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Single-cell transcriptomic analysis of Alzheimer’s disease

Author

Listed:
  • Hansruedi Mathys

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Jose Davila-Velderrain

    (MIT Computer Science and Artificial Intelligence Laboratory
    Broad Institute of MIT and Harvard)

  • Zhuyu Peng

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Fan Gao

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Shahin Mohammadi

    (MIT Computer Science and Artificial Intelligence Laboratory
    Broad Institute of MIT and Harvard)

  • Jennie Z. Young

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Madhvi Menon

    (Broad Institute of MIT and Harvard
    Harvard Medical School
    Harvard Medical School)

  • Liang He

    (MIT Computer Science and Artificial Intelligence Laboratory
    Broad Institute of MIT and Harvard)

  • Fatema Abdurrob

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Xueqiao Jiang

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Anthony J. Martorell

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Richard M. Ransohoff

    (Third Rock Ventures)

  • Brian P. Hafler

    (Broad Institute of MIT and Harvard
    Harvard Medical School
    Harvard Medical School
    Harvard Medical School)

  • David A. Bennett

    (Rush University Medical Center)

  • Manolis Kellis

    (MIT Computer Science and Artificial Intelligence Laboratory
    Broad Institute of MIT and Harvard)

  • Li-Huei Tsai

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Broad Institute of MIT and Harvard)

Abstract

Alzheimer’s disease is a pervasive neurodegenerative disorder, the molecular complexity of which remains poorly understood. Here, we analysed 80,660 single-nucleus transcriptomes from the prefrontal cortex of 48 individuals with varying degrees of Alzheimer’s disease pathology. Across six major brain cell types, we identified transcriptionally distinct subpopulations, including those associated with pathology and characterized by regulators of myelination, inflammation, and neuron survival. The strongest disease-associated changes appeared early in pathological progression and were highly cell-type specific, whereas genes upregulated at late stages were common across cell types and primarily involved in the global stress response. Notably, we found that female cells were overrepresented in disease-associated subpopulations, and that transcriptional responses were substantially different between sexes in several cell types, including oligodendrocytes. Overall, myelination-related processes were recurrently perturbed in multiple cell types, suggesting that myelination has a key role in Alzheimer’s disease pathophysiology. Our single-cell transcriptomic resource provides a blueprint for interrogating the molecular and cellular basis of Alzheimer’s disease.

Suggested Citation

  • Hansruedi Mathys & Jose Davila-Velderrain & Zhuyu Peng & Fan Gao & Shahin Mohammadi & Jennie Z. Young & Madhvi Menon & Liang He & Fatema Abdurrob & Xueqiao Jiang & Anthony J. Martorell & Richard M. Ra, 2019. "Single-cell transcriptomic analysis of Alzheimer’s disease," Nature, Nature, vol. 570(7761), pages 332-337, June.
  • Handle: RePEc:nat:nature:v:570:y:2019:i:7761:d:10.1038_s41586-019-1195-2
    DOI: 10.1038/s41586-019-1195-2
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