Sixteen-year longitudinal evaluation of blood-based DNA methylation biomarkers for early prediction of Alzheimer’s disease

Abstract

Abstract Background: DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, has shown promise for 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 16 years before clinical onset, and post-onset follow-up. Novel DNAm biomarkers 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-values>0.05). Three new DNA biomarkers showed 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=146 cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOEε4-carriership (OR=1.38 per 1 SD DNAm score increase vs. OR=13.58 for ε4-allele carriage; AUCs=77.2% vs. 87.0%). Literature review showed low overlap (n=4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with our identified CpGs. Conclusions: The limited predictive value of EAA for AD extends prior findings by considering a longer follow-up time, and with appropriate control for age, sex, APOE, and blood-cell proportions. Results also highlight challenges with replicating discriminatory or predictive CpGs across studies.