High-Dimensional Single-Cell Mapping of Central Nervous System Immune Cells Reveals Distinct Myeloid Subsets in Health, Aging, and Disease

Mrdjen, Dunja; Pavlovic, Anto; Hartmann, Felix J.; Schreiner, Bettina; Utz, Sebastian G.; Leung, Brian P.; Lelios, Iva; Heppner, Frank L.; Kipnis, Jonathan; Merkler, Doron; Greter, Melanie; Becher, Burkhard

doi:10.1016/j.immuni.2018.02.014

Cited by 277 publications

(413 citation statements)

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“…Thus, the results cannot be directly compared. Taken together, our results and the intriguing recently reported results in experimental autoimmune encephalomyelitis, 14,15 Huntingtin transgenic mice, 14 the mutant superoxide dismutase-1 transgenic mouse model of Amyotrophic Lateral Sclerosis, 14 aged C57Bl6 mice, 15 and the APP-PS1 mouse model of Alzheimer's disease, 15 indicate the substantial value of the mass cytometry approach to analysis of microglia.…”

Section: Discussionsupporting

confidence: 75%

“…These results should be interpreted as a complement to gene expression studies [20][21][22][23] , which while more unbiased and able to assess a broader range of genes, do not offer the opportunity to directly assess protein expression at a single cell level. Our study used a substantially different set of mass cytometry markers than the recently published, elegant studies in other mouse models of neurological disorders 14,15 . Thus, the results cannot be directly compared.…”

Section: Discussionmentioning

confidence: 99%

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Microglial Heterogeneity in a Mouse Model of Alzheimer’s Disease: A Mass Cytometry Analysis

Esparza

Malkova³

et al. 2018

Preprint

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Microglia, the resident immune cells of the central nervous system, have been subject to intense scrutiny recently because of their implicated role in the pathogenesis of Alzheimer's disease, as well as many other neurological conditions. However, little is known about the diversity of microglial phenotypes, apart from the clear recognition that the M1-M2 distinction is an oversimplification. We used mass cytometry, a high dimensional analog of flow cytometry involving mass spectrometry-based analyses of single cells bound with metal-tagged antibodies, to characterize the diversity of microglia isolated from the brains of 3xTg-AD mice at 12, 18, and 24 months of age. Antibodies to microglial surface antigens CD11b, MHC class II, Siglec F, and TLR4 as well as intracellular antigens Arginase-1, IL10, IL12p40, iNOS, NADPH Oxidase, TGF-beta, and TNF-alpha were conjugated to unique metal isotopes, and used for mass cytometry. Phenograph-based clustering of the resulting high dimensional datasets identified 28 cell clusters of widely varying sizes, including clearly discrete phenotypes as well as pseudo-continuous/fractal phenotypic diversity. Monte Carlo simulations involving random reshuffling of the datasets revealed very different and much more uniform clustering patterns. Furthermore, control analyses of mouse peripheral blood mononuclear cells and brain microglia using the same markers revealed largely disjoint clusterings, indicating that these microglial clusters were not the result of peripheral blood contamination. Most of the microglial clusters were similar in samples from 3xTg-AD mice at all 3 ages, as well as from 12-month-old wild-type mice. The largest cluster expressed high levels of canonical microglial markers CD11b, CD11c, CD18, CD64, CD68, CD200R, CX3CR1, F4-80, NADPH oxidase, and TGF-beta but did not vary between experimental groups. However, 3 clusters did differ across experimental groups, one of which increased significantly with age in the 3xTg-AD mice as a fraction of the total microglial population. This cluster expressed high levels of CD18, CD38, CD45, CD86, and CD200R, but not other canonical markers. In summary, these mass cytometry-based analyses revealed previously uncharacterized microglial phenotypic heterogeneity in a mouse model of Alzheimer's disease. The specific roles of the putative subclasses of microglia, their relevance to human disease, and many other questions remain to be addressed.

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Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 99%

Microglial Heterogeneity in a Mouse Model of Alzheimer’s Disease: A Mass Cytometry Analysis

Esparza

Malkova³

et al. 2018

Preprint

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“…The identification of the infiltrates as peripherally derived hinged largely on their expression of CD11b and CD45 (Korin et al, 2017; Mildner et al, 2011). However, recent work has refuted this assertion (Mrdjen et al, 2018). Transcriptomic studies (Keren-Shaul et al, 2017; Krasemann et al, 2017) have allowed delineation of microglia from macrophages and other immune cells, but have not been able to resolve the issue of ontogenic origin of the plaque-associated cells, owing to the rapid and diverse changes in myeloid cell gene expression in the brain microenvironment (Lund et al, 2018).…”

Section: Resultsmentioning

confidence: 99%

Plaque-associated myeloid cells derive from resident microglia in an Alzheimer’s disease model

Reed-Geaghan

Croxford

Becher

et al. 2020

Journal of Experimental Medicine

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Alzheimer’s disease (AD) is accompanied by a robust inflammatory response mediated by plaque-associated myeloid cells of the brain. These cells exhibit altered gene expression profiles and serve as a barrier, preventing neuritic dystrophy. The origin of these cells has been controversial and is of therapeutic importance. Here, we genetically labeled different myeloid populations and unequivocally demonstrated that plaque-associated myeloid cells in the AD brain are derived exclusively from resident microglia, with no contribution from circulating peripheral monocytes.

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“…Importantly, leakage of nonspecific molecules is distinct from leukocyte extravasation, which occurs via an active trafficking process. Single-cell sequencing has identified many subsets of immune cells with distinct roles in neuroinflammation that likely interact with the BBB in disease (Mrdjen et al, 2018; Jordão et al, 2019; Kierdorf et al, 2019; Masuda et al, 2019; Mundt et al, 2019). Parenchymal ECs up-regulate leukocyte adhesion molecules, thus increasing leukocyte trafficking.…”

Section: Bbb Dysfunctionmentioning

confidence: 99%

The blood–brain barrier in health and disease: Important unanswered questions

Profaci

Munji

Pulido

et al. 2020

Journal of Experimental Medicine

442

358

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The blood vessels vascularizing the central nervous system exhibit a series of distinct properties that tightly control the movement of ions, molecules, and cells between the blood and the parenchyma. This “blood–brain barrier” is initiated during angiogenesis via signals from the surrounding neural environment, and its integrity remains vital for homeostasis and neural protection throughout life. Blood–brain barrier dysfunction contributes to pathology in a range of neurological conditions including multiple sclerosis, stroke, and epilepsy, and has also been implicated in neurodegenerative diseases such as Alzheimer’s disease. This review will discuss current knowledge and key unanswered questions regarding the blood–brain barrier in health and disease.

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High-Dimensional Single-Cell Mapping of Central Nervous System Immune Cells Reveals Distinct Myeloid Subsets in Health, Aging, and Disease

Cited by 277 publications

References 0 publications

Microglial Heterogeneity in a Mouse Model of Alzheimer’s Disease: A Mass Cytometry Analysis

Microglial Heterogeneity in a Mouse Model of Alzheimer’s Disease: A Mass Cytometry Analysis

Plaque-associated myeloid cells derive from resident microglia in an Alzheimer’s disease model

The blood–brain barrier in health and disease: Important unanswered questions

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