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<p>Extensive studies have shown that cerebrovascular dysfunction is a critical factor in the onset and progression of Alzheimer’s disease (AD). Neurovascular unit (NVU) is impaired in AD brains, including damage of tight junction between endothelial cells, degeneration of pericytes, activation of astrocytes and microglia, and apoptosis of neurons. As decreased cerebral blood flow is observed before amyloid-beta (Aβ) generation, it is supposed that NVU dysfunction may precede and exacerbate the pathological state of AD neural system, and that the events of NVU dysfunction and Aβ deposition synergistically promote AD progression. Technological breakthroughs of three-dimensional NVU organoids, spatial transcriptomics with single-cell resolution, and development of artificial intelligence technology, such as machine learning and deep learning, offer the possibility of constructing accurate functional structural models. Here we systematically review the NVU dysfunction during AD progression as well as the applications of spatial transcriptomics and organoid technology in NVU studies.</p>

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Dysfunction of the neurovascular unit as a temporal driver in Alzheimer’s pathogenesis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月22日

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  • Lifang Wang,
  • Lei Han,
  • Shiping Liu

摘要

Extensive studies have shown that cerebrovascular dysfunction is a critical factor in the onset and progression of Alzheimer’s disease (AD). Neurovascular unit (NVU) is impaired in AD brains, including damage of tight junction between endothelial cells, degeneration of pericytes, activation of astrocytes and microglia, and apoptosis of neurons. As decreased cerebral blood flow is observed before amyloid-beta (Aβ) generation, it is supposed that NVU dysfunction may precede and exacerbate the pathological state of AD neural system, and that the events of NVU dysfunction and Aβ deposition synergistically promote AD progression. Technological breakthroughs of three-dimensional NVU organoids, spatial transcriptomics with single-cell resolution, and development of artificial intelligence technology, such as machine learning and deep learning, offer the possibility of constructing accurate functional structural models. Here we systematically review the NVU dysfunction during AD progression as well as the applications of spatial transcriptomics and organoid technology in NVU studies.