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Single-cell analysis of human adipose tissue identifies depot- and disease-specific cell types

Abstract

The complex relationship between metabolic disease risk and body fat distribution in humans involves cellular characteristics that are specific to body fat compartments. Here we show depot-specific differences in the stromal vascular fraction of visceral and subcutaneous adipose tissue by performing single-cell RNA sequencing of tissue specimens from obese individuals. We characterize multiple immune cells, endothelial cells, fibroblasts, adipose and haematopoietic stem cell progenitors. Subpopulations of adipose-resident immune cells are metabolically active and associated with metabolic disease status, including a population of potential dysfunctional CD8+ T cells that express metallothioneins. We identify multiple types of adipocyte progenitors that are common across depots, including a subtype enriched in individuals with type 2 diabetes. Depot-specific analysis reveals a class of adipocyte progenitors unique to visceral adipose tissue, which shares common features with beige pre-adipocytes. Our human single-cell transcriptome atlas across fat depots provides a resource to dissect the functional genomics of metabolic disease.

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Fig. 1: Identified cell populations in the non-adipocyte fraction of adipose tissue.
Fig. 2: SVF-derived immune cells.
Fig. 3: SVF-derived progenitor clusters.
Fig. 4: Main cell clusters in the SVF based on depot.
Fig. 5: Progenitor clusters specific to the SAT.
Fig. 6: Progenitor clusters specific to the VAT derived from individuals with obesity.
Fig. 7: Progenitor clusters specific to the VAT derived from a healthy individual.

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Data availability

Raw data files from single-cell and bulk RNA-seq used in this study are uploaded in the Gene Expression Omnibus (GEO) in a SuperSeries with accession number: GSE136230. The expression data from the MuTHER cohort have been deposited in the ArrayExpress (https://www.ebi.ac.uk/arrayexpress/) with accession number E-TABM-1140. Source data are available online for Figs. 3, 5 and 6, and Supplementary Fig. 6.

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Acknowledgements

This work was supported by a Canadian Institute of Health Research (CIHR) team grant awarded to E.G. (EGM141898) and the CIHR-funded Epigenome Mapping Centre at McGill University (EP1-120608) awarded to T.P. E.G. holds the Roberta D. Harding & William F. Bradley, Jr. Endowed Chair in Genomic Research and T.P. holds the Dee Lyons/Missouri Endowed Chair in Pediatric Genomic Medicine. A.T. is the director of a Research Chair in Bariatric and Metabolic Surgery. M.C.V. is the recipient of the Canada Research Chair in Genomics Applied to Nutrition and Metabolic Health (tier 1). The MuTHER study was funded by a program grant from the Wellcome Trust (081917/Z/07/Z) and core funding for the Wellcome Trust Centre for Human Genetics (090532). The TwinsUK study was funded by the Wellcome Trust and European Community’s Seventh Framework Programme (FP7/2007-2013). The TwinsUK study also receives support from the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. The authors thank M. Korhonen and M. Ahti at the Finnish Red Cross Blood Service, Helsinki, Finland, for valuable help in this study. The GTEx Project was supported by the Common Fund of the Office of the Director of the NIH, and by the National Cancer Institute (NCI), National Human Genome Research Institute (NHGRI), National Heart, Lung and Blood Institute (NHLBI), National Institute of Drug Abuse (NIDA), National Institute of Mental Health (NIMH) and National Institue of Neurological Disorders and Stroke (NINDS). The data used for the analyses described in this manuscript were obtained from the dbGaP accession number phs000424.v7.p2 on 7 October 2019.

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Authors

Contributions

E.G. conceived the study. E.G., A.T., T.P. and M.-C.V. designed experiments. A.T., J.D.F. and M.-F.G prepared or provided the clinical samples. L.B. and B.B. managed the clinical aspects of the study. A.P., R.L.B., M.G., D.A.L. and M.-M.S performed the experiments. W.A.C, J.J.J., H.D., A.S. and G.B. provided bioinformatics support. A.L and J.N. provided the MSC cell lines and culture protocols. J.V. and E.G. analysed the data and drafted the manuscript. All authors reviewed and contributed feedback on the final manuscript.

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Correspondence to André Tchernof or Elin Grundberg.

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A.T. receives funding from Johnson & Johnson Medical Companies and Medtronic for research unrelated to the present manuscript. The other authors declare no competing interests.

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Editor recognition Primary handling editor: Elena Bellafante.

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Extended data

Extended Data Fig. 1 Multiple macrophage clusters were identified in SVF from both SAT and VAT depots.

Multiple macrophage clusters were identified in SVF from both SAT and VAT depots (a) 4 distinct macrophage clusters showing varying expression of CD68 (19–52% of cells), CD9 (10–51% of cells) and CD36 (25–72% of cells). The y axis of the violin plot indicate log transformed expression values and the width indicate number of cells expressing the particular gene. (b)Genes involves in lipid metabolism is found expressed in macrophage cluster – IS2, whereas IS3 is rich in inflammatory markers.

Extended Data Fig. 2 Gene expression of marker genes in 6 visceral specific progenitor clusters.

Gene expression of marker genes in 6 visceral specific progenitor clusters. The y axis of the violin plot indicate log transformed expression values and the width indicate number of cells expressing the particular gene.

Supplementary information

Supplementary Information

Supplementary Figures 1–7

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Supplementary Tables

Supplementary Tables 1–23

Supplementary Data

Statistical source data for Supplementary Figure 6

Source data

Source Data Fig. 3

Statistical source data for Figure 3c

Source Data Fig. 5

Statistical source data for Figure 5d and 5f

Source Data Fig. 6

Statistical source data for Figure 6d

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Vijay, J., Gauthier, MF., Biswell, R.L. et al. Single-cell analysis of human adipose tissue identifies depot- and disease-specific cell types. Nat Metab 2, 97–109 (2020). https://doi.org/10.1038/s42255-019-0152-6

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