. 2022 Mar;603(7903):926-933.

doi: 10.1038/s41586-022-04518-2. Epub 2022 Mar 16.

A single-cell atlas of human and mouse white adipose tissue

Margo P Emont^{1

2}, Christopher Jacobs^{1

2}, Adam L Essene¹, Deepti Pant¹, Danielle Tenen^{1

2}, Georgia Colleluori³, Angelica Di Vincenzo³, Anja M Jørgensen⁴, Hesam Dashti², Adam Stefek², Elizabeth McGonagle², Sophie Strobel², Samantha Laber², Saaket Agrawal^{2

5}, Gregory P Westcott¹, Amrita Kar^{1

2}, Molly L Veregge¹, Anton Gulko¹, Harini Srinivasan^{1

2}, Zachary Kramer¹, Eleanna De Filippis⁶, Erin Merkel¹, Jennifer Ducie⁷, Christopher G Boyd⁸, William Gourash⁹, Anita Courcoulas⁹, Samuel J Lin¹⁰, Bernard T Lee¹⁰, Donald Morris¹⁰, Adam Tobias¹⁰, Amit V Khera^{2

5

10}, Melina Claussnitzer^{2

11}, Tune H Pers⁴, Antonio Giordano³, Orr Ashenberg¹², Aviv Regev^{12

13

14}, Linus T Tsai^{1

2

15}, Evan D Rosen^{16

17

18}

Affiliations

¹ Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA.
² Broad Institute of MIT and Harvard, Cambridge, MA, USA.
³ Department of Experimental and Clinical Medicine, Center of Obesity, Marche Polytechnic University, Ancona, Italy.
⁴ Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
⁵ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
⁶ Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic Scottsdale, AZ, USA.
⁷ Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
⁸ Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA.
⁹ Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
¹⁰ Division of Plastic Surgery, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹¹ Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
¹² Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹³ Howard Hughes Medical Institute, Koch Institute of Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
¹⁴ Genentech, South San Francisco, CA, USA.
¹⁵ Harvard Medical School, Boston, MA, USA.
¹⁶ Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA. erosen@bidmc.harvard.edu.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA. erosen@bidmc.harvard.edu.
¹⁸ Harvard Medical School, Boston, MA, USA. erosen@bidmc.harvard.edu.

PMID: 35296864
PMCID: PMC9504827
DOI: 10.1038/s41586-022-04518-2

A single-cell atlas of human and mouse white adipose tissue

Margo P Emont et al. Nature. 2022 Mar.

. 2022 Mar;603(7903):926-933.

doi: 10.1038/s41586-022-04518-2. Epub 2022 Mar 16.

Authors

Affiliations

¹ Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA.
² Broad Institute of MIT and Harvard, Cambridge, MA, USA.
³ Department of Experimental and Clinical Medicine, Center of Obesity, Marche Polytechnic University, Ancona, Italy.
⁴ Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
⁵ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
⁶ Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic Scottsdale, AZ, USA.
⁷ Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
⁸ Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA.
⁹ Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
¹⁰ Division of Plastic Surgery, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹¹ Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
¹² Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹³ Howard Hughes Medical Institute, Koch Institute of Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
¹⁴ Genentech, South San Francisco, CA, USA.
¹⁵ Harvard Medical School, Boston, MA, USA.
¹⁶ Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA. erosen@bidmc.harvard.edu.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA. erosen@bidmc.harvard.edu.
¹⁸ Harvard Medical School, Boston, MA, USA. erosen@bidmc.harvard.edu.

PMID: 35296864
PMCID: PMC9504827
DOI: 10.1038/s41586-022-04518-2

Erratum in

Author Correction: A single-cell atlas of human and mouse white adipose tissue.
Emont MP, Jacobs C, Essene AL, Pant D, Tenen D, Colleluori G, Di Vincenzo A, Jørgensen AM, Dashti H, Stefek A, McGonagle E, Strobel S, Laber S, Agrawal S, Westcott GP, Kar A, Veregge ML, Gulko A, Srinivasan H, Kramer Z, De Filippis E, Merkel E, Ducie J, Boyd CG, Gourash W, Courcoulas A, Lin SJ, Lee BT, Morris D, Tobias A, Khera AV, Claussnitzer M, Pers TH, Giordano A, Ashenberg O, Regev A, Tsai LT, Rosen ED. Emont MP, et al. Nature. 2023 Aug;620(7973):E14. doi: 10.1038/s41586-023-06445-2. Nature. 2023. PMID: 37495702 No abstract available.

