Parallel single-nucleus chromatin accessibility and transcriptomic profiling of human late-onset Alzheimer's disease brains

Journal Article (Journal Article)

BACKGROUND: In the post-GWAS era for late-onset Alzheimer's disease (LOAD), the precise disease-causing genes, the specific causal variants, and molecular mechanisms mediating their pathogenic effects remain unknown. Recent studies using single-nucleus (sn)RNA-seq on human LOAD tissue have achieved unprecedented resolution in identifying cell type-specific gene dysregulation, however the regulatory mechanisms and genetic variability underlying these LOAD-specific transcriptomic signatures remain to be identified. METHOD: Nuclei were isolated from frozen post-mortem human temporal cortex tissue from LOAD patients and cognitively healthy controls (n = 24, all Caucasian and APOE 3/3). 10X Genomics technology was used to generate single-nucleus (sn)RNA-seq and snATAC-seq libraries in parallel from the same pool of nuclei isolated from each brain sample. RESULT: Uniform manifold approximation and projection (UMAP) analysis showed a total of 29 clusters assigned to 8 cell types including astrocytes, excitatory neurons, inhibitory neurons, microglia, oligodendrocytes, and oligodendrocyte precursor cells (OPCs) in both snRNA-seq and snATAC-seq datasets. We identified differentially expressed genes (DEGs) and differentially accessible peaks (DAPs) for each cluster and found overlaps with known LOAD GWAS regions (SNP+/- 1Mb) as well as new LOAD loci that were not discovered previously. We next performed co-accessibility analysis and identified co-accessible peaks that were more open in LOAD and corresponded to dysregulation of nearby target genes. This analysis also produced networks of co-accessible LOAD peaks that were enriched in transcription factor (TF) motifs of TFs that are specifically overexpressed in LOAD samples. CONCLUSION: Integrative multi-omics is a powerful strategy to identify regulatory elements underlying gene dysregulation in LOAD. By integrating single-nucleus transcriptomic and open chromatin profiles from the same pool of nuclei, we are able to identify cell subtype-specific molecular mechanisms contributing to LOAD pathogenesis. This new genetic knowledge will progress the identification of new therapeutic targets.

Full Text

Duke Authors

Cited Authors

  • Gamache, J; Barrera, J; Gingerich, D; Garrett, M; Chipman, D; Fradin, H; Ashley-Koch, A; Crawford, G; Chiba-Falek, O

Published Date

  • December 1, 2021

Published In

Volume / Issue

  • 17 /

Start / End Page

  • e057261 -

Electronic International Standard Serial Number (EISSN)

  • 1552-5279

Digital Object Identifier (DOI)

  • 10.1002/alz.057261

Citation Source

  • Scopus