DNA methylation signatures of Alzheimer’s disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types

Abstract

Alzheimer’s disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n = 2013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at loci not previously implicated in dementia. We subsequently profiled DNA methylation in NeuN+ (neuronal-enriched), SOX10+ (oligodendrocyte-enriched) and NeuN–/SOX10– (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in ‘bulk’ cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types.

Methylation differences in Alzheimer’s disease neuropathologic change in the aged human brain

“…To develop a more comprehensive understanding of the brain DNA methylome in older individuals, we analyzed bulk samples from eight different brain regions important in the progression of ADNC. Previous studies that analyzed sorted cells instead of bulk samples have shown that cell type proportions of tissue homogenates highly influence methylation changes [5,9]. Instead of cell sorting, we used cell type deconvolution methods that can extract cell-type-specific (CTS) signals from bulk data [10][11][12].…”

Brain DNA methylomic analysis of frontotemporal lobar degeneration revealsOTUD4in shared dysregulated signatures across pathological subtypes

“…As DNA methylation patterns are often cell-type specific, changes in different brain cell-type proportions constitute an important confounding factor for DNA methylation studies performed on ‘bulk’ brain tissue. We have used a novel cell-type deconvolution algorithm described by Shireby et al 21 which brings more granularity and expands previous methods that would account only for neuronal (NeuN+) versus all other cell types (NeuN-). This new method uses novel DNA methylation reference panels data obtained from fluorescence activated sorted nuclei from cortical brain tissue to estimate the relative proportions of neurons (NeuN+), oligodendrocytes (SOX10+) and other brain cell types (Double- [NeuN- /SOX10-]).…”

“…This new method uses novel DNA methylation reference panels data obtained from fluorescence activated sorted nuclei from cortical brain tissue to estimate the relative proportions of neurons (NeuN+), oligodendrocytes (SOX10+) and other brain cell types (Double- [NeuN- /SOX10-]). Cell-type proportions in bulk brain tissue were thus estimated using the CETYGO (CEll TYpe deconvolution GOodness) package (https://github.com/ds420/CETYGO), and the sorted cell-type reference datasets as described by Shireby et al 21 . Pairwise comparisons between FTLD cases and controls were conducted using Wilcoxon rank sum test with Benjamini-Hochberg correction for multiple testing, and adjusted p<0.05 was considered significant.…”

“…However, studies investigating non-sequence-based regulatory mechanisms such as epigenetic modifications in FTLD brain tissue are limited [15][16][17][18] . DNA methylation variation, the most well studied epigenetic modification, have consistently been associated with Alzheimer's disease pathology in epigenome-wide studies (EWAS) and subsequent meta-analysis [19][20][21] . In FTLD, brain tissue EWAS are scarce and limited to a single PSP study 15 .…”

Single-Cell DNA Methylation Analysis in Cancer

“…These regulatory properties of DNAme are crucial in numerous fundamental biological processes throughout the lifespan, including cell-cycle control, cell fate decisions, X-chromosome inactivation, genomic imprinting, embryonic development, chromosomal stability, and transposable element silencing [ 11 , 12 , 13 , 14 ]. Considering the above, it is not surprising that aberrant DNAme patterns are implicated in many diseases, including Alzheimer’s [ 15 ], cardiovascular diseases [ 16 ], and, of interest to this review, all types of cancer [ 17 ]. Furthermore, aberrations in enzymes associated with DNAme, such as ten-eleven translocation proteins, have been identified as cancer hallmarks [ 18 ], as well as intermediate states of 5mC, such as 5-hydroxymethylcytosine (5hmC) [ 19 , 20 ].…”