Journal of NeuroscienceNeurosciencePeer-reviewed journal article
Endothelial Cells are Heterogeneous in Different Brain Regions and are Dramatically Altered in Alzheimer's Disease
Annie G. BryantiD, Zhaozhi LiiD, Rojashree JayakumariD, Alberto Serrano‐PozoiD, Benjamin Woost, Miwei HuiD, Maya E. WoodburyiD, Astrid WachteriD, Gen LiniD, Taekyung Kwon, Robert V. TalanianiD, Knut P. H. BiberiD, Eric H. KarraniD, Bradley T. HymaniD, Sudeshna DasiD, Rachel E. BennettiD
Abstract
Vascular endothelial cells play an important role in maintaining brain health, but their contribution to Alzheimers disease (AD) is obscured by limited understanding of the cellular heterogeneity in normal aged brain and in disease. To address this, we performed single nucleus RNAseq on tissue from 32 AD and non-AD donors each with five cortical regions: entorhinal cortex, inferior temporal gyrus, prefrontal cortex, visual association cortex and primary visual cortex. Analysis of 51,586 endothelial cells revealed unique gene expression patterns across the five regions in non-AD donors. Alzheimers brain endothelial cells were characterized by upregulated protein folding genes and distinct transcriptomic differences in response to amyloid beta plaques and cerebral amyloid angiopathy (CAA). This dataset demonstrates previously unrecognized regional heterogeneity in the endothelial cell transcriptome in both aged non-AD and AD brain. Significance StatementIn this work, we show that vascular endothelial cells collected from five different brain regions display surprising variability in gene expression. In the presence of Alzheimers disease pathology, endothelial cell gene expression is dramatically altered with clear differences in regional and temporal changes. These findings help explain why certain brain regions appear to differ in susceptibility to disease-related vascular remodeling events that may impact blood flow.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: database / resource
- approach: statistical model
- approach: experimental assay
- Citations
- 77
- FWCI
- 7.92
- Field percentile
- top 2%
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