Abstract

White adipose tissue, once regarded as morphologically and functionally bland, is now recognized to be dynamic, plastic and heterogenous, and is involved in a wide array of biological processes including energy homeostasis, glucose and lipid handling, blood pressure control and host defence¹. High-fat feeding and other metabolic stressors cause marked changes in adipose morphology, physiology and cellular composition¹, and alterations in adiposity are associated with insulin resistance, dyslipidemia and type 2 diabetes². Here we provide detailed cellular atlases of human and mouse subcutaneous and visceral white fat at single-cell resolution across a range of body weight. We identify subpopulations of adipocytes, adipose stem and progenitor cells, vascular and immune cells and demonstrate commonalities and differences across species and dietary conditions. We link specific cell types to increased risk of metabolic disease and provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity. These data comprise an extensive resource for the exploration of genes, traits and cell types in the function of white adipose tissue across species, depots and nutritional conditions.

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Figures

**Extended Data Fig. 1.. Additional analysis of the effects of depot and BMI on human WAT populations.**
a, UMAP projections of cells from the lowest and highest BMI ranges in the dataset, split by depot. To facilitate comparison, samples were randomly subset to contain the same number of cells in each plot (n = 20,339). b, Graph showing the proportion of sNuc-seq cells in each cluster per sample, split by depot and BMI, n = 4 SAT < 30, 6 SAT > 40, 3 VAT < 30, 5 VAT > 40. C, Estimated cell type proportions in bulk RNA sequencing data of subcutaneous adipose tissue from 331 individuals from the METSIM cohort calculated using sNuc-seq data as reference. Vascular cells include endothelial, lymphatic endothelial, pericytes, and smooth muscle cells. Myeloid immune includes macrophages, monocytes, dendritic cells, mast cells and neutrophils, and lymphoid immune includes B cells, NK cells, and T cells. For lines of best fit: Adipocytes R² = 0.031, ASPCs R² = 0.034, Vascular R² = 0.076, Myeloid Immune R² = 0.13, Lymphoid Immune R² = 0.0049. For scatterplots, error bands represent a confidence level of 0.95 and p values were calculated using an F-test with the null hypothesis that the slope = 0. For bar graphs, error bars represent SEM, * indicates credible depot effect and # indicates credible BMI effect, calculated using dendritic cells as reference.

**Extended Data Fig. 2.. Additional analysis of the effects of depot and diet on mouse WAT populations and association with human WAT populations.**
a, UMAP projection of all mouse WAT cells split by depot. b, Proportion of cells in each cluster per sample, split by sex as well as by depot and diet, for male mice n = 4 ING Chow, 4 ING HFD, 3 EPI Chow, and 5 EPI HFD. For female mice, n = 2 per condition. c, Riverplot showing the relationship between mouse and human clusters. Mouse cells were mapped onto human sNuc-seq cells using multimodal reference mapping. The riverplot represents the relationship between manually assigned mouse cluster and mapped human cluster for every mouse cell. For bar graphs, error bars represent SEM, * indicates credible depot effect and # indicates credible diet effect, calculated using dendritic cells as reference.

**Extended Data Fig. 3.. Highly similar vascular cells in human and mouse WAT.**
a, UMAP projection of 22,734 human vascular cells. b, Marker genes for 11 distinct clusters of human WAT vascular cells. c, UMAP projection of 7,632 mouse vascular cells. **d, M**arker genes for 9 distinct clusters of mouse WAT vascular cells. e, Riverplot showing the correlation between annotated mouse and human vascular clusters based on multimodal reference mapping for each mouse cell. **f-g**, Bar graphs showing the proportion of cells in each cluster per sample split by depot and BMI for human (f) and depot, diet, and sex for mouse (g). For humans, n = 9 SAT < 30, 6 SAT > 40, 3 VAT < 30, and 5 VAT > 40. For male mice n = 4 ING Chow, 4 ING HFD, 3 EPI Chow, and 5 EPI HFD. For female mice, n = 2 per condition. For bar graphs, error bars represent SEM, * indicates credible depot effect and # indicates credible BMI/diet effect, calculated using hEndoA2 (human) and mEndoA2 (mouse) as reference.

