytes sequenced from the same brain region.

  • May combine two claims.

    Findingown data

    astR1 and astR2 reactive astrocytes are more frequent in EC and ITG, and astR1 frequency tends to increase with pathology stages.

    “both astR1 and astR2 reactive astrocytes were more frequent in EC and ITG, and the frequency of astR1 tended to increase with pathology stages”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Gene set 3 was not enriched in either EC or V1 signatures, whereas gene set 4 was enriched in EC-high and V1-high genes.

    “The gene set specifically upregulated in PFC (gene set 3) was not enriched in either EC or V1 signatures, whereas the gene set specifically downregulated in PFC was enriched in EC-high and V1-high genes.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Subcluster astR0 exhibits a reactive phenotype and is further enriched in extracellular matrix genes.

    “Subcluster astR0 also exhibited a reactive phenotype and was further enriched in extracellular matrix genes (COL21A1, COL24A1, COLGAT and LAMA2).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Temporal gene sets 3 and 4 either peaked or dropped at late stage but returned to near baseline at end stage.

    “Two other temporal gene sets either peaked (gene set 3) or dropped (gene set 4) at the late stage (moderate/frequent NPs, Braak NFT stage V) but surprisingly returned to near baseline at end stage (moderate/frequent NPs, Braak NFT stage VI)”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The four pathology stages, based on cross-sectional CERAD NP scores and Braak NFT stages, represent the temporal progression of ADNC within a brain region.

  • May combine two claims.

    Findingown data

    The proportion of reactive astR0 astrocytes increases in parallel with pathology stages and decreases along brain regions from EC to V1.

    “The proportion of reactive astR0 astrocytes increased in parallel with pathology stages and decreased along brain regions from EC to V1.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Gene set 1 was significantly enriched in EC-high and V1-low genes, whereas gene set 2 was significantly enriched in EC-low and V1-high genes.

    “Specifically, the gene set with monotonic decrease from EC to V1 (gene set 1) was significantly enriched in EC-high and V1-low genes, whereas the gene set with monotonic increase from EC to V1 (gene set 2) was significantly enriched in EC-low and V1-high genes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Reactive subclusters (astR0, astR1, astR2) have positive enrichment for spatial gene set 1 (positively correlated with pTau) and spatial gene set 4 (stress chaperones/heat-shock response genes), and negative enrichment for spatial gene set 2 (negatively correlated with pTau); astH0 shows the opposite effects.

    “the reactive subclusters had a positive enrichment score for spatial gene set 1 (positively correlated with pTau) as well as spatial gene set 4 (stress chaperones/heat-shock response genes) and a negative enrichment score for spatial gene set 2 (negatively correlated with pTau), whereas the homeostatic subcluster astH0 demonstrated the opposite effects”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The frequency of astIM declines along the spatial axis but is reduced only in pathology stage 3.

    “the frequency of astIM declined along the spatial axis but was reduced only in pathology stage 3”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Homeostatic astH0 astrocytes also transition to astMet and astTinf, which appear to be terminal states with no further progression into the reactive subclusters.

    “the homeostatic astH0 astrocytes also transitioned to astMet and astTinf, which appeared to be terminal states with no further progression into the reactive subclusters”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Reactive astrocytes represent less than 25% of all astrocyte nuclei and express higher levels of aquaporins, heat-shock proteins, extracellular matrix and cytoskeletal genes.

    “reactive astrocytes represent less than 25% of all astrocyte nuclei and express higher levels of aquaporins, heat-shock proteins, extracellular matrix and cytoskeletal genes”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Homeostatic astrocytes constitute the majority of the astrocyte population, regardless of the severity of AD pathology, and express higher levels of typical homeostatic genes such as glutamate metabolism-related genes.

    “homeostatic astrocytes constitute the majority of the astrocyte population, regardless of the severity of AD pathology, and express higher levels of typical homeostatic genes such as glutamate metabolism-related genes”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Astrocytes may have a key role in synaptic dysfunction and the trans-synaptic propagation of pTau between excitatory neurons along vulnerable AD neural networks.

    “these results could be indicating that astrocytes, as part of the tripartite excitatory synapses, have a key role in synaptic dysfunction and the trans-synaptic propagation of pTau between excitatory neurons along vulnerable AD neural networks”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    astMet and astTinf are distinct subclusters that deviate from the prototypical homeostatic-to-reactive transition path.

