Single-cell Epigenetics of Tau Dementia | Part 1 - Understanding Cell-specific CREs, Chromatin Accessibility, and Differentially-Accessible Regions in Tauopathies

By Stuart P. Atkinson

Single-nucleus epigenomic landscape of AD, PiD and PSP across brain regions. (A) Schematic overview of the snATAC-seq workflow.

Understanding Tauopathies Through Single-cell Epigenetic and Transcriptomic Analyses

The abnormal aggregation of the tau (tubulin-associated unit) protein (encoded by the MAPT gene) and dementia-like symptoms characterize diseases known as neurodegenerative tauopathies. Tau represents the major pathological component in primary tauopathies such as Pick’s disease (PiD) and progressive supranuclear palsy (PSP), while the pathological protein amyloid beta drives/accelerates tau aggregation in the secondary tauopathy Alzheimer’s disease (AD). While these diseases share the aggregation of tau as a pathological feature, they possess relatively unexplored specific and Valentino et al., Wang et al., Li et al., and Zhao et al.) and neuropathological factors (Chung et al. and Moloney et al.). While neurons represent a major target for investigations, the glial cells that maintain and support neuronal function also undergo gradual dysregulation.

Recent research has begun to reveal some of these shared and distinct cellular responses to tau-associated disorders (Rexach et al. 2020 and Rexach et al. 2024). These studies highlighted an AD-enriched microglial state with the elevated expression of genes associated with AD polygenic risk and those known to protect against AD pathology; but do glial subpopulations play diverse roles across tau dementia disorders in disease pathogenesis through distinct mechanisms? A subsequent single-cell epigenetic and transcriptomic study from researchers led by Jessica E. Rexach (University of California, Los Angeles) sought to define cell-type-specific cis-regulatory elements (CREs) via chromatin accessibility (using snATAC-seq) and gene expression (using snRNA-seq) analysis in single nuclei across 6 cell types and 50 subclasses in samples from brain regions with distinct vulnerabilities in AD, PiD, and PSP patients to understand the regulatory circuitry of non-coding genetic variants underlying risk-associated cell states (Han et al.).

Epigenome Technologies Blog now brings you part one of a three-part summary of this exciting new single-cell epigenetics preprint article; overall, the authors provide a cross-disorder atlas linking gene regulation, chromatin dynamics, and cellular functions across three tau-related disorders PiD, PSP, and AD to highlight disorder-specific glial states with differential levels of resilience. In doing so, they further our understanding of disease regulatory circuits by uncovering epigenomic dynamics and mapping genetic variants to their target through CREs, prioritize genes for validation to inform causal mechanisms/therapeutic strategies by identifying molecular targets linked to polygenic disease risk, enhance our understanding of glial contributions to tauopathies, and underscore the importance of cross-disorder and cell-specific chromatin profiling in brain regions with moderate levels of pathology.

(B) Tracks of chromatin accessibility profiles generated using pseudo-bulk data for each cell type at canonical marker genes. Marker cis-regulatory elements (CREs) of 500 bp are labeled. Visualization and modifications were performed using the UCSC Genome Browser. Condition-dynamic and case-control differentially accessible CREs across human brain cell types. (C) Heatmaps displaying identified marker peaks (left), marker gene scores (right), and TFs enriched in marker peaks (middle) for each cell type.

Understanding Cell-specific CREs, Chromatin Accessibility, and Differentially-Accessible Regions in Tauopathies

(C) Pie chart illustrating the distribution of promoter peaks (left) and enhancer peaks (right) across cell types. (D) Enriched functional GO terms for genes linked to cell type-specific CRE, analyzed using enrichR. (E) Enrichment of TFs in the top 100 marker CREs uniquely identified in specific cell types, analyzed using MEME 37. FDRs were standardized within each cell type group. (F) Schematic diagram illustrating the identification of condition-dynamic peaks for each cell type. (G) Bar plot showing the number of dynamic and stable peaks across cell types. (H) Pie charts display the distribution of dynamic peaks across cell types (left) and across diseases (right). (I) Enriched functional GO terms and KEGG pathways of genes associated with the top 100 dynamic CREs, either unique or shared among the three diseases, in glia or neurons. Functional enrichment was performed using enrichR. (J) TF enrichment for dynamic CREs in the same groups as described in (I), analyzed using MEME.

