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Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum
Muhammad Ali, Jigyasha Timsina, Daniel Western, Menghan Liu, Aleksandra Beric, John Budde, Anh N. Do, Gyujin Heo et al.. Neuron, 2025-03-14
Topic: Amyloid, tau and blood-test diagnosis
Changes in β-amyloid (Aβ) and hyperphosphorylated tau (T) in brain and cerebrospinal fluid (CSF) precede Alzheimer's disease (AD) symptoms, making the CSF proteome a potential avenue to understand disease pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 analytes (2,029 unique proteins) dysregulated in AD. Of these, 865 (43%) were previously reported, and 1,164 (57%) are novel. The identified proteins cluster in four different pseudo-trajectories groups spanning the AD continuum and were enriched in pathways including neuronal death, apoptosis, and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfunction (mid stages), brain plasticity and longevity (mid stages), and microglia-neuron crosstalk (late stages). Using machine learning, we created and validated highly accurate and replicable (area under the curve [AUC] > 0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD.
Key findings
- Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 analytes (2,029 unique proteins) dysregulated in AD.
- Of these, 865 (43%) were previously reported, and 1,164 (57%) are novel.
- The identified proteins cluster in four different pseudo-trajectories groups spanning the AD continuum and were enriched in pathways including neuronal death, apoptosis, and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfunction (mid stages), brain plasticity and longevity (mid stages), and microglia-neuron crosstalk (late stages).
- Using machine learning, we created and validated highly accurate and replicable (area under the curve [AUC] > 0.90) models that predict AD biomarker positivity and clinical status.
- These models can also identify people that will convert to AD.
Why it matters
By analyzing cerebrospinal fluid proteins across the Alzheimer's disease continuum, this study identified over 2,000 proteins that are dysregulated and grouped them into stages involving processes like neuronal death, microglial changes, and brain plasticity. Machine learning models built from these proteins predicted Alzheimer's biomarker status and clinical status with high accuracy and could identify people who would later convert to Alzheimer's disease.
Study details
- Study designmeta-analysis
- Evidence strengthHigh
How this study scored 73/100
Published in a peer-reviewed journal, and it is a meta-analysis pooling many studies. Scored zero for sample size, effect reported and studied in people because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Neuron) |
| Journal's citation record | 4 / 4 | Neuron: journal h-index 689 (OpenAlex, 2026-10-29) |
| Study design | 12 / 12 | A meta-analysis pooling many studies |
| Strength of evidence | 5 / 5 | Rated “high” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 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 | A review of other studies — randomisation is not credited here |
| Times cited | 4 / 7 | Cited 61 times (OpenAlex, 2026-10-10) |
| Citations per year | 4 / 5 | 20.3 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 5 / 6 | Cited 33.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 5 other studies in this library |
| Still being cited | 3 / 4 | Cited 61 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Carlos C Cruchaga: h-index 102 (OpenAlex, whole career) |
| Institution's track record | 3 / 3 | Stanford University: institution h-index 2,684 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40088886) |
| Free to read | 2 / 2 | Free to read |
| Total | 73 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
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's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Ali, M., Timsina, J., Western, D., Liu, M., Beric, A., Budde, J., et al. (2025). Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum. Neuron. https://doi.org/10.1016/j.neuron.2025.02.014
Vancouver
Ali M, Timsina J, Western D, Liu M, Beric A, Budde J, et al. Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum. Neuron. 2025. doi:10.1016/j.neuron.2025.02.014. PMID: 40088886.
BibTeX
@article{ali2025-40088886,
author = {Ali, Muhammad and Timsina, Jigyasha and Western, Daniel and Liu, Menghan and Beric, Aleksandra and Budde, John and Do, Anh N. and Heo, Gyujin and others},
title = {{Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum}},
journal = {Neuron},
year = {2025},
doi = {10.1016/j.neuron.2025.02.014},
pmid = {40088886},
url = {https://doi.org/10.1016/j.neuron.2025.02.014}
}
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