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Review
. 2024 Feb;47(2):100031.
doi: 10.1016/j.mocell.2024.100031. Epub 2024 Feb 13.

Adipose tissue macrophage heterogeneity in the single-cell genomics era

Haneul Kang  1 , Jongsoon Lee  2
Affiliations
Review

Adipose tissue macrophage heterogeneity in the single-cell genomics era

Haneul Kang et al. Mol Cells. 2024 Feb.

Abstract

It is now well-accepted that obesity-induced inflammation plays an important role in the development of insulin resistance and type 2 diabetes. A key source of the inflammation is the murine epididymal and human visceral adipose tissue. The current paradigm is that obesity activates multiple proinflammatory immune cell types in adipose tissue, including adipose-tissue macrophages (ATMs), T Helper 1 (Th1) T cells, and natural killer (NK) cells, while concomitantly suppressing anti-inflammatory immune cells such as T Helper 2 (Th2) T cells and regulatory T cells (Tregs). A key feature of the current paradigm is that obesity induces the anti-inflammatory M2 ATMs in lean adipose tissue to polarize into proinflammatory M1 ATMs. However, recent single-cell transcriptomics studies suggest that the story is much more complex. Here we describe the single-cell genomics technologies that have been developed recently and the emerging results from studies using these technologies. While further studies are needed, it is clear that ATMs are highly heterogeneous. Moreover, while a variety of ATM clusters with quite distinct features have been found to be expanded by obesity, none truly resemble classical M1 ATMs. It is likely that single-cell transcriptomics technology will further revolutionize the field, thereby promoting our understanding of ATMs, adipose-tissue inflammation, and insulin resistance and accelerating the development of therapies for type 2 diabetes.

Keywords: ATM heterogeneity; Adipose tissue macrophages (ATMs); Inflammation; Insulin resistance; Obesity.

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Conflict of interest statement

Declaration of Competing Interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
The basic workflow of the 4 RNA-seq technologies. While scRNA-seq can only be used with fresh samples, snRNA-seq, scATAC-seq, and spatial RNA-seq can be used with both fresh and frozen samples.
Fig. 2
Fig. 2
The subpopulations and markers of ATMs that have been discovered in adipose tissues from humans and mice by single-cell genomics technologies to date. PVMs and NPVMs are abundant in lean adipose tissue and are significantly reduced by obesity. IMs are highly expanded by obesity, as are LAMs and P-LAMs. Although it is a very small population, RMs also appear to be increased by obesity. PVMs appear to be significantly decreased by obesity. CMs tend to be elevated by obesity, although this does not achieve statistical significance. Efferocytes were present at very similar frequencies in lean and obese adipose tissue. PVM, perivascular macrophage; NPVM, nonperivascular macrophage; IM, inflammatory macrophage; LAM, lipid-associated macrophage; P-LAM, proliferative-LAM; RM, regulatory macrophage; CEM, collagen-expressing macrophage; CM, Cycling macrophage.
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