    “astMet and astTinf are distinct subclusters that deviate from the prototypical homeostatic-to-reactive transition path”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    astMet are exhausted astrocytes, undergoing exhaustion (failure in proteostasis and energy metabolism) after prolonged exposure to ADNC (Braak stage VI).

    “these data suggest that astMet are undergoing exhaustion, that is, failure in proteostasis and energy metabolism, after prolonged exposure to ADNC (Braak stage VI).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Our data confirm that astrocytes, in addition to neurons, suffer mitochondrial dysfunction and energy deficits that contribute to observed bulk RNA changes and could potentially contribute to clinical progression.

    “Our data confirm that astrocytes, in addition to neurons, suffer mitochondrial dysfunction and energy deficits that contribute to these observed bulk RNA changes and could also potentially contribute to clinical progression.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The higher interdonor variability possibly reflects differences in the duration of each stage across donors.

    “possibly reflecting differences in the duration of each stage across donors.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Reactive astrocytes may initially increase their metabolic rate but finally fail to meet their energy needs and contribute to the typical bilateral temporoparietal hypometabolism observed in AD.

    “reactive astrocytes may initially increase their metabolic rate but finally fail to meet their energy needs and contribute to the typical bilateral temporoparietal hypometabolism observed in AD”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Astrocyte transcriptomic changes along AD progression are dynamic, complex and nonlinear.

    “Together, these results underscore the dynamic, complex and nonlinear pattern of astrocyte transcriptomic changes along AD progression”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    astMet and astTinf are unique terminal subclusters with a complex, stage-dependent response to ADNC.

    “These findings indicate that astMet and astTinf are unique terminal subclusters with a complex, stage-dependent response to ADNC”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Gene sets 5 and 6 likely represent ADNC-associated pan-reactive upregulated and downregulated signatures, respectively.

    “likely representing ADNC-associated pan-reactive upregulated and downregulated signatures, respectively.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    There are two terminal states that are off-pathway from prototypical astrocyte reactivity, including a previously unrecognized exhausted state.

    “uncovering two terminal states that are off-pathway the prototypical astrocyte reactivity, including a previously unrecognized exhausted state”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    These astrocyte transcriptomic changes are partly associated with local levels of Aβ plaques and/or pTau and partly explained by region-specific microenvironmental factors.

    “and suggest that these astrocyte transcriptomic changes are partly associated with the local levels of Aβ plaques and/or pTau and partly explained by region-specific microenvironmental factors.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Data were analyzed using mixed-effects models with diagnosis and location as fixed effects and donor ID as random effect to account for within-donor correlation.

    “Data were analyzed running mixed-effects models with diagnosis and location as fixed effects and donor ID as random effect to account for within-donor correlation.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Batch effects due to technical variation were corrected using Harmony.

    “Batch effects due to technical variation were corrected using the RunHarmony function in Harmony (v.0.1.1) package64, with the top 20 principal components as input.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    In plaque-centered quantitative analyses, plaque selection was blind to the expression level of the reactive astrocyte marker of interest.

    “in each AD donor, n = 50 Thioflavin-S-positive dense-core plaques were randomly selected and outlined throughout all layers of the cortical ribbon in the green channel being blindfolded to the expression level of the reactive astrocyte marker of interest in the red channel.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Low-quality cells were removed using thresholds of fewer than 200 genes, greater than 20,000 UMIs, and/or greater than 15% mitochondrial genes.

    “For each brain region, we removed cells with fewer than 200 genes, greater than 20,000 unique molecular identifiers (UMIs) and/or greater than 15% mitochondrial genes”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    After filtering, donor-specific effects and percentage of mitochondrial genes were regressed out via canonical correlation analysis.

    “After filtering, a second round of integration was performed via canonical correlation analysis to regress out donor-specific effects as well as the percentage of mitochondrial genes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    No randomization was performed.

    “no randomization was performed”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Tissue used for snRNA-seq was selected to have RIN ≥ 5.

    “RIN value was measured from 130 donors, of which 83 met the selected cut-off of RIN ≥ 5.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Statistical analyses of plaque-centered data used mixed-effects models controlling for donor ID.