**Extended Data Fig. 4.. Comparison of immune cells in human and mouse WAT.**
a, UMAP projection of 34,268 immune cells from human WAT. b, Marker genes for human immune cell clusters. c, UMAP projection of 70,547 immune cells from mouse WAT. d, Marker genes for mouse immune cell clusters. **e-f,** Riverplots showing the correlation between annotated mouse cluster and mapped human cluster for mouse (e) dendritic cells, mast cells, neutrophils, B cells, NK cells, and T cells and (f) monocytes and macrophages.

**Extended Data Fig. 5.. Human and mouse immune cells are differentially regulated by depot and BMI/diet.**
**a-b,** UMAP projections of human (a) and mouse (b) WAT immune cells split by depot. **c-d,** UMAP projections of human (c) and mouse (d) WAT immune cells split by BMI (c) and diet (d). **e-f,** Bar graphs showing the proportion of cells in each cluster per sample split by depot and BMI for human (e) and depot, diet, and sex for mouse (f). For humans, n = 10 SAT < 30, 6 SAT > 40, 3 VAT < 30, and 5 VAT > 40. For male mice n = 4 ING Chow, 4 ING HFD, 3 EPI Chow, and 5 EPI HFD. For female mice, n = 2 per condition. For bar graphs, error bars represent SEM, * indicates credible depot effect and # indicates credible BMI/diet effect, calculated using hMono2 (human) and mcDC1 (mouse) as reference.

**Extended Data Fig. 6.. Subpopulations of human and mouse mesothelial cells.**
a, UMAP projection of 30,482 human mesothelial cells. b, Marker genes for distinct human mesothelial populations. c, UMAP projection of 14,947 mouse mesothelial cells. d Marker genes for distinct mouse mesothelial populations. e, Riverplots showing relationship of mouse and human mesothelial clusters. **f-g,** Proportion of cells in each cluster per sample, split by BMI for human (f) and diet and sex for mouse (g). For humans, n = 3 VAT < 30, and 5 VAT > 40. For male mice n = 3 EPI Chow, and 5 EPI HFD. For female mice, n = 2 per condition. Error bars represent SEM, # indicates credible BMI/diet effect, calculated using hMes3 (human) and mMes1 (mouse) as reference.

**Extended Data Fig. 7.. Human and mouse ASPCs share commonalities with previously reported subtypes.**
a, UMAP projection of 52,482 human ASPCs. b, Marker genes for distinct ASPC subpopulations. c, UMAP projection of 51,227 mouse ASPCs. d, Marker genes for distinct ASPC subpopulations. e, Riverplot depicting the relationship between mouse and human ASPC clusters. f, Integration of ASPCs from this paper with ASPCs from other groups.

**Extended Data Fig. 8.. Human ASPCs exhibit strong depot dependency while mouse ASPCs are dependent on both depot and diet.**
**a-b,** UMAP projections of human (a) and mouse (b) ASPCs split by depot. **c-d,** UMAP projections of human (c) and mouse (d) ASPCs split by BMI/diet. **e-f,** Proportion of ASPC cells in each cluster per sample split by depot and BMI for human (e) and depot, diet, and sex for mouse (f). For humans, n = 11 SAT < 30, 6 SAT > 40, 3 VAT < 30, and 5 VAT > 40. For male mice n = 4 ING Chow, 4 ING HFD, 3 EPI Chow, and 5 EPI HFD. For female mice, n = 2 per condition. For bar graphs, error bars represent SEM, * indicates credible depot effect and # indicates credible BMI/diet effect, calculated using hASPC2 (human) and mASPC4 (mouse) as reference.

**Extended Data Fig. 9.. Human adipocyte subtypes are highly dependent on depot and may be responsible for distinct functions.**
**a-b,** UMAP projections of human white adipocytes split by depot (a) and BMI (b). c, Proportion of cells in each human cluster by sample split by depot and BMI, n = 4 SAT < 30, 6 SAT > 40, 3 VAT < 30, and 5 VAT > 40. D, Quantification of immunofluorescence analysis of GRIA4+ cells in mature human adipocytes from two individuals. Each dot represents an image, n = 12 images from individual 1 and 9 images from individual 2 with a total of 704 counted cells. Only cells with visible nuclei were included in the quantification. e, Representative image of GRIA4+ cells, white arrows represent positive cells, grey represent negative, scale bar = 100 μm. In total, there were 21 images from samples taken from two individuals. f, Expression of genes associated with adipokine secretion, insulin signaling, lipid handling, and thermogenesis across human adipocyte subclusters. **g-m,** Expression of genes associated with GO or KEGG pathways indicative of individual human adipocyte subclusters. For bar graph, error bars represent SEM, * indicates credible depot effect and # indicates credible BMI effect, calculated using hAd5 as reference.

