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Obesity and hyperinsulinemia drive adipocytes to activate a cell cycle program and senesce

Nature Medicine volume 27, pages 1941–1953 (2021)Cite this article

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Abstract

Obesity is considered an important factor for many chronic diseases, including diabetes, cardiovascular disease and cancer. The expansion of adipose tissue in obesity is due to an increase in both adipocyte progenitor differentiation and mature adipocyte cell size. Adipocytes, however, are thought to be unable to divide or enter the cell cycle. We demonstrate that mature human adipocytes unexpectedly display a gene and protein signature indicative of an active cell cycle program. Adipocyte cell cycle progression associates with obesity and hyperinsulinemia, with a concomitant increase in cell size, nuclear size and nuclear DNA content. Chronic hyperinsulinemia in vitro or in humans, however, is associated with subsequent cell cycle exit, leading to a premature senescent transcriptomic and secretory profile in adipocytes. Premature senescence is rapidly becoming recognized as an important mediator of stress-induced tissue dysfunction. By demonstrating that adipocytes can activate a cell cycle program, we define a mechanism whereby mature human adipocytes senesce. We further show that by targeting the adipocyte cell cycle program using metformin, it is possible to influence adipocyte senescence and obesity-associated adipose tissue inflammation.

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Fig. 1: Mature human adipocytes express a cell cycle transcriptional profile.
Fig. 2: Mature human adipocytes are positive for cell cycle markers.
Fig. 3: Adipocyte cell cycle progression is associated with obesity and hyperinsulinemia.
Fig. 4: Insulin induces adipocyte cell cycle reentry and EdU incorporation.
Fig. 5: Adipocyte senescence is induced by obesity and insulin resistance.
Fig. 6: Cell cycle entry or arrest governs adipocyte senescence.

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Data availability

The datasets generated and analyzed during the current study can be accessed from https://gitlab.inria.fr/knibbe/adipocyte-senescence/ (cyclin A2 and SABG datasets) and https://github.com/PingChen-Angela/Adipocytes_cell_cycle/ (data repository for mRNA-seq gene expression matrix (RPKMs) and sample group annotations). Source data are provided with this paper.

Code availability

Regression analysis scripts (for cyclin A2 and SABG analyses) are available at https://gitlab.inria.fr/knibbe/adipocyte-senescence/ and mRNA-seq codes are available at https://github.com/PingChen-Angela/Adipocytes_cell_cycle/.

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Acknowledgements

We acknowledge the assistance of research nurses A. Bratt and A. -S. Andersson (Ersta Hospital) and laboratory technicians L. Appelsved and A. Olsson. This study was supported by grants from the Swedish Research Council (no. 542-2013-8358 to K.S., no. 350-2012-6538 to C.E.H.), the Strategic Research Program for Diabetes at Karolinska Institutet (no. C5471152 to K.S.), the Novo Nordisk Foundation (Excellence Project Award no. NNF12OC1016064 to K.S.), the Karolinska Institutet/AstraZeneca Integrated Cardiometabolic Centre (no. H725701603 to K.S.), the Erling-Persson Family Foundation (no. 140604 to A.T.), the Swedish Foundation for Strategic Research (I.A.) and the Vallee Foundation Vallee Scholar Award (no. C5471234 to K.S.). C.E.H. was supported by the Swedish Society for Medical Research (no. P13-0057) and Wilhelm och Else Stockmanns Stiftelse.

Author information

Author notes

  1. These authors contributed equally: Qian Li, Carolina E. Hagberg.

Authors and Affiliations

  1. Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden

    Qian Li, Shuai Lang, Mervi T. Hyvönen, Niels Krämer & Kirsty L. Spalding

  2. Karolinska Institutet/AstraZeneca Integrated Cardio Metabolic Centre (KI/AZ ICMC), Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden

    Carolina E. Hagberg, Helena Silva Cascales, Firoozeh Salehzadeh, Ping Chen, Eleni Terezaki, Maria Kutschke, Nahida Arifen, Myriam Aouadi & Kirsty L. Spalding

  3. Cardiovascular Medicine Division, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden

    Carolina E. Hagberg

  4. School of Pharmacy, University of Eastern Finland, Kuopio, Finland

    Mervi T. Hyvönen

  5. Center for Infectious Medicine, Department of Medicine, Karolinska Institute, Stockolm, Sweden

    Ping Chen & Myriam Aouadi

  6. Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

    Ida Alexandersson, Matthew J. Harms & Jeremie Boucher

  7. Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm, Sweden

    Maria Kutschke

  8. CarMeN Laboratory, Lyon University, INRIA, INSA Lyon, Lyon, France

    Carole Knibbe

  9. The Lundberg Laboratory for Diabetes Research, University of Gothenburg, Gothenburg, Sweden

    Jeremie Boucher

  10. Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden

    Jeremie Boucher

  11. Department of Clinical Science, Danderyds Hospital, Karolinska Institutet and Department of Surgery, Ersta Hospital, Karolinska Institutet, Stockholm, Sweden

    Anders Thorell

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Contributions

K.L.S., C.E.H. and Q.L. designed the study. A.T. recruited the participants. F.S., C.E.H., P.C. and J.W. prepared and analyzed sequencing samples. Q.L., C.E.H., S.L., H.S.C., E.T. and M.K. developed and performed adipocyte ICC, IHC and senescence stainings. Q.L., S.L., I.A., N.K., E.T. and M.H. designed and performed in vitro experiments and molecular analyses. M.H., I.A., M.A. and J.B. did western blotting. C.H., Q.L., H.S.C., N.K. and C.K. performed statistical analyses and C.K. performed the multiple-regression analyses. C.E.H., Q.L. and K.L.S. wrote the first version of the paper. Q.L. prepared the figures. All authors contributed to and approved the final version of the paper.

