Abstract
Abnormal DNA methylation patterns have been demonstrated to be associated with the pathogenesis of Alzheimer's disease (AD). The present study aimed to identify differential methylation in the superior temporal gyrus (STG) of patients with late-onset AD based on epigenome-wide DNA methylation data by bioinformatics analysis. The genome-wide DNA methylation data in the STG region of 34 patients with late-onset AD and 34 controls without dementia were recruited from the Gene Expression Omnibus database. Through systemic quality control, differentially methylated CpG sites were determined by the Student's t-test and mean methylation value differences between the two conditions. Hierarchical clustering analysis was applied to assess the classification performance of differentially methylated CpGs. Functional analysis was performed to investigate the biological functions of the genes associated with differentially methylated CpGs. A total of 17,895 differentially methylated CpG sites were initially identified, including 11,822 hypermethylated CpGs and 6,073 hypomethylated CpGs. Further analysis examined 2,211 differentially methylated CpGs (covering 1,991 genes). AD subjects demonstrated distinctive DNA methylation patterns when compared with the controls, with a classification accuracy value of 1. Hypermethylation was mainly detected for genes regulating the cell cycle progression, whereas hypomethylation was observed in genes involved in transcription factor binding. The present study demonstrated widespread and distinctive DNA methylation alterations in late-onset AD. Identification of AD-associated epigenetic biomarkers may allow for the development of novel diagnostic and therapeutic targets.