**Extended Data Fig. 10.. Human adipocytes differentiated ex vivo recapitulate many of the adipocyte subclusters found in vivo.**
a, Plot of estimated cell type proportion in *ex vivo* adipocyte cultures differentiated from subcutaneous or visceral preadipocytes for 14 days, ordered by estimated proportion. **b-c,** Scatterplots showing the relationship between estimated cell type proportion and the LipocyteProfiler-calculated features Large BODIPY objects (b) and Median BODIPY Intensity (c). p values were calculated using an F-test with the null hypothesis that the slope = 0. d, Representative images of hAd3 low/hAd5 or hAd3 high hAd5 low *ex vivo* differentiated cultures. Green represents BODIPY staining, blue represents Hoechst staining. Scale bars are 100 μm, in total, 3 randomly selected images/sample were analyzed from 3 SAT samples and 3 VAT samples with the lowest and highest predicted proportions of hAd3 and hAd5.

**Extended Data Fig. 11.. Visceral-specific adipocyte subpopulation hAd6 is associated with thermogenic traits.**
a, Regional visualization of associations of common genetic variants near EBF2 with VATadj. b, Effect size of association of rs4872393 with VATadj, ASATadj, GFATadj, and BMI per minor allele A; n = 37,641. Error bars reflect a 95% confidence interval around the effect size estimate from regression. c, VATadj raw data plotted according to rs4872393 carrier status; n = 36,185. For box plots, horizontal line = median, lower and upper bounds of the box = 1^st and 3^rd quartile respectively, lower and upper whisker = 1^st quartile – 1.5 x interquartile range (IQR) and 3^rd quartile + 1.5 x IQR respectively, outliers are plotted as points. d, Scatterplot showing the relationship between estimated cell type proportion and the LipocyteProfiler calculated feature Mitochondrial Intensity in visceral samples. e, Expression of mitochondrial and thermogenic genes in visceral *ex vivo* differentiated adipocytes stratified by estimated hAd6 proportion and matched for amount of differentiation using *PPARG* expression, n = 7 mAd6 low and 5 mAd6 high. Error bars represent SEM, p values were calculated using two tailed t-tests with no adjustments for multiple comparison, *, p < .05, **, p < .01. Exact p values: *EBF2* = 0.027, *TFAM* = 0.019, *CKMT1A* = 0.049, *CKMT1B* = 0.005. f, Representative images of hAd6 low and high visceral in vitro differentiated cultures. Green represents BODIPY staining, red represents MitoTracker staining, and blue represents Hoechst staining. Scale bars are 100 μm, in total 3 random images/sample were analyzed from 5 hAd6 low and 5 hAd6 high samples. g, Violin plot of sNuc-seq data showing axon guidance genes in adipocyte subclusters. h, Scatterplots showing the relationship between calculated proportion of visceral subpopulations hAd2 and hAd6 and expression of pan-neuronal markers on the ambient RNA of individual visceral sNuc-seq samples. For scatterplots, p values were calculated using an F-test with the null hypothesis that the slope = 0.

**Extended Data Fig. 12.. Mouse adipocytes appear to have distinct functionality but are not analogous to human adipocyte subpopulations.**
**a-b,** UMAP projections of mouse adipocytes split by depot (a) and diet (b). c, Proportion of cells in each mouse cluster per sample split by depot, diet, and sex. For male mice n = 4 ING Chow, 4 ING HFD, 3 EPI Chow, and 5 EPI HFD. For female mice, n = 2 per condition. d, Expression of genes associated with known adipocyte functions in mouse adipocyte subclusters. **e-k,** Expression of genes associated with GO or KEGG pathways indicative of individual mouse adipocyte subclusters. **l-n,** Riverplots of mouse cells showing the association between mouse and human adipocyte clusters from both subcutaneous and visceral depots (l), subcutaneous (ING and SAT) adipocytes only (m) or visceral (PG and VAT) adipocytes only (n). For depot comparisons, both mouse query objects and human reference objects were subset to the respective depot before mapping. For bar graph, error bars represent SEM, * indicates credible depot effect and # indicates credible diet effect, calculated using mAd6 as reference.