Evaluating Single-cell Transcriptomic and Chromatin Accessibility Profiles in Disease-affected Brain Regions

The authors characterized disease progression-associated cellular heterogeneity and epigenomic differences across the calcarine of the visual cortex (calcarine), insular cortex (insula), and precentral gyrus of the frontal cortex (PreCG) via single-nucleus ATAC sequencing (snATAC-seq) on 41 individuals (10 controls, 10 AD, 10 PiD, and 11 PSP)

This data supported the construction of eight major clusters after removing two undefined groups
Initial annotation of six main cell types employed unambiguous canonical marker expression, with two excitatory and two inhibitory major groups
The calcarine samples suffered from variability, so the study focused on the insula and PreCG in downstream analyses

Accessible chromatin regions identified within each cell type displayed an enrichment for cell-type-specific transcription factors (TFs)

snATAC-derived cell-type clustering matched snRNA-derived cell types, with comparable cell distribution across brain regions

The study identified TFs that regulated gene expression and had links to motif variability in chromatin accessibility

Distinct cell-type-specific TFs exhibited consistent patterns of activity, expression, and motif variability
TF variability in PSP-affected glia deviated from that of the remaining diseases, with glial types clustering naturally within PSP rather than grouping by cell types across diseases

Can Cell Type-specific Cis-Regulatory Elements Define Cell Type Identity?

Genome-wide chromatin accessibility mapping identified a consensus peak set for all subclusters
Determining which peaks represent candidate cis-regulatory elements (CREs) for genes combined peak co-accessibility with gene-peak correlation from snRNA-seq data in cell subclusters split by disease

This detected 223,710 enhancers and 14,416 promoters, defining 25.8% (238,126) of peaks as CREs

The subsequent evaluation of chromatin accessibility regulation in CREs across cell types revealed that enhancers displayed more cell-type-specificity, while cell types shared promoters

6.5% of enhancers were unique to one cell type, and another 6.5% were specific to glia

Functional enrichment of cell-type-specific CRE-linked genes revealed functions associated with corresponding cell-type identities

Overall, specific TFs drove cell-type-specific CREs
The proportion of annotated enhancers did not differ when comparing dynamic to stable peaks

Dynamic accessible regions implicate disease heritability through GWAS, MPRA and sn-eQTL analysis. (A) Partition of disease heritability in dynamic and stable peaks across cell types for AD, PiD, and PSP GWAS, represented by LDSC standardized effect size. (B) Partition of disease heritability in dynamic peaks, stratified by up- and down-regulated peaks for each disease, within each cell type, measured specifically for the corresponding disease. For example, the PSP track depicts LDSC for PSP GWAS in PSP up- or down-regulated peaks. (C) Enrichment of sn-eQTLs in dynamic versus stable peaks, tested using Fisher's exact test. (D) Schematic of the MPRA experiment and integration with dynamic peaks. (E) Volcano plot of MPRA-tested variants, labeled by their overlapping genes' CREs. (F) Enrichment of MPRA-derived functional regulatory variants (frVars) in dynamic versus stable peaks, tested using Fisher's exact test. (G) Gene enrichment for dynamic enhancers containing MPRA frVars, analyzed using ShinyGO 0.80.

Do Dynamic Changes in Chromatin Accessibility Occur Across Conditions in Specific Cell Types?

Identifying cell-type-specific peaks in the consensus peak set revealed 48.7% unique peaks in five major cell types
Identifying dynamic and stable peaks for each subcluster based on whether a peak represented a marker for a specific condition revealed that an average of 16.1% of cell-type-specific peaks dynamically changed across conditions in different subclusters

Half of the total number of dynamic peaks (103,553) occurred in neurons and half in glia, with disease-specific dynamic peaks distributed evenly across all three disorders
Cell-type-level analysis revealed an increase in the average proportion of dynamic cell-type-specific peaks across conditions to 24%, with astrocytes exhibiting the highest percentage of dynamic peaks (33%)

Elucidating common and distinct biological pathways underlying epigenomic dynamics across disorders and cell types employed gene ontology analysis on genes linked to dynamic CREs in glia and neurons

Disease-shared dynamic CREs related to immune regulation in glia, which reflected immune activation in glial cells across conditions
Disease-shared dynamic CREs participated in apoptosis and neuronal differentiation in neurons, with additional disease-unique dynamic peaks regulating stress-related processes shared across disorders
Disease-shared and -distinct dynamic CREs and associated biological pathways displayed more prominence and diversity among glia
While disease-shared dynamic CREs in glia regulated inflammation, ER stress, and ferroptosis, differentially dynamic CREs in PiD and PSP glia regulated lipid metabolism compared to AD glia, which participated more robustly in the regulation of T cell activation-associated genes

