Abstract
INTRODUCTION: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection. METHODS: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts. RESULTS: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10 −3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia= 2.59). DISCUSSION: Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk. Highlights: We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.
| Original language | English |
|---|---|
| Pages (from-to) | 6682-6698 |
| Number of pages | 17 |
| Journal | Alzheimer's & Dementia |
| Volume | 20 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - Oct 2024 |
Keywords
- Alzheimer's disease
- DNA methylation
- Parkinson's disease
- aging
- dementia
- epigenetics
- machine learning
- mild cognitive impairments
- risk prediction
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