    “Statistical analyses were conducted with mixed-effects models with area fraction of the reactive marker as the dependent variable, diagnosis (control versus AD) and location (sham or Thioflavin-S-positive plaque, ≤50 μm halo, or >50 μm) as fixed effects and controlling for donor ID (random effect).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    astMet corresponds to the exhausted astrocytes whose proportion and gene expression program peak in AD late stage (Braak stage V) and normalize in end stage (Braak stage VI).

    “corresponds to the exhausted astrocytes whose proportion and gene expression program peak in AD late stage (Braak stage V) and normalize in end stage (Braak stage VI)”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Data collection and analysis were not performed blind to neuropathological diagnosis.

    “Data collection and analysis were not performed blind to neuropathological diagnosis.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    No donors or samples were excluded from the analysis.

    “No donors or samples were excluded from the analysis.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Astrocyte nuclei were identified by high expression of ADGRV1, ALDH1L1, AQP4 and GFAP.

    “Astrocyte nuclei were identified by their high expression of ADGRV1, ALDH1L1, AQP4 and GFAP.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    No statistical methods were used to predetermine sample sizes.

    “No statistical methods were used to predetermine sample sizes”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    Significance was evaluated by a two-sided Welch's t test, and P values were adjusted using the Benjamini-Hochberg method to correct for multiple comparisons when two or more comparisons were conducted within studies.

    “Significance was evaluated by a two-sided Welch’s t test. P values were adjusted using the Benjamini–Hochberg method to correct for multiple comparisons when two or more comparisons were conducted within studies.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Donors were selected based on their global AD neuropathological burden.

    “Donors were selected based on their global AD neuropathological burden”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Donor-specific effects were removed using reciprocal principal component analysis (rPCA) integration.

    “used reciprocal principal component analysis (rPCA) integration based on the top 2,000 highly variable genes (HVGs) to remove donor-specific effects using the Seurat R package (v.4.3.0)60.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Multiplex fluorescence immunohistochemistry images in Figs. 2c and 5d and Supplementary Figs. 5, 6 and 7 have the same display settings across brain regions and diagnoses.

    “Multiplex fluorescence immunohistochemistry images in Figs. 2c and 5d as well as Supplementary Figs. 5, 6 and 7 have the same display settings across brain regions and diagnoses.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The effects of age and sex on cell subcluster frequency were modeled using multiple linear regression.

    “The effects of factors such as age and sex on cell subcluster frequency across samples were modeled using multiple linear regression with the formula: frequency ~1 + pTau/tau + region + sex + age + pTau/tau × sex + pTau/tau × region.”
    Quote in the paperNot a substantial claim
84 of 84

  • The paper relies on this without support.

    The four pathology stages, based on cross-sectional CERAD NP scores and Braak NFT stages, represent the temporal progression of ADNC within a brain region.

    “To reflect the progression of ADNC, we then grouped the 32 donors into four pathology stages based on their global semiquantitative measures of neuritic plaques (Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuritic plaque (NP) score) and NFTs (Braak NFT stages) complemented with these immunohistochemical and biochemical quantitative measures of local Aβ and pTau burdens.”

  • The paper relies on this without support.

    The local Aβ plaque load and pTau/tau ratio measured in adjacent tissue samples reflect the local ADNC burden experienced by the astrocytes sequenced from the same brain region.

    “Because astrocyte morphology changes near Aβ plaques and pTau NFTs23,24, we quantified the local burden of ADNC in adjacent tissue samples by measuring the 3D6-positive Aβ-immunoreactive percentage area fraction via immunohistochemistry and the pTau/total tau ratio via ELISA.”

  • The paper relies on this without support.

    Single-nucleus RNA sequencing of astrocyte nuclei accurately reflects the astrocyte transcriptome.

    “Astrocyte nuclei were identified by the expression levels of the marker genes ADGRV1 (refs. 13,22), ALDH1L1, aquaporin-4 (AQP4) and GFAP (Fig. 1c)”

  • The authors state this as an assumption.

    Autopsy findings of ADNC severity can be temporally ordered.

    “Assuming that autopsy findings of ADNC severity can be temporally ordered, which is well supported by the PET imaging biomarker literature”

  • The paper relies on this without support.

    The five brain regions can be rank ordered along a spatial axis following the typical hierarchical progression of AD.

    “When we rank ordered the five brain regions along a spatial axis following the typical hierarchical progression of AD”

  • The paper relies on this without support.

