. Transcriptomic analysis of purified human cortical microglia reveals age-associated changes. Nat Neurosci. 2017 Aug;20(8):1162-1171. Epub 2017 Jul 3 PubMed.


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  1. Overall the paper is a great resource—there really is nothing out there at the moment for microglia researchers to use as a gold standard for what the transcriptome of human microglia should be.

    The validation of selected human microglial transcriptome targets with immunostaining of human postmortem tissue is a great addition. Of course this tissue is from similar postmortem delay, and so does not remove the concern that these genes may only be expressed due to activation in a dead brain. But it does wonderfully show their localization in microglia and not other cells.

    The differences with aging are interesting. In figure 5, the heatmap shows numbers of genes upregulated in senescence and others downregulated over the same aging timeframe. These could become key targets for further investigation of neurodegenerative disease.

    This new human microglial transcriptome database was produced from microglia isolated from the right parietal cortex. Considering there is now considerable information about the heterogeneity of microglia, are the differences seen between the human and rodent cells due to species differences or regional heterogeneity differences? I.e., were the compared mouse samples prepared from the same brain region?

    The postmortem delay, which is always the problem when dealing with microglia, is reasonable and likely renders moot most arguments about cells randomly becoming activated due to slow cell preparations.

    This resource is going to be heavily used by a lot of researchers—not only to determine the baseline expression of genes that should be looked for in any human microglia cell culture experiments, but also as a great comparative resource for people to purify microglia from patient postmortem brain with neurodegenerative disease, infection, or trauma.

    View all comments by Shane Liddelow
  2. It is reassuring that these data show good concordance with the data set from the Barres Lab in 2016. We now have an additional treasure trove for investigators interested in mechanistic learnings from neuro-glia (microglia and astrocyte) interactions and interactors in rodents, with potential to inform on human studies.

    View all comments by Ayodeji Asuni

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