**Extended Data Fig. 13.. CellphoneDB identifies increasing numbers of cell-cell interactions within WAT during obesity.**
a, Heatmap showing number of significant interactions identified between cell types in SAT of low (<30) and high (>40) BMI individuals as determined by CellphoneDB. b, Expression of ligand and receptor genes from Figure 4b in human adipocyte subclusters. c, Heatmaps showing number of significant interactions identified between cell types in ING and PG WAT of chow and HFD fed mice. d, Venn diagrams showing the overlap of significant interactions between adipocytes and endothelial cells, ASPCs, and macrophages between depot, BMI/diet, and species. e, Jitter plots of the relationship between number of WAT cell types expressing a ligand (y axis) vs. the number of cell types expressing the receptor (x axis) for all significant interactions in high BMI human VAT (left) and mouse HFD PG (right).

**Extended Data Fig. 14.. Association with GWAS data provides further insight into the contribution of white adipocytes to human traits.**
**a-c,** Expression of *PPARG* in human adipocyte subclusters (a), and in METSIM SAT bulk RNA-seq plotted against WHR (b) or HOMA-IR (c). d, Expression of *PPARG* in isolated subcutaneous adipocyte bulk RNA-seq plotted against HOMA-IR. **e-h,** SNPs in the *PPARG* gene identified by DEPICT as associated with BMI-adjusted WHR plotted against *PPARG* gene expression (**e, g**) and HOMA-IR (**f, h**) in isolated subcutaneous adipocyte bulk RNA-seq data and cohort. For rs17819328 n = 7 for T/T, 30 for T/G, and 6 for G/G. For rs1797912 n = 7 for A/A, 31 for A/C, and 5 for C/C. For box plots, horizontal line = median, lower and upper bounds of the box = 1^st and 3^rd quartile respectively, lower and upper whisker = 1^st quartile – 1.5 x interquartile range (IQR) and 3^rd quartile + 1.5 x IQR respectively. p values were calculated using a Wilcoxin test. **i-j,** Expression of genes in human adipocyte subtypes from sNuc-seq data (i) and from isolated subcutaneous adipocyte bulk RNA-seq plotted against LDL (j). k, p values of the association between mouse cell types and GWAS studies. **l-m,** p values of the association between mouse adipocyte (l) or ASPC (m) subclusters with GWAS studies. For all graphs, the grey line represents p = 0.05 and the orange line represents significant p value after Bonferroni adjustment (p = 0.003 for all cell, p = 0.001 for subclusters), calculated based on number of cell types queried. For scatterplots, p values were calculated using an F-test with the null hypothesis that the slope = 0.

**Fig. 1.. A single cell atlas of human white adipose tissue.**
a, Schematic of workflows for scRNA-seq and sNuc-seq of human WAT. b, Graphical representation of the cohorts for both studies. Only the sNuc-seq cohort contains VAT. c, UMAP projection of all 166,129 sequenced human cells split by cohort. d, Marker genes for each cell population in the human WAT dataset.

**Fig. 2.. A single cell atlas of mouse white adipose tissue.**
a, Schematic of workflow for sNuc-seq of mouse ING and PG adipose tissue. a, Body weight of chow and high fat fed animals used for sNuc-seq (n = 5 chow and 5 HFD male mice, 2 chow and 2 HFD female mice). Error bars represent standard error of the mean (SEM). c, UMAP projection of all 197,721 sequenced mouse cells split by diet. d, Marker genes for each cell population in the mouse WAT dataset.

**Fig. 3.. Subclustering of human and mouse adipocytes reveals multiple distinct populations that vary across depot and diet.**
a, UMAP projection of clusters formed by 25,871 human white adipocytes. b, Expression of adipocyte marker *ADIPOQ* and specific marker genes for each adipocyte subpopulation. c, IHC for marker genes of adipocyte subpopulations hAd4, hAd5, hAd6, and hAd7 in human adipose tissue and percentage of positive adipocytes per slide in lean and obese individuals (GRIA4: 5 lean, 5 obese, 2 slides each; PGAP1: 5 lean SAT, 4 obese SAT, 3 lean VAT, 4 obese VAT, 1 slide each; EBF2: 3 lean, 4 obese, 2 slides each; AGMO: 4 lean, 4 obese, 2 slides each). Scale bars are 25 μm for GRIA4, EBF2, and AGMO, 20 μm for PGAP1. d, Estimated proportions of adipocyte subpopulations in bulk RNA sequencing data of enzymatically isolated subcutaneous adipocytes from 43 individuals plotted against BMI. p values were calculated using an F-test (with null hypothesis slope = 0), error bands represent a confidence level of 0.95. e, Representative images of *ex vivo* differentiated human subcutaneous adipocytes predicted to have low or high hAd3 content based on deconvolution of bulk RNA sequencing data. Green represents BODIPY staining, blue represents Hoechst staining. Scale bars are 100 μm. f, Normalized count of BODIPY-related features in *ex vivo* differentiated adipocytes stratified into hAd3 low and high populations. Points represent normalized feature for cultures derived from individual subjects, n = 8 hAd3 low SAT, 4 hAd3 high SAT, 19 hAd3 low VAT, 4 hAd3 high VAT. g, UMAP projection 39,934 mouse white adipocytes. h, Expression of *Adipoq* and marker genes for each mouse adipocyte subpopulation. For bar graphs, error bars represent SEM, p values were calculated using two tailed t-tests with no correction for multiple comparisons.

