DNA methylation in peripheral blood leukocytes in late onset Alzheimer's disease

Abstract

Background: Chronic systemic inflammation is implicated in Alzheimer's disease (AD) pathogenesis and has measurable effects on blood cells. There is increasing interest in non-invasive diagnostic tools that use blood-based biomarkers for AD, such as DNA methylation. Notably, DNA methylation changes in blood are also linked to systemic inflammation. The evaluation of DNA methylation profiles in peripheral blood leukocytes as potential biomarkers for AD is promising.

Objective: To determine DNA methylation patterns in blood for AD, and to explore specific blood CpG sites that act as surrogates for brain-tissue methylation.

Methods: DNA methylation data from peripheral blood leukocytes of AD patients and controls were obtained from the Gene Expression Omnibus (GSE59685 and GSE53740). Differential methylation analysis was performed for individual CpGs Differentially methylated positions (DMPs) and regions with multiple probes (DMRs) and the intersection analysis of DMPs and DMRs was conducted. Functional enrichment analysis highlights relevant biological processes. Furthermore, previously validated specific CpGs used as surrogate of brain tissue were explored.

Results: DNA methylation patterns included BTBD3, PGPEP1L, DUSP29, and MIB2 top genes ordered by statistical significance were found in the intersection of DMP and DMR. Differential methylation analyses revealed differentially methylated genes including HOXA-AS3, HOXA6, CACNA1A, KMT5A, MIDEAS, FAM234A, and KATNBL1P6. Gene enrichment analysis showed immune processes and intracellular signaling disruptions. Surrogate genes from brain found differentially methylated were PCDHGB1-3 and PCDHGA1-6.

Conclusions: This study identified DNA methylation patterns in peripheral blood leukocytes as potential biomarkers for AD. These findings offer insights into epigenetic mechanisms associated with systemic peripheral inflammation in AD.

Keywords: Alzheimer's disease; DNA methylation; biomarkers; dementia; epigenetics.

Figure 1.

The bar chart shows the proportion of intragenic (blue) and intergenic (red) CpGs among all tested probes (“Tested”) and those found to be differentially methylated in AD (“Found”). Among the CpGs analyzed, 24.68% were intragenic and in the differentially methylated subset were 34.91%.

Figure 2.

The bar chart shows the comparative distribution of CpG island-associated regions (CpGIsland, IslandShore, IslandShelf, OpenSea) in tested vs. differentially methylated CpG sites in AD.

Figure 3.

UCSC hg19 Genome Browser View for differentially methylated regions supported by multiple CpGs in the DMP, DMR, and sensitivity analyses. (a) shows the region near BTBD3 on chromosome 20. (b) shows the region near PGPEP1L on chromosome 15. Both panels illustrate hypermethylated loci identified in the present study. The chromosome charts indicate each region's position. Mapped Infinium probes are those present on the Illumina 450K microarray (not necessarily encompassing all CpGs covered by the EPIC array). Promoters from EPDnew human version 006 represent experimentally validated promoters in the Eukaryotic Promoter Database. SwitchGear transcription start sites track the TSSs identified by SwitchGear Genomics. CpG islands follow the Gardiner-Garden criteria. DNase I hypersensitivity clusters mark areas tested across diverse cell types by the ENCODE project. The H3K27Ac histone mark track indicates regions of active regulatory elements via ChIP-seq assays. Transcription ChIP-seq clusters show binding sites from a large collection of ENCODE ChIP-seq experiments. Finally, repeating elements by RepeatMasker identify interspersed repeats and low-complexity DNA sequences.