A global view of aging and Alzheimer’s pathogenesis-associated cell population dynamics and molecular signatures in human and mouse brains
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Abstract
Conventional methods fall short in unraveling the dynamics of rare cell types related to aging and diseases. Here we introduce EasySci, an advanced single-cell combinatorial indexing strategy for exploring age-dependent cellular dynamics in the mammalian brain. Profiling approximately 1.5 million single-cell transcriptomes and 400,000 chromatin accessibility profiles across diverse mouse brains, we identified over 300 cell subtypes, uncovering their molecular characteristics and spatial locations. This comprehensive view elucidates rare cell types expanded or depleted upon aging. We also investigated cell-type-specific responses to genetic alterations linked to Alzheimer’s disease, identifying associated rare cell types. Additionally, by profiling 118,240 human brain single-cell transcriptomes, we discerned cell- and region-specific transcriptomic changes tied to Alzheimer’s pathogenesis. In conclusion, this research offers a valuable resource for probing cell-type-specific dynamics in both normal and pathological aging.
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A comprehensive molecular characterization of region-specific differences in Alzheimer's disease is currently lacking.
“Although some brain regions relevant to AD have been studied individually at scale or jointly in samples from a few individuals8–16, a comprehensive molecular characterization of region-specific differences in AD is currently lacking”
From Single-cell multiregion dissection of Alzheimer’s disease (2024) · cites this paper as [16]
The Main section says prior studies sampled brain cell populations relatively shallowly, supporting a general gap in comprehensive characterization. The Results section identifies region-specific AD gene signatures in two human brain regions, but the paper does not explicitly say that a comprehensive molecular characterization of region-specific differences in AD is currently lacking. No page numbers are available in our copy. (LLM, conf=0.77)
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Cites
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Sorted by citations
Single-cell multiregion dissection of Alzheimer’s disease
Mathys, H., Boix, C. A., Akay, L. A., Xia, Z., Davila-Velderrain, J., Ng, A. P., Jiang, X., Abdelhady, G., Galani, K., Mantero, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07606-7 · Cited by 343 · see citing works
A panoramic view of cell population dynamics in mammalian aging
Zhang, Z., Schaefer, C., Jiang, W., Lu, Z., Lee, J., Sziraki, A., Abdulraouf, A., Wick, B., Haeussler, M., Li, Z., et al. (2025) · Science · doi:10.1126/science.adn3949 · Cited by 95 · see citing works
Self-citationXu, Z., Sziraki, A., Lee, J., Zhou, W., & Cao, J. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01948-9 · Cited by 52 · see citing works
Self-citation
- Authors
- Sziraki, A., Lu, Z., Lee, J., Banyai, G., Anderson, S., Abdulraouf, A., Metzner, E., Liao, A., Banfelder, J., Epstein, A., Schaefer, C., Xu, Z., Zhang, Z., Gan, L., Nelson, P. T., Zhou, W., & Cao, J.
- ORCID
- Venue
- Nature Genetics
- Published
- 2023-11-30
- Volume
- 55
- Issue
- 12
- Pages
- 2104-2116
- ISSN
- 1061-4036
- 1546-1718
- PMC
- PMC10703679
- Cited by
- 100
- References
- 23
- Language
- en
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.
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.
What counts as a claim ›How we measure confidence ›How we check this ›
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