Blood DNA methylation signatures predict clinical progression in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study

Blood-based biomarkers are emerging as promising tools for the early detection and monitoring of Alzheimer’s disease (AD). However, peripheral DNA methylation signatures have shown limited and inconsistent associations with diagnostic status in cross-sectional studies. Whether blood DNA methylation captures dynamic processes related to disease progression remains unclear. We analyzed genome-wide DNA methylation profiles from peripheral blood samples of 639 individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including cognitively normal (CN), mild cognitive impairment (MCI), and AD participants. Epigenome-wide differential methylation analyses were performed across diagnostic groups. To investigate prognostic value, we applied Cox proportional hazards models to assess the association between CpG methylation and time to clinical conversion from CN or MCI to AD. In addition, we evaluated the relationship between CpG methylation and plasma biomarkers in a subset of individuals with matched data. Cross-sectional analyses did not identify differentially methylated positions after multiple testing correction, consistent with prior studies. In contrast, survival analyses revealed specific CpG sites significantly associated with risk of clinical conversion, highlighting methylation patterns with prognostic relevance rather than diagnostic discrimination. Higher epigenetic age was consistently associated with increased conversion risk across multiple clocks. Integrative analyses identified CpG sites associated with plasma p-tau217 levels, with two loci remaining independently associated after multivariable adjustment. Our results suggest that peripheral blood DNA methylation is more informative as a prognostic marker of disease progression than as a cross-sectional diagnostic biomarker in AD. Longitudinal and survival-based approaches appear to better capture biologically relevant epigenetic variation associated with clinical trajectories and may indicate dynamic indicators of disease progression. Integration of methylation markers with established biomarkers such as p-tau217 may then improve risk stratification.