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Single-cell transcriptomic analysis of Alzheimer’s disease
Hansruedi Mathys, José Dávila-Velderrain, Zhuyu Peng, Fan Gao, Shahin Mohammadi, Jennie Z. Young, Madhvi Menon, Liang He, Fatema Abdurrob, Xueqiao Jiang, Anthony J. Martorell, Richard M. Ransohoff, Brian P. Hafler, David Alan Bennett, Manolis Kellis, Li‐Huei Tsai. Nature, 2019-05-01
Topic: Amyloid, tau and blood-test diagnosis
This study analyzed 80,660 single-nucleus transcriptomes from the prefrontal cortex of 48 individuals with varying degrees of Alzheimer's disease pathology to examine molecular and cellular changes across six major brain cell types. The researchers identified transcriptionally distinct cell subpopulations associated with pathology, early cell-type-specific disease changes, late-stage global stress responses, and distinct transcriptional responses between sexes. They also observed recurrent perturbations in myelination-related processes across multiple cell types.
Key findings
- Across six major brain cell types, we identified transcriptionally distinct subpopulations, including those associated with pathology and characterized by regulators of myelination, inflammation, and neuron survival.
- The strongest disease-associated changes appeared early in pathological progression and were highly cell-type specific, whereas genes upregulated at late stages were common across cell types and primarily involved in the global stress response.
- Female cells were overrepresented in disease-associated subpopulations, and transcriptional responses were substantially different between sexes in several cell types, including oligodendrocytes.
- Myelination-related processes were recurrently perturbed in multiple cell types, suggesting that myelination has a key role in Alzheimer's disease pathophysiology.
Why it matters
Reports a single-cell transcriptomic analysis of Alzheimer's disease.
How this study scored 64/100
Published in a top-tier journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on strength of evidence, so that was left out: it earned 61 of the 95 points we could judge it on, which is 64 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 10 / 10 | Tier 1 — top-tier general journal (Nature) |
| Journal's citation record | 4 / 4 | Nature: journal h-index 1,841 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | — / 5 | No evidence rating recorded — left out of this score |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2019 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 7 / 7 | Cited 2,566 times (OpenAlex, 2026-10-10) |
| Citations per year | 5 / 5 | 285.1 citations a year over 9 year(s) since 2019 |
| Impact for its field and year | 6 / 6 | Cited 77.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 4 / 4 | Cited 1,132 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Li‐Huei Tsai: h-index 131 (OpenAlex, whole career) |
| Institution's track record | 3 / 3 | Harvard University: institution h-index 3,235 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 31042697) |
| Free to read | 2 / 2 | Free to read |
| Points | 61 / 95 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 61 of the 95 points we could judge it on is 64 out of 100. |
| Total | 64 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1038/s41586-019-1195-2
- PubMed: 31042697
- Original source →
- Free full text: Research Explorer (The University of Manchester) →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 16 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Mathys, H., Dávila-Velderrain, J., Peng, Z., Gao, F., Mohammadi, S., Young, J. Z., et al. (2019). Single-cell transcriptomic analysis of Alzheimer’s disease. Nature. https://doi.org/10.1038/s41586-019-1195-2
Vancouver
Mathys H, Dávila-Velderrain J, Peng Z, Gao F, Mohammadi S, Young JZ, et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature. 2019. doi:10.1038/s41586-019-1195-2. PMID: 31042697.
BibTeX
@article{mathys2019-31042697,
author = {Mathys, Hansruedi and Dávila-Velderrain, José and Peng, Zhuyu and Gao, Fan and Mohammadi, Shahin and Young, Jennie Z. and Menon, Madhvi and He, Liang and Abdurrob, Fatema and Jiang, Xueqiao and Martorell, Anthony J. and Ransohoff, Richard M. and Hafler, Brian P. and Bennett, David Alan and Kellis, Manolis and Tsai, Li‐Huei},
title = {{Single-cell transcriptomic analysis of Alzheimer’s disease}},
journal = {Nature},
year = {2019},
doi = {10.1038/s41586-019-1195-2},
pmid = {31042697},
url = {https://doi.org/10.1038/s41586-019-1195-2}
}
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