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Association Between Plasma Metabolomic Profile and Machine Learning‐Based Brain Age
Yang Li, Jiao Wang, Yuyang Miao, Michelle M. Dunk, Yan Liu, Zhongze Fang, Qiang Zhang, Weili Xu. Aging Cell, 2025-09-01
Topic: Brain proteins, microglia and lab models
Metabolomics has been associated with cognitive decline and dementia, but the relationship between metabolites and brain aging remains unclear. We aimed to investigate the associations of metabolomics with brain age assessed by neuroimaging and to explore whether these relationships vary according to apolipoprotein E (APOE) ε4. This study included 17,770 chronic brain disorder-free participants aged 40-69 years from UK Biobank who underwent neuroimaging scans an average of 9 years after baseline. A total of 249 plasma metabolites were measured using nuclear magnetic resonance spectroscopy at baseline. Brain age was estimated using LASSO regression and 1079 brain MRI phenotypes and brain age gap (BAG; i.e., brain age minus chronological age) was calculated. Data were analyzed using linear regression. We identified 64 and 77 metabolites associated with brain age and BAG, respectively, of which 55 overlapped. Lipids (including cholesterol, cholesteryl esters, free cholesterol, phospholipids, and total lipids) in S/M-HDL, as well as phospholipids and triglycerides as a percentage of total lipids in different-density lipoproteins, were associated with larger BAG. The percentages of cholesterol, cholesteryl esters, and free cholesterol to total lipids in VLDL, LDL, and HDL of different particle sizes were associated with smaller BAG. The associations of LA/FA, omega-6/FA, SFA/FA, and phospholipids to total lipids in L-HDL with brain age were consistent across APOE ε4 carriers and non-carriers (all p for interaction > 0.05). Plasma metabolites show remarkably widespread associations with brain aging regardless of APOE ε4 genetic risk. Metabolic profiles could serve as an early indicator of accelerated brain aging.
Key findings
- Metabolomics has been associated with cognitive decline and dementia, but the relationship between metabolites and brain aging remains unclear.
- We identified 64 and 77 metabolites associated with brain age and BAG, respectively, of which 55 overlapped.
- Lipids (including cholesterol, cholesteryl esters, free cholesterol, phospholipids, and total lipids) in S/M-HDL, as well as phospholipids and triglycerides as a percentage of total lipids in different-density lipoproteins, were associated with larger BAG.
- The percentages of cholesterol, cholesteryl esters, and free cholesterol to total lipids in VLDL, LDL, and HDL of different particle sizes were associated with smaller BAG.
Why it matters
In 17,770 participants free of chronic brain disorders, 64 and 77 plasma metabolites were associated with brain age and brain age gap, with lipids among those linked to larger or smaller gaps. This identifies associations between metabolites and brain aging, not a treatment, cure or prevention.
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Study details
- Participants17,770
- Evidence strengthLow
How this study scored 46/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Aging Cell) |
| Journal's citation record | 2 / 4 | Aging Cell: journal h-index 216 (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 | 1 / 5 | Rated “low” 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 | 4 / 4 | 17,770 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 | 1 / 7 | Cited 4 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.3 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 1.0× 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 | 1 / 4 | Cited 4 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Weili Xu: h-index 57 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Karolinska Institutet: institution h-index 1,477 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 6 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40888555) |
| Free to read | 2 / 2 | Free to read |
| Total | 46 / 100 | — |
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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 names 8 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
Li, Y., Wang, J., Miao, Y., Dunk, M. M., Liu, Y., Fang, Z., et al. (2025). Association Between Plasma Metabolomic Profile and Machine Learning‐Based Brain Age. Aging Cell. https://doi.org/10.1111/acel.70208
Vancouver
Li Y, Wang J, Miao Y, Dunk MM, Liu Y, Fang Z, et al. Association Between Plasma Metabolomic Profile and Machine Learning‐Based Brain Age. Aging Cell. 2025. doi:10.1111/acel.70208. PMID: 40888555.
BibTeX
@article{li2025-40888555,
author = {Li, Yang and Wang, Jiao and Miao, Yuyang and Dunk, Michelle M. and Liu, Yan and Fang, Zhongze and Zhang, Qiang and Xu, Weili},
title = {{Association Between Plasma Metabolomic Profile and Machine Learning‐Based Brain Age}},
journal = {Aging Cell},
year = {2025},
doi = {10.1111/acel.70208},
pmid = {40888555},
url = {https://doi.org/10.1111/acel.70208}
}
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