Cellular dynamics across aged human brains uncover a multicellular cascade leading to Alzheimer’s disease
Open accessAbstract
Alzheimer’s Disease (AD) is a progressive neurodegenerative disease seen with advancing age. Recent studies have revealed diverse AD-associated cell states, yet when and how they impact the causal chain leading to AD remains unknown. To reconstruct the dynamics of the brain’s cellular environment along the disease cascade and to distinguish between AD and aging effects, we built a comprehensive cell atlas of the aged prefrontal cortex from 1.64 million single-nucleus RNA-seq profiles. We associated glial, vascular and neuronal subpopulations with AD-related traits for 424 aging individuals, and aligned them along the disease cascade using causal modeling. We identified two distinct lipid-associated microglial subpopulations, one contributed to amyloid-β proteinopathy while the other mediated the effect of amyloid-β in accelerating tau proteinopathy, as well as an astrocyte subpopulation that mediated the effect of tau on cognitive decline. To model the coordinated dynamics of the entire cellular environment we devised the BEYOND methodology which uncovered two distinct trajectories of brain aging that are defined by distinct sequences of changes in cellular communities. Older individuals are engaged in one of two possible trajectories, each associated with progressive changes in specific cellular communities that end with: (1) AD dementia or (2) alternative brain aging. Thus, we provide a cellular foundation for a new perspective of AD pathophysiology that could inform the development of new therapeutic interventions targeting cellular communities, while designing a different clinical management for those individuals on the path to AD or to alternative brain aging.
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The pseudobulk snRNAseq data analyzed were generated from DLPFC (BA9) brain tissue from 131 AD and 162 NCI ROSMAP participants.
“These data were generated from brain tissue (DLPFC, BA9) from 131 AD and 162 NCI ROSMAP participants.”
From INPP5D regulates inflammasome activation in human microglia (2023) · cites this paper as [36]
The cell-atlas section (page unavailable) confirms that the paper generated snRNA-seq data from DLPFC tissue of ROSMAP participants. It reports 465 profiled participants, while the Methods section reports 424 retained for downstream analyses. Our copy does not establish that the cited data were a pseudobulk subset from BA9 comprising 131 AD and 162 NCI participants. (LLM, conf=0.86)
Experimental — accuracy not yet measuredRNA levels of INPP5D are elevated in Alzheimer's disease brain.
“confirm previous findings that RNA levels of INPP5D are elevated in AD brain21.”
From INPP5D regulates inflammasome activation in human microglia (2023) · cites this paper as [36]
The section “Two distinct disease-associated microglial subpopulations” reports RNA expression of CPM, TPRG1, and MRC1, but does not report whether INPP5D RNA is elevated in AD brain. Searches for INPP5D and SHIP1 found no passage in our copy addressing that comparison. The retrieved passages have no page numbers. (LLM, conf=0.70)
Experimental — accuracy not yet measuredPseudobulk snRNAseq comparison of AD microglia with LP-NCI microglia yielded 260 DEGs at q < 0.05.
“This analysis yielded 260 DEGs (q < 0.05; Fig. 7j, Supplementary Data 19).”
From INPP5D regulates inflammasome activation in human microglia (2023) · cites this paper as [36]
The ‘Two distinct disease-associated microglial subpopulations’ section describes gene-expression differences between Mic.12, Mic.13 and other microglia, but does not report the claimed AD-versus-LP-NCI pseudobulk comparison or 260 DEGs at q < 0.05. Searches for ‘260,’ ‘LP-NCI,’ and ‘pseudobulk’ found no passage establishing that result; the indexed passages provide no page numbers. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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Cited by
Sorted by citations
INPP5D regulates inflammasome activation in human microglia
Chou, V., Pearse, R. V., Aylward, A. J., Ashour, N., Taga, M., Terzioglu, G., Fujita, M., Fancher, S. B., Sigalov, A., Benoit, C. R., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42819-w · Cited by 79 · see citing works
Self-citation
- Authors
- Green, G. S., Fujita, M., Yang, H.-S., Taga, M., McCabe, C., Cain, A., White, C. C., Schmidtner, A. K., Zeng, L., Wang, Y., Regev, A., Menon, V., Bennett, D. A., Habib, N., & De Jager, P. L.
- Affiliations
- Hebrew University of Jerusalem (IL)
- Brigham and Women's Hospital (US)
- Broad Institute (US)
- Columbia University Irving Medical Center (US)
- Rush University Medical Center (US)
- Corresponding author
- Habib, Naomi
- ORCID
- Venue
- Alzheimer s & Dementia
- Publisher
- openRxiv
- Published
- 2023-03-09
- Volume
- 19
- Issue
- S24
- ISSN
- 1552-5260 (ISSN-L)
- PMC
- PMC10028913
- OpenAlex
- W4390191939
- Cited by
- 51
- References
- 5
- Citations by year
- 2026: 3 · 2025: 15 · 2024: 23 · 2023: 10
- FWCI
- 4.63
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Alzheimer s & Dementia (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- Rush University
- Israel Science Foundation
- National Institutes of Health (AG015819)
- National Institute on Aging (U01AG046152, R01AG015819, U01AG061356, K23AG062750, R01AG066831, RF1AG057473, U01AG072572, P30AG072975)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, brain aging
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