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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. [ABSTRACT FROM AUTHOR]

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., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)