Mathys H, Davila-Velderrain J, Peng Z, Gao F, Mohammadi S, Young JZ, Menon M, He L, Abdurrob F, Jiang X, Martorell AJ, Ransohoff RM, Hafler BP, Bennett DA, Kellis M, Tsai LH. Single-cell transcriptomic analysis of Alzheimer's disease. Nature. 2019 Jun;570(7761):332-337. Epub 2019 May 1 PubMed.

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Comments

  1. This is a tour de force by the teams of Li-Huei Tsai and Manolis Kellis. A particular strength is the separate treatment of early and advanced pathology, with analyses of early versus control, and late versus early. This helps distinguish changes in an end-stage brain, which may simply be secondary and non-specific.

    Comparison of these groups indeed shows very interesting results. Late changes are different, with upregulated genes often shared by most cell types, and consistent with a general response to stress. It would be interesting to determine if similar changes are seen at advanced stages of other neurodegenerative disorders, or other brain regions. Early changes are almost always specific to neurons, or one glial type. These changes were additionally shown to be distinct from profiles related to postmortem interval, or age at death.

    Another important message is that bulk RNA signal, when compared to single-cell data, was dominated by changes in excitatory neurons and oligodendrocytes. Microglia, emerging as key players in Alzheimer's, were very poorly represented in bulk RNA, highlighting the need for cell-type specific analysis. The importance of microglia is supported by the detection of a specific disease-associated microglial sub-population, although disease-related sub-populations of astrocytes and oligodendrocytes are now also reported.

    Interestingly, although there was clear overlap of disease-related microglia expression patterns with those reported in aged microglia, there were important differences, with the key risk factor APOE only found in the disease-related population. In another new study which analysed the microglial response in an App knock-in mouse model, which included prominent ApoE upregulation, this response was severely impaired in the absence of ApoE (Sala Frigerio et al., 2019). These studies suggest a role of APOE in the microglial response in Alzheimer’s.

    Tsai and Kellis correctly conclude that they cannot differentiate cause and effect in their findings, or beneficial from harmful changes, but they have clearly advanced our understanding of how pathology develops.

    References:

    Sala Frigerio C, Wolfs L, Fattorelli N, Thrupp N, Voytyuk I, Schmidt I, Mancuso R, Chen WT, Woodbury ME, Srivastava G, Möller T, Hudry E, Das S, Saido T, Karran E, Hyman B, Perry VH, Fiers M, De Strooper B. The Major Risk Factors for Alzheimer's Disease: Age, Sex, and Genes Modulate the Microglia Response to Aβ Plaques. Cell Rep. 2019 Apr 23;27(4):1293-1306.e6. PubMed.

    View all comments by Christos Proukakis

  2. It is exciting to see all these studies examining cell-type-specific responses to Alzheimer’s disease pathology at the transcriptomic levels. The isolated cell-type approach from Srinivasan, Friedman et al. and the single-nucleus approach from Mathys, Davila-Velderrain et al. shared some common findings that challenge whether microglial phenotypes described in mouse models of neurodegeneration exist in human disease. Although both studies identified upregulation of APOE in microglia from AD brain, other “disease-associated microglia” (DAM) markers were not as readily detectable.

    It is worth noting that DAM cells as described by Keren-Shaul et al. comprised a relatively small proportion of microglia in the 5xFAD amyloid model, which may make it difficult to capture with single-cell/nucleus analysis (Keren-Shaul et al., 2017). In this regard, it would be interesting to use the cell-extraction approach described by Srinivasan et al; using putative DAM markers such as CD11c would enrich for microglia in DAM-like transcriptomic states.

    Additionally, the SlideSeq approach recently described by Rodriques, Stickels et al. would be a powerful way to get around the difficulty in enriching for particular cell types such as microglia or astrocytes and assess the transcriptomic state of cells in regards to their spatial proximity to pathology (Rodriques et al., 2019). 

    References:

    Keren-Shaul H, Spinrad A, Weiner A, Matcovitch-Natan O, Dvir-Szternfeld R, Ulland TK, David E, Baruch K, Lara-Astaiso D, Toth B, Itzkovitz S, Colonna M, Schwartz M, Amit I. A Unique Microglia Type Associated with Restricting Development of Alzheimer's Disease. Cell. 2017 Jun 15;169(7):1276-1290.e17. Epub 2017 Jun 8 PubMed.

    Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, Welch J, Chen LM, Chen F, Macosko EZ. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019 Mar 29;363(6434):1463-1467. Epub 2019 Mar 28 PubMed.

    View all comments by Jason Ulrich

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