**Fig. 4.. Extensive cell-cell interactions in WAT and associations with human disease traits.**
a, Heatmap showing number of significant interactions identified between cell types in VAT of low (<30) and high (>40) BMI individuals as determined by CellphoneDB. b, Selected interactions between adipocytes and ASPCs, endothelial cells, and macrophages identified using CellphoneDB; orange and green indicate interactions that are significant only in BMI > 40 or only in BMI >30, respectively. c, CELLECT p values of the association between cell types in the human adipose sNuc-seq dataset with GWAS studies. The grey line represents p = 0.05 and the orange line represents significant p value after Bonferroni adjustment (p = 0.003), based on number of cell types queried. Both T2D and WHR were BMI-adjusted. d, CELLECT p values for adipocyte subpopulations. The grey line represents p = 0.05 and the orange line represents significant p value after Bonferroni adjustment (p = 0.001), based on all cell subtypes queried. e, Estimated cell type proportion of hAd7 in bulk RNA-seq data of enzymatically isolated subcutaneous adipocytes from 43 individuals plotted against HOMA-IR. For line of best fit, R² = 0.11, the error band represents a confidence level of 0.95. f-g, Expression of hAd7 marker genes negatively correlated with HOMA-IR in human adipocyte subpopulations (f) and bulk RNA sequencing data of human adipocytes (g). For scatterplots, p values were calculated using an F-test with the null hypothesis that the slope = 0.

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Can we target obesity using a single-cell atlas of adipose tissue?
Scheele C, Nielsen S. Scheele C, et al. Med. 2022 May 13;3(5):276-278. doi: 10.1016/j.medj.2022.04.006. Epub 2022 May 13. Med. 2022. PMID: 35584644

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References

1. Rosen ED & Spiegelman BM What We Talk About When We Talk About Fat. Cell 156, 20–44 (2014). - PMC - PubMed
1. Kahn SE, Hull RL & Utzschneider KM Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 444, 840–846 (2006). - PubMed
1. Schwalie PC et al. A stromal cell population that inhibits adipogenesis in mammalian fat depots. Nature 559, 103–108 (2018). - PubMed
1. Burl RB et al. Deconstructing Adipogenesis Induced by β3-Adrenergic Receptor Activation with Single-Cell Expression Profiling. Cell Metab. 28, 300–309.e4 (2018). - PMC - PubMed
1. Merrick D et al. Identification of a mesenchymal progenitor cell hierarchy in adipose tissue. Science 364, (2019). - PMC - PubMed

METHODS REFERENCES

1. Chi J et al. Three-Dimensional Adipose Tissue Imaging Reveals Regional Variation in Beige Fat Biogenesis and PRDM16-Dependent Sympathetic Neurite Density. Cell Metab. 27, 226–236.e3 (2018). - PubMed
1. Katz A et al. Quantitative Insulin Sensitivity Check Index: A Simple, Accurate Method for Assessing Insulin Sensitivity In Humans. J. Clin. Endocrinol. Metab 85, 2402–2410 (2000). - PubMed
1. Matthews DR et al. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412–419 (1985). - PubMed
1. Macosko EZ et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell 161, 1202–1214 (2015). - PMC - PubMed
1. Drokhlyansky E et al. The Human and Mouse Enteric Nervous System at Single-Cell Resolution. Cell 182, 1606–1622.e23 (2020). - PMC - PubMed

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A single-cell atlas of human and mouse white adipose tissue

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A single-cell atlas of human and mouse white adipose tissue

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