Accelerated aging-related transcriptome alterations in neurovascular unit cells in the brain of Alzheimer’s disease

• Published in: Frontiers in aging neuroscience Vol. 14; p. 949074
• Main Authors: Zhao, Yan, Xie, Yong-Zhi, Liu, You-Shuo
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 18.08.2022; Frontiers Media S.A
• Subjects: Aging; Alzheimer's disease; Astrocytes; Datasets; Dementia; Dementia disorders; Endothelial cells; Gene expression; Gene set enrichment analysis; Genomics; Genotype & phenotype; Glial stem cells; Homeostasis; Microenvironments; Microglia; neurodegenerative disease; Neurodegenerative diseases; Neuroscience; neurovascular unit; Older people; Oligodendrocytes; Pathogenesis; Pericytes; Risk factors; Signal transduction; single-nucleus RNA sequencing; Therapeutic targets; Transcriptomes; Transcriptomics
• ISSN: 1663-4365; 1663-4365
• DOI: 10.3389/fnagi.2022.949074

Alzheimer’s disease (AD) is the most common cause of dementia with no effective therapies. Aging is a dominant risk factor for AD. The neurovascular unit (NVU) plays an important role in maintaining homeostasis of the brain microenvironment. The accelerated aging of NVU cells may directly impair NVU function and contribute to AD pathogenesis. However, the expression patterns of aging-related genes (AGs) in NVU cells of AD remain unclear. In this study, we performed single-nucleus transcriptome analysis of 61,768 nuclei from prefrontal cortical samples of patients with AD and normal control (NC) subjects. Eight main cell types were identified, including astrocytes, microglia, excitatory neurons, inhibitory neurons, oligodendrocytes, oligodendrocyte precursor cells, pericytes, and endothelial cells. Transcriptomic analysis identified the expression patterns of AGs in NVU cells of AD. Gene set enrichment analysis confirmed the key aging-associated cellular pathways enriched in microglia and oligodendrocytes. These aging-related transcriptomic changes in NVU were cross-validated using bulk transcriptome data. The least absolute shrinkage and selection operator regression method was used to select the crucial AGs most associated with AD: IGF1R, MXI1, RB1, PPARA, NFE2L2, STAT5B, FOS, PRKCD, YWHAZ, HTT, MAPK9, HSPA9, SDHC, PRKDC, and PDPK1. This 15-gene model performed well in discriminating AD from NC samples. Among them, IGF1R, MXI1, PPARA, YWHAZ, and MAPK9 strongly correlated with pathologic progression in AD, were identified as critical regulators of AD. Although most AGs showed similar trends of expression changes in different types of NVU cells in AD, certain AGs were expressed in a cell-specific manner. Our comprehensive analysis of brain NVU from patients with AD reveals previously unknown molecular changes associated with aging that may underlie the functional dysregulation of NVU, providing important insights for exploring potential cell-specific therapeutic targets to restore brain homeostasis in AD.