    Cross-sectional Braak NFT stages in donor brains can be interpreted as a temporal progression of ADNC exposure.

    “our five-region snRNA-seq study of astrocytes from 32 donors spanning the normal aging-severe AD continuum”

  • The paper relies on this without support.

    snRNA-seq clusters and pseudotime/RNA velocity trajectories correspond to actual astrocyte state transitions in vivo.

    “uncovers the existence of intermediate states that appear to be transitional between homeostatic and reactive astrocytes”

  • The paper relies on this without support.

    Postmortem brain tissue transcriptomes reflect antemortem astrocyte biology.

    “Frozen (−80 °C) brain specimens from 32 participants were obtained from the Massachusetts Alzheimer’s Disease Research Center (MADRC) Brain Bank”
8 of 8

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • This astrocyte subcluster was enriched for genes involved in extracellular matrix organization, metabolic support, and inflammatory modulation.

    “This subcluster was enriched for genes involved in extracellular matrix organization [102, 135, 136], metabolic support [135, 137], and inflammatory modulation [138–141].”

    From Tau Ablation Rewires Brain Cell Programs in Health and Restores Function in Disease (2026) · cites this paper as [135]

    The Results section on astrocyte clustering reports extracellular-matrix enrichment in astTinf and glucose-metabolism genes in astMet, but does not place both features in the same subcluster. In the citing sentence, this source is attached to extracellular matrix organization and metabolic support, not to inflammatory modulation. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Abstract says reactive and intermediate subclusters change only spatially

    Major

    The abstract says these subclusters change only along the spatial axis, but the results report pathology-stage changes in both reactive astR0 and intermediate astIM astrocytes.

  • Stage 1 pTau values do not follow the stated regional ordering

    Minor

    The text says ITG has a higher pTau/tau ratio than PFC at every stage, but Table 1 reports 0.343 for ITG and 0.348 for PFC at stage 1.

  • Clustering is described as producing both nine and ten subclusters

    Minor

    The results describe nine astrocyte subclusters, while the Fig. 5 caption says the same clustering produced ten.

  • Stage 2 has conflicting Braak-stage labels

    Minor

    Table 1 labels pathology stage 2 as Braak II/III, whereas the Fig. 7 caption labels the corresponding 39 present-study samples as Braak III-IV; Fig. 6 identifies 39 samples as stage 2.

4 of 4

Cites

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2 of the 77 references couldn’t be matched to a known paper.

Cited by

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Related

Authors
Serrano-Pozo, A., Li, H., Li, Z., Muñoz-Castro, C., Jaisa-aad, M., Healey, M. A., Welikovitch, L. A., Jayakumar, R., Bryant, A. G., Noori, A., Connors, T. R., Hu, M., Zhao, K., Liao, F., Lin, G., Pastika, T., Tamm, J., Abdourahman, A., Kwon, T., Bennett, R. E., Woodbury, M. E., Wachter, A., Talanian, R. V., Biber, K., Karran, E. H., Hyman, B. T., & Das, S.
Affiliations
  • Harvard University (US)
  • Massachusetts General Hospital (US)
  • AbbVie (United States) (US)
  • AbbVie (Germany) (DE)
Corresponding author
Das, Sudeshna
ORCID
Venue
Nature Neuroscience
Publisher
Springer Science and Business Media LLC
Published
2024-11-11
Volume
27
Issue
12
Pages
2384-2400
ISSN
  • 1097-6256 (ISSN-L)
  • 1546-1726
DOI
10.1038/s41593-024-01791-4
PMC
PMC11614739
OpenAlex
W4404224839
Cited by
140
References
77
Citations by year
2026: 87 · 2025: 51 · 2023: 2
FWCI
32.04
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Neuroscience (publishedVersion, cc-by-nc-nd)
  • Research Square (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
Funders
  • Massachusetts Life Sciences Center (Neuroscience Consortium award)
  • Alzheimer’s Association (AACF-17-524184, AACF-17-524184-RAPID)
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
astrocytes, Alzheimer's disease, single-nucleus RNA sequencing, reactive astrocytes, brain regions, neuropathology, transcriptional programs
MeSH terms
Aged, Aged, 80 and over, Alzheimer Disease, Astrocytes, Brain, Female, Humans, Male, Middle Aged, Disease Progression, Transcriptome

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-27.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-27.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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