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Background: DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, hasshown promise for Alzheimer’s disease (AD) prediction.Objective: Testing long-term predictive ability (>15 years) of existing DNAm-based epigenetic age acceleration (EAA)measures and identifying novel early blood-based DNAm AD-prediction biomarkers.

Methods: EAA measures calculated from Illumina EPIC data from blood were tested with linear mixed-effects models(LMMs) in a longitudinal case-control sample (50 late-onset AD cases; 51 matched controls) with prospective data up to 16years before clinical onset, and post-onset follow-up. NovelDNAmbiomarkers were generated with epigenome-wide LMMs,and Sparse Partial Least Squares Discriminant Analysis applied at pre- (10–16 years), and post-AD-onset time-points.

Results: EAA did not differentiate cases from controls during the follow-up time (p > 0.05). Three new DNA biomarkersshowed in-sample predictive ability on average 8 years pre-onset, after adjustment for age, sex, and white blood cell proportions(p-values: 0.022-<0.00001). Our longitudinally-derived panel replicated nominally (p = 0.012) in an external cohort (n = 146cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOE 4-carriership(OR = 1.38 per 1 SD DNAmscore increase versus OR= 13.58 for 4-allele carriage; AUCs = 77.2% versus 87.0%). Literaturereview showed low overlap (n = 4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with ouridentified CpGs.

Conclusion: The limited predictive value of EAA for AD extends prior findings by considering a longer follow-up time, andwith appropriate control for age, sex, APOE, and blood-cell proportions. Results also highlight challenges with replicatingdiscriminatory or predictive CpGs across studies.