Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics.
Nurun N FancyAmy M SmithAlessia CaramelloStergios TsartsalisKaren DaveyRobert C J MuirheadAisling McGarryMarion H JenkynsEleonore SchneegansVicky ChauMichael ThomasSam BoulgerTo Ka Dorcas CheungEmily AdairMarianna PapageorgopoulouNanet WillumsenCombiz KhozoieDiego Gomez-NicolaJohanna S JacksonPaul M MatthewsPublished in: Acta neuropathologica (2024)
Aging is associated with cell senescence and is the major risk factor for AD. We characterized premature cell senescence in postmortem brains from non-diseased controls (NDC) and donors with Alzheimer's disease (AD) using imaging mass cytometry (IMC) and single nuclear RNA (snRNA) sequencing (> 200,000 nuclei). We found increases in numbers of glia immunostaining for galactosidase beta (> fourfold) and p16 INK4A (up to twofold) with AD relative to NDC. Increased glial expression of genes related to senescence was associated with greater β-amyloid load. Prematurely senescent microglia downregulated phagocytic pathways suggesting reduced capacity for β-amyloid clearance. Gene set enrichment and pseudo-time trajectories described extensive DNA double-strand breaks (DSBs), mitochondrial dysfunction and ER stress associated with increased β-amyloid leading to premature senescence in microglia. We replicated these observations with independent AD snRNA-seq datasets. Our results describe a burden of senescent glia with AD that is sufficiently high to contribute to disease progression. These findings support the hypothesis that microglia are a primary target for senolytic treatments in AD.
Keyphrases
- single cell
- rna seq
- dna damage
- endothelial cells
- inflammatory response
- cell therapy
- stress induced
- genome wide
- neuropathic pain
- poor prognosis
- high resolution
- stem cells
- dna methylation
- cognitive decline
- spinal cord injury
- risk factors
- photodynamic therapy
- mass spectrometry
- copy number
- spinal cord
- mesenchymal stem cells
- oxidative stress
- genome wide identification
- bioinformatics analysis