Huang, KunRobling, Charles OliverFadel, WilliamJohnson, Travis2025-08-052025-08-052025-07https://hdl.handle.net/1805/49962https://doi.org/10.7912/FZXM-4Z98IUIAlzheimer’s Disease is a progressive neurodegenerative disease resulting in impaired cognition and function. The prevalence of Alzheimer’s Disease has increased steadily in the United States as the average lifespan has risen. Previous research has suggested that aging patterns are not identical for each person due to Various epigenetic clock models have been made to assess the biological or metabolic age of a person, regardless of chronological age based on DNA methylation gene expression values. For the benefit of this analysis, we propose using epigenetic aging algorithms in estimating biological age in postmortem patients and merging this data with Alzheimer’s Disease data, exploring various correlations and relationships. The results show that the biological age is not a significant predictor of Alzheimer’s Disease diagnosis.en-USCC0 1.0 UniversalBiostatisticsAlgorithmEpigentic AgingBiological AgeMethylationThesis