Association of epigenetic age acceleration with MRI biomarkers of aging and Alzheimer's disease neurodegeneration
McEvoy, L. K.; Zhang, B.; Nguyen, S.; Maihofer, A. X.; Nievergelt, C. M.; Ramon, C.; Horvath, S.; Lu, A. T.; Davatzikos, C.; Erus, G.; Resnick, S. M.; Espeland, M. A.; Rapp, S. R.; Beckman, K.; Ferrucci, L.; LaCroix, A. Z.; Shadyab, A. H.
Show abstract
Epigenetic clocks of biological aging have been associated with cognitive impairment and dementia. Less is known about whether they are associated with an older-appearing brain or with an atrophy pattern associated with dementia. We examined associations of five epigenetic clocks measured at baseline with the Spatial Pattern of Atrophy for Recognition of Brain Aging (SPARE-BA) and the Alzheimers Disease Pattern Similarity Score (AD-PS) derived from structural MRIs obtained an average of 8 years later among 1,196 older women. Using linear regression models adjusting for relevant covariates, we observed no associations between any epigenetic clock and accelerated brain aging based on SPARE-BA. We observed a significant association between AgeAccelGrim2 and AD-PS ({beta} = 0.015; 95% CI 0.004 to 0.027; p = 0.01). This association appeared to be primarily driven by the association of a DNA methylation marker of smoking pack years with frontal and temporal lobe volumes. AgeAccelGrim2 was not associated with volumes in regions implicated in early AD (hippocampus and entorhinal cortex). Taken together with prior findings, these results suggest that measures of epigenetic and brain age acceleration capture different aspects of biological aging, and that AgeAccelGrim2 is predictive of neurodegenerative changes associated with smoking that increase risk of dementia.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Effect of Pathway-specific Polygenic Risk Scores for Alzheimer’s Disease (AD) on Rate of Change in Cognitive Function and AD-related Biomarkers among Asymptomatic Individuals 95%
- Inferring Alzheimer’s disease pathologic traits from clinical measures in living adults 95%
- Inflammation in Alzheimer's disease: do sex and APOE matter? 94%
Similar papers in this journal
- Deep Learning Chest X-Ray Age, Epigenetic Aging Clocks and Associations with Age-Related Subclinical Disease in the Project Baseline Health Study 95%
- DunedinPACE Predicts Incident Metabolic Syndrome: Cross-sectional and Longitudinal Data from the Berlin Aging Study II (BASE-II) 94%
- Multiomic clocks to predict phenotypic age in mice 93%
Similar papers in this journal
- Relationship between five Epigenetic Clocks, Telomere Length and Functional Capacity assessed in Older Adults: Cross-sectional and Longitudinal Analyses 96%
- Evaluation of epigenetic and metabolomic biomarkers indicating biological age 96%
- Expression of Exosome Biogenesis Genes is Pervasively Altered by Aging in the Mouse and in the Human Brain During Alzheimer’s Disease 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.