Aging the Brain: Multi-Region Methylation Principal Component Based Clock in the Context of Alzheimer’s Disease

Abstract

Alzheimer’s disease (AD) risk increases exponentially with age and is associated with multiple molecular hallmarks of aging, one of which is epigenetic alterations. Epigenetic age predictors based on 5’ cytosine methylation (DNAm) have previously suggested that biological age acceleration may occur in AD brain tissue. To further investigate brain epigenetic aging in AD, we generated a novel age predictor termed PCBrainAge that was trained solely in cortical samples. This predictor utilizes a combination of principal components analysis and regularized regression, which reduces technical noise and greatly improves test-retest reliability. For further testing, we generated DNAm data from multiple brain regions in a sample from the Religious Orders Study and Rush Memory & Aging Project. PCBrainAge captures meaningful heterogeneity of aging, calculated according to an individual’s age acceleration beyond expectation. Its acceleration demonstrates stronger associations with clinical AD dementia, pathologic AD, and APOE ε4 carrier status compared to extant epigenetic age predictors. It does so across multiple cortical and subcortical regions. Overall, PCBrainAge is useful for investigating heterogeneity in brain aging, as well as epigenetic alterations underlying AD risk and resilience.