Identifying upstream TF drivers of shared and distinct chromatin dynamics employed motif enrichment analysis

TF analysis of dynamic CREs in glia and neurons in each disease revealed the enrichment of SP and KLF family TFs in neurons shared across diseases, likely influencing neuronal differentiation/apoptosis
A TF uniquely enriched in glia (BHLHE40) drove disease-associated microglia responses in AD

Investigating TFs driving dynamic peaks in specific cell types across diseases focused on the top ten enriched motifs in each cell type and revealed how disease-associated TFs significantly regulated accessibility dynamics

These findings suggest that neurons engage in conserved stress responses across disorders, while glial cells display more dynamic gene regulation to govern their diverse and context-responsive biology

Diversity and heterogeneity of cellular subtypes in human brain of tauopathies. (A-C) UMAP embedding of subclusters of astrocytes (A), with a heatmap of gene score matrix labeled by log2fc > 1 for marker gene scores (B) and enriched functional terms associated with these marker genes (C). ASC, astrocytes. (D-F) Similar analyses for microglia subclusters. MG, microglia.

Do Differentially-Accessible Regions Transition Regarding Gene Activation from Middle- to High-Pathology Regions?

The authors next performed pairwise comparisons of disease and control samples to identify differentially accessible regions at the cell type level and determine which cell type exhibits significant disease-associated accessibility changes

A focus on differentially accessible CREs (DA-CREs) revealed a higher number in glia than neurons
Astrocytes contained the most significant number of DA-CREs, consistent with observations of dynamic CREs and highlighting the importance of disease-associated epigenomic dysregulation in astrocytes

The authors observed a trend towards gene deactivation with higher pathology when comparing the less affected brain region (PreCG) to the more affected brain region (insula)

PiD displayed a pattern of downregulated DARs that increased in astrocytes, inhibitory neurons, and oligodendrocytes

They examined the functional effects of genes linked to DA-CREs shared between two regions (upregulated in PreCG and downregulated in the insula)

In PiD, deactivated genes in astrocytes associated with cellular survival and inflammatory responses, while deactivated genes in oligodendrocytes associated with immune regulation, cell migration, and apoptosis
CRE deactivation in PiD-inhibitory neurons displayed the enrichment for genes regulating synaptic plasticity, suggesting a disruption in neuronal synapse response associated with disease progression

Progressive chromatin accessibility loss in advanced disease underlies the functional impairments in glia and neurons and contributes to neuroinflammatory responses and imbalances in excitatory/inhibitory signaling

Integrated analysis of accessibility changes, gene activity, GWAS heritability partition, epigenomic stability, and cell-cell interactions identifies disease-associated glia subtypes. (A) PSP-associated chromatin accessibility changes in astrocytes. Bar plots (left) show the number of differentially accessible CREs in PSP across astrocyte subclusters, categorized by up- and down-regulation. The right panel shows partitioned disease heritability of dynamic peaks in ast.C1 and ast.C10 (right), displaying LDSC standardized effect size ( ). FDR *< 0.05; ** <0.005; *** < 0.001. (B) Differentially activated TFs in astrocytes and ast.C1. (C) Schematic of molecular changes and dysregulated pathways driven by PSP GWAS risk variants in PSP ast.C1. Myelin-related astrocytes proliferate in tauopathy, activating SNARE mediated vesicle trafficking and lysosomal pathway to mitigate lipid stress induced by PSP risk variants. (D) Disease heritability partition in subcluster-specific peaks for FTD GWAS across microglia subtypes. FDR *< 0.05; ** <0.005; *** < 0.001. (E) Differentially activated genes in microglia and mg.C4. (F) Schematic of molecular changes and dysregulated pathways driven by FTD GWAS risk variants in PiD mg.C4. Myelin-related microglia proliferate in tauopathy, activating lysosome phagocytosis pathways to counteract ER and metabolic stress induced by FTD risk variants. Genes with upregulation are shown in red font, and those with downregulation in blue, based on differential gene scores or genes linked to differentially accessible CREs.

What Can Paired-Tag from Epigenome Technologies Do for Your Research?

Paired-Tag from Epigenome Technologies generates joint epigenetic and transcriptomic profiles at single-cell resolution and detects histone modifications and RNA transcripts in individual nuclei with comparable efficiency to single-nucleus RNA-seq/ChIP-seq assays while avoiding the need for cell sorting. The implementation of Paired-Tag technology may enable researchers to make significant strides in understanding gene regulation and improving the management of diseases, such as the neurodegenerative tauopathies explored in this exciting preprint.