| Title: | Dementia risk across distinct metabolic profiles in the UK Biobank |
| Journal: | GeroScience |
| Published: | 28 Nov 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41315132/ |
| DOI: | https://doi.org/10.1007/s11357-025-01970-6 |
| URL: | https://link.springer.com/content/pdf/10.1007/s11357-025-01970-6.pdf |
Publication 17284
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Abstract
Sub-optimal metabolism is linked to dementia risk, yet metabolic traits rarely occur in isolation. Using data from 308,019 UK Biobank participants, we examined associations of six diverse metabolic subgroups (I-VI) - previously derived via a self-organising map (SOM) that captures patterns of co-occurring metabolic biomarker traits in the population - and 39 individual biomarkers, with incident all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD). Biomarker associations were assessed using both linear and nonlinear (restricted cubic spline) models. After adjusting for age, sex, socioeconomic, and lifestyle factors, subgroup analyses showed that participants in the two leanest and two most adipose subgroups had higher risk of dementia outcomes compared to others. Subgroups with high adiposity exhibited elevated VaD risk, which was linked to hypertension, hyperglycaemia, and liver stress (Subgroup II); inflammation, microalbuminuria, and low apolipoprotein A1 (III). For AD, the risk was elevated in the lean subgroups (IV, V), characterised by low body mass index (BMI), triglycerides, and urate, and high sex-hormone binding globulin; as well as for adipose Subgroup II. APOE-ε4 allele count had limited influence on dementia associations with metabolic subgroups and biomarkers. This marked metabolic heterogeneity in dementia risk suggests that metabolic profiling could inform targeted prevention strategies. Interpretation of these findings is supported by previously reported MRI profiles of the metabolic subgroups, providing biological context.</p>
3 Authors
- Amanda L. Lumsden
- Anwar Mulugeta
- Elina Hyppönen
1 Application
| Application ID | Title |
|---|---|
| 89630 | Improving disease risk prediction and prevention |
Enabling scientific discoveries that improve human health