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Del-Aguila JL, Li Z, Dube U, Mihindukulasuriya KA, Budde JP, Fernandez MV, Ibanez L, Bradley J, Wang F, Bergmann K, Davenport R, Morris JC, Holtzman DM, Perrin RJ, Benitez BA, Dougherty J, Cruchaga C, Harari O. A single-nuclei RNA sequencing study of Mendelian and sporadic AD in the human brain. Alzheimers Res Ther. 2019 Aug 9;11(1):71. PubMed.
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Washington University
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.
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