Home › Research › Long-term cohort studies
Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease
Guo Y, Chen SD, You J, Huang SY, Chen YL, Zhang Y, Wang LB, He XY et al.. Nature human behaviour, 2024-07-10
Topic: Amyloid, tau and blood-test diagnosis
Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively.
Key findings
- Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD.
- Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively.
- Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers.
- Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline.
Why it matters
This study analyzed cerebrospinal fluid proteins and found that YWHAG and multi-protein panels diagnosed Alzheimer's disease with high accuracy, validated in an independent cohort and against autopsy-confirmed cases. It is a biomarker study for diagnosis and prediction, not a treatment or cure.
Study details
- Effect sizeAUC = 0.969; AUC = 0.857
- Evidence strengthModerate
How this study scored 52/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Nature human behaviour) |
| Journal's citation record | 2 / 4 | Nature Human Behaviour: journal h-index 180 (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 | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2024 — 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 | 3 / 3 | Effect reported with a statistic (interval, p-value, ratio or similar) |
| 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 | 4 / 7 | Cited 68 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 17.0 citations a year over 4 year(s) since 2024 |
| Impact for its field and year | 4 / 6 | Cited 18.5× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 4 other studies in this library |
| Still being cited | 3 / 4 | Cited 68 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Jin‐Tai Yu: h-index 39 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Fudan University: institution h-index 954 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 38987357) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 52 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
May need a subscription OpenAlex found no free copy of the full text (checked 6 Feb 1020), so the publisher may charge for it. The PubMed abstract is free.
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
Guo, Y., Chen, S. D., You, J., Huang, S. Y., Chen, Y. L., Zhang, Y., et al. (2024). Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease. Nature human behaviour. https://doi.org/10.1038/s41562-024-01924-6
Vancouver
Guo Y, Chen SD, You J, Huang SY, Chen YL, Zhang Y, et al. Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease. Nature human behaviour. 2024. doi:10.1038/s41562-024-01924-6. PMID: 38987357.
BibTeX
@article{guo2024-38987357,
author = {Guo, Y. and Chen, S. D. and You, J. and Huang, S. Y. and Chen, Y. L. and Zhang, Y. and Wang, L. B. and He, X. Y. and others},
title = {{Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease}},
journal = {Nature human behaviour},
year = {2024},
doi = {10.1038/s41562-024-01924-6},
pmid = {38987357},
url = {https://doi.org/10.1038/s41562-024-01924-6}
}
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here. Showing 12 of 14.
Later studies that cite this one
4 studies in the alzhub library list this one in their references.
Related studies in Long-term cohort studies
Also tagged “biomarkers”
821 studies in the library carry the topic tag “biomarkers”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 821 tagged studies.