What Metabolic Aging Says About Dementia Risk

May 28, 2026

The Pathologist

Overview

A blood-based metabolomic aging clock, termed 'MileAge', was linked to increased dementia risk and earlier onset in a UK Biobank study involving 223,496 participants. The findings suggest that metabolomic profiling could identify individuals at risk of dementia before symptoms appear.

Background

Cognitive decline during aging significantly impacts health, with midlife cognitive capabilities serving as predictors for future dementia risk. The prevalence of Alzheimer's disease is projected to rise dramatically, with estimates suggesting it will reach 13.8 million cases among individuals aged 65 and older by 2060, underscoring the need for early identification and intervention strategies.

Data Highlights

Measure	Findings
MileAge delta	Higher scores linked to increased dementia risk
Follow-up duration	Median of 13.7 years
Dementia cases	3,976 individuals developed dementia
APOE ε4 alleles	Elevated MileAge scores increased risk over 10-fold

Key Findings

The MileAge model was based on 168 plasma metabolites measured by NMR, including lipids, lipoproteins, and amino acids.
Higher MileAge scores correlated with increased risk of vascular dementia, unspecified dementia, and all-cause dementia.
Inflammatory biomarker GlycA was associated with higher vascular dementia risk.
Several lipid and lipoprotein markers were linked to lower dementia risk.
Individuals with elevated MileAge and two APOE ε4 alleles had significantly higher dementia risk.
Specific metabolite groups linked to the MileAge model included branched-chain amino acids and inflammatory markers.

Clinical Implications

The MileAge measure may serve as a valuable tool for identifying individuals at risk of dementia, potentially allowing for earlier intervention. Clinicians should consider incorporating specific metabolic profiling methods, such as NMR analysis, in assessments for dementia risk, especially in patients with genetic predispositions.

Conclusion

The study highlights the potential of metabolomic aging as a predictive tool for dementia risk, emphasizing the importance of early identification in clinical practice and its relevance to current dementia prevention strategies.