ArticleDiabetes, obesity & metabolism2023
Metabolic profile-based subgroups can identify differences in brain volumes and brain iron deposition.
Article in Diabetes, obesity & metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Dementia risk across distinct metabolic profiles in the UK Biobank.GeroScience · 2026Article
- Socio-environmental and health-related factors and their association with longitudinal change in brain neuroimaging markers through the plasma metabolome among UK adults: An additive Bayesian network analysis.Brain, behavior, & immunity - health · 2025Article
- Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes.Journal of translational medicine · 2024Article
- Metabolomic age and risk of 50 chronic diseases in community-dwelling adults: A prospective cohort study.Aging cell · 2024Article
- Trace Elements in Alzheimer's Disease and Dementia: The Current State of Knowledge.Journal of clinical medicine · 2024Review
- Higher baseline resting metabolic rate is associated with 1-year frailty decline among older adults residing in an urban area.BMC geriatrics · 2023Article
- Metabolic profile-based subgroups can identify differences in brain volumes and brain iron deposition.Diabetes, obesity & metabolism · 2023Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
aimsTo evaluate associations of metabolic profiles and biomarkers with brain atrophy, lesions, and iron deposition to understand the early risk factors associated with dementia. MATERIALS AND
methodsUsing data from 26 239 UK Biobank participants free from dementia and stroke, we assessed the associations of metabolic subgroups, derived using an artificial neural network approach (self-organizing map), and 39 individual biomarkers with brain MRI measures: total brain volume (TBV), grey matter volume (GMV), white matter volume (WMV), hippocampal volume (HV), white matter hyperintensity (WMH) volume, and caudate iron deposition.
resultsIn metabolic subgroup analyses, participants characterized by high triglycerides and liver enzymes showed the most adverse brain outcomes compared to the healthy reference subgroup with high-density lipoprotein cholesterol and low body mass index (BMI) including associations with GMV (β
conclusionsMetabolic profiles were associated differentially with brain neuroimaging characteristics. Associations of BMR, BP and other individual biomarkers may provide insights into actionable mechanisms driving these brain associations.
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