Corresponding author

Correspondence to Kirsty L. Spalding.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information: Nature Medicine thanks Suneil Koliwad, Lluis Fajas, Valery Krizhanovsky and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Jennifer Sargent was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Purity of isolated human adipocytes and the expression of a cell cycle transcriptional profile.

a. Representative transmitted light image showing pure fractions of isolated adipocytes without the presence of contaminating stromal vascular cells. Scale bar, 100 µm. The experiment was repeated for each isolation with similar results. b. QPCR analysis of CD45 mRNA expression in isolated mature adipocytes compared to CD45+/CD14+ macrophages sorted by flow cytometry, showing both raw CT values (left) and relative abundance (right, normalized to 18S expression, mean ± SEM). Each dot represents one individual, with the n indicated in the figure. c. RNA-Seq data (mean ± SD) showing the expression of adipocyte-specific (LEP, ADIPOQ, CIDEC, PLIN1, TUSC5) and pre-adipocyte specific (WNT10B, PDGFRA) genes in isolated human adipocytes (n = 13, blue bars) and in FACS sorted and sequenced preadipocyte samples (n = 3, red bars). Note the logarithmic scale. d. Table showing the absence of immune cell markers in the adipocyte mRNA sequencing dataset. e. RNA-Seq data (mean ± SD) showing expression of cell death related transcripts in isolated human adipocytes. N= 3 lean, 6 OB/NI, and 4 OB/HI individuals. f. Correlation between C-peptide and HOMA-IR levels for each individual using two-sided Spearman correlation. g. Enriched pathways for lean individuals based on the differentially expressed genes shown in Extended Data Fig. 2 based on Kruskal-Wallis tests. h. Percentage of S-phase associated transcripts (as listed by Wikipathways and Pathcards, n=123 genes) detected in four or more individuals with obesity out of the 13 analysed adipocyte mRNA sequencing samples. i. Relative mRNA expression of CCNA2 (cyclin A2) in mature adipocytes from WOB, OB/NI and OB/HI individuals, with the n indicated in the plot (mean ± SD). Data are normalized to TATA-box binding protein (TBP) expression and analyzed using Welch ANOVA test, followed by a Dunnett’s T3 multiple comparisons test.

Extended Data Fig. 2 Differentially expressed genes between patient groups.

Heatmap of RNA-seq data showing the differentially expressed genes in Lean, OB/NI, and OB/HI individuals (n = 13 individuals). Each column represents data from one individual. Colour intensity represents row Z-score.

Extended Data Fig. 3 Adipocyte cell cycle re-entry markers correlate with metabolic parameters.

a. Correlation between the percentage of adipocytes positive for cell cycle markers (cyclin D1, cyclin A2, pHH3 and cyclin E1) as determined by ICC, and serum insulin, HbA1c (glycosylated hemoglobin A1c), insulin-like growth factor 1 (IGF-1), triglyceride (TG) and low-denisty liporpotein (LDL) levels. Each dot represents the percentage of positive adipocytes from one individual,with individual number (n) indicated in each plot. Plots highlighted in grey indicate a significant correlation (p < 0.05) using two-sided Spearman correlation analysis. b. QPCR quantification of relative CCND1 (cyclin D1) and CCNA2 (cyclin A2) mRNA expression correlated with C-peptide levels and patient BMI (n = 16 individuals) using two-sided Spearman correlation. Data are normalized to TBP expression.

Extended Data Fig. 4 Statistical analysis of correlations between cell cycle–related markers and patient clinical parameters.

Correlation between the percentage of adipocytes positive for cell cycle markers (cyclin E1, cyclin D1, cyclin A2, pHH3, as determined by ICC), adipocyte cell or nuclear size and clinical parameters. Data was analysed using two-sided Spearman correlation analysis, with individual number (n) indicated in each row. Blocks highlighted in light red indicate a significant correlation (p < 0.05), blocks highlighted in dark red indicate a highly significant correlation (p < 0.0001).

Extended Data Fig. 5 Insulin induces adipocyte cell cycle re-entry and EdU incorporation.

a. Representative flow cytometric analysis of EdU staining in nuclei isolated from adipocytes unstained (left) or stained for EdU (right), demonstrating how the gates were set based on unstained samples. b. Image cytometry-based quantification of nuclear DNA, showing the integrated density (area x median staining intensity) of immobilized Dapi-stained nuclei for two lean individuals (grey, n = 52 nuclei in individual 1, n = 109 nuclei in individual 2) and four individuals with obesity (blue, n = 89 nuclei in individual 1, n = 96 nuclei in individual 2, n = 113 nuclei in individual 3, n = 133 nuclei in individual 4), with the corresponding histograms for each group to the right. In the left graph, each dot represents one nucleus with mean ± SD. c. Nuclear size quantification from adipocyte ICC images showing the fold change in mean nuclear size of cyclin A2 positive adipocytes, compared to cyclin A2 negative adipocytes (set to 1.0) from the same individual, analyzed by two-sided Wilcoxon paired test. Each dot represents the fold change from one individual, with >70 nuclei measured per individual by imaging quantification (n = 21 individuals). Mean ± SEM. d. Correlation between the rate of adipocyte EdU incorporation when cultured in basal medium for 4 days, and clinical parameters. For d-e, each dot represents one individual. Grey plot highlighting indicates a significant correlation (p < 0.05) using two-sided Spearman correlation analysis