ArticleScientific reports2021
Brain age estimation at tract group level and its association with daily life measures, cardiac risk factors and genetic variants.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 17 citations in OpenAlex.
- Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes.npj aging · 2026Article
- The impact of balance exercise on brain age and brain morphometry: insights from MRI analysis.Aging clinical and experimental research · 2026Observational
- [Research progress in electroencephalogram-based brain age prediction].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Review
- A review of artificial intelligence-based brain age estimation and its applications for related diseases.Briefings in functional genomics · 2025Review
- Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer's Disease in the UK Biobank.Biological psychiatry global open science · 2024Article
- Histopathologic brain age estimation via multiple instance learning.Acta neuropathologica · 2023Article
- Brain-wide associations between white matter and age highlight the role of fornix microstructure in brain ageing.Human brain mapping · 2023Article
- Ischemic Heart Disease and Vascular Risk Factors Are Associated With Accelerated Brain Aging.JACC. Cardiovascular imaging · 2023Article
- Conceptual Overview of Biological Age Estimation.Aging and disease · 2023Article
- A systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility.Patterns (New York, N.Y.) · 2023Review
- Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Bio-psycho-social factors' associations with brain age: a large-scale UK Biobank diffusion study of 35,749 participants.Frontiers in psychology · 2023Article
- Neuroimaging-Based Brain Age Estimation: A Promising Personalized Biomarker in Neuropsychiatry.Journal of personalized medicine · 2022Review
- Telomere length is causally connected to brain MRI image derived phenotypes: A mendelian randomization study.PloS one · 2022Article
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Authors and funding
10 authors at 5 institutions in 3 countries.
Funding
Abstract
Brain age can be estimated using different Magnetic Resonance Imaging (MRI) modalities including diffusion MRI. Recent studies demonstrated that white matter (WM) tracts that share the same function might experience similar alterations. Therefore, in this work, we sought to investigate such issue focusing on five WM bundles holding that feature that is Association, Brainstem, Commissural, Limbic and Projection fibers, respectively. For each tract group, we estimated brain age for 15,335 healthy participants from United Kingdom Biobank relying on diffusion MRI data derived endophenotypes, Bayesian ridge regression modeling and 10 fold-cross validation. Furthermore, we estimated brain age for an Ensemble model that gathers all the considered WM bundles. Association analysis was subsequently performed between the estimated brain age delta as resulting from the six models, that is for each tract group as well as for the Ensemble model, and 38 daily life style measures, 14 cardiac risk factors and cardiovascular magnetic resonance imaging features and genetic variants. The Ensemble model that used all tracts from all fiber groups (FG) performed better than other models to estimate brain age. Limbic tracts based model reached the highest accuracy with a Mean Absolute Error (MAE) of 5.08, followed by the Commissural ([Formula: see text]), Association ([Formula: see text]), and Projection ([Formula: see text]) ones. The Brainstem tracts based model was the less accurate achieving a MAE of 5.86. Accordingly, our study suggests that the Limbic tracts experience less brain aging or allows for more accurate estimates compared to other tract groups. Moreover, the results suggest that Limbic tract leads to the largest number of significant associations with daily lifestyle factors than the other tract groups. Lastly, two SNPs were significantly (p value [Formula: see text]) associated with brain age delta in the Projection fibers. Those SNPs are mapped to HIST1H1A and SLC17A3 genes.
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