| Title: | Plasma proteomics-based brain aging signature and incident dementia risk |
| Journal: | GeroScience |
| Published: | 12 Nov 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39532828/ |
| DOI: | https://doi.org/10.1007/s11357-024-01407-6 |
Publication 14151
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Abstract
Investigating brain-enriched proteins with machine learning methods may enable a brain-specific understanding of brain aging and provide insights into the molecular mechanisms and pathological pathways of dementia. The study aims to analyze associations of brain-specific plasma proteomic aging signature with risks of incident dementia. In 45,429 dementia-free UK Biobank participants at baseline, we generated a brain-specific biological age using 63 brain-enriched plasma proteins with machine learning methods. The brain age gap was estimated, and Cox proportional hazards models were used to study the association with incident all-cause dementia, Alzheimer's disease (AD), and vascular dementia. Per-unit increment in the brain age gap z-score was associated with significantly higher risks of all-cause dementia (hazard ratio [95% confidence interval], 1.67 [1.56-1.79], P < 0.001), AD (1.85 [1.66-2.08], P < 0.001), and vascular dementia (1.86 [1.55-2.24], P < 0.001), respectively. Notably, 2.1% of the study population exhibited extreme old brain aging defined as brain age gap z-score > 2, correlating with over threefold increased risks of all-cause dementia and vascular dementia (3.42 [2.25-5.20], P < 0.001, and 3.41 [1.05-11.13], P = 0.042, respectively), and fourfold increased risk of AD (4.45 [2.32-8.54], P < 0.001). The associations were stronger among participants with healthier lifestyle factors (all P-interaction < 0.05). These findings were corroborated by magnetic resonance imaging assessments showing that a higher brain age gap aligns global pathophysiology of dementia, including global and regional atrophy in gray matter, and white matter lesions (P < 0.001). The brain-specific proteomic age gap is a powerful biomarker of brain aging, indicative of dementia risk and neurodegeneration.</p>
18 Keywords
- Aged
- Aged, 80 and over
- Aging
- Alzheimer Disease
- Biomarkers
- Brain
- Dementia
- Dementia, Vascular
- Female
- Humans
- Incidence
- Machine Learning
- Male
- Middle Aged
- Proportional Hazards Models
- Proteomics
- Risk Factors
- United Kingdom
5 Authors
- Minghao Kou
- Hao Ma
- Xuan Wang
- Yoriko Heianza
- Lu Qi
1 Application
| Application ID | Title |
|---|---|
| 29256 | Study of gene-environment interaction and Mendelian randomization of obesity and cardiometabolic risk |
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