ArticleAging cell2025
Association Between Plasma Metabolomic Profile and Machine Learning-Based Brain Age.
Article in Aging cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Associations of Iron Indicators with Cognitive Impairment Risk in Postmenopausal Women: Evidence from a Matched Case-Control Study and Back Propagation Neural Network Model.Molecular neurobiology · 2026Article
- Metabolomic signatures of brain aging: A multimodal and genetic study.Molecular psychiatry · 2026Article
- Lipid Metabolism Reprogramming in the Aging Brain: Glial-Mediated Pathogenic Mechanisms and Translational Strategies in Neurodegeneration.International journal of molecular sciences · 2026Review
- Association of glymphatic function with 40-Hz neural oscillations, systemic metabolic markers, and cognitive performance in healthy aging adults: An EEG and MRI study.Translational psychiatry · 2026Article
- Association Between Plasma Metabolomic Profile and Machine Learning-Based Brain Age.Aging cell · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
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.
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Registered trials
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