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Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants
Qiang YX, You J, He XY, Guo Y, Deng YT, Gao PY, Wu XR, Feng JF et al.. Alzheimer's research & therapy, 2024-01-22
Topic: Risk, prevention and care in population studies
Background Blood-based biomarkers for dementia are gaining attention due to their non-invasive nature and feasibility in regular healthcare settings. Here, we explored the associations between 249 metabolites with all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VaD) and assessed their predictive potential. Methods This study included 274,160 participants from the UK Biobank. Cox proportional hazard models were employed to investigate longitudinal associations between metabolites and dementia. The importance of these metabolites was quantified using machine learning algorithms, and a metabolic risk score (MetRS) was subsequently developed for each dementia type. We further investigated how MetRS stratified the risk of dementia onset and assessed its predictive performance, both alone and in combination with demographic and cognitive predictors. Results During a median follow-up of 14.01 years, 5274 participants developed dementia. Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD. Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance. Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile. When MetRS was combined with demographic and cognitive predictors, the model yielded the area under the receiver operating characteristic curve (AUC) values of 0.857 for ACD, 0.861 for AD, and 0.873 for VaD. Conclusions We conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.
Key findings
- Results During a median follow-up of 14.01 years, 5274 participants developed dementia.
- Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD.
- Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance.
- Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile.
- Conclusions We conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.
Why it matters
In 274,160 UK Biobank participants, 143 of 249 metabolites were significantly associated with incident all-cause dementia, and a metabolic risk score stratified dementia risk. This is about predicting risk, not about treating, curing or preventing dementia.
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Study details
- Study designlongitudinal study
- Participants274,160
- Evidence strengthModerate
How this study scored 65/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Alzheimer's research & therapy) |
| Journal's citation record | 1 / 4 | Alzheimer s Research & Therapy: journal h-index 146 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| 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 | 4 / 4 | 274,160 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 56 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 14.0 citations a year over 4 year(s) since 2024 |
| Impact for its field and year | 4 / 6 | Cited 15.2× 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 56 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Jin‐Tai Yu: h-index 94 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Fudan University: institution h-index 954 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 8 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 38254212) |
| Free to read | 2 / 2 | Free to read |
| Total | 65 / 100 | — |
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Read the original
- DOI: 10.1186/s13195-023-01379-3
- PubMed: 38254212
- Original source →
- Free full text: Alzheimer s Research & Therapy →
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
Qiang, Y. X., You, J., He, X. Y., Guo, Y., Deng, Y. T., Gao, P. Y., et al. (2024). Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants. Alzheimer's research & therapy. https://doi.org/10.1186/s13195-023-01379-3
Vancouver
Qiang YX, You J, He XY, Guo Y, Deng YT, Gao PY, et al. Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants. Alzheimer's research & therapy. 2024. doi:10.1186/s13195-023-01379-3. PMID: 38254212.
BibTeX
@article{qiang2024-38254212,
author = {Qiang, Y. X. and You, J. and He, X. Y. and Guo, Y. and Deng, Y. T. and Gao, P. Y. and Wu, X. R. and Feng, J. F. and others},
title = {{Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants}},
journal = {Alzheimer's research \& therapy},
year = {2024},
doi = {10.1186/s13195-023-01379-3},
pmid = {38254212},
url = {https://doi.org/10.1186/s13195-023-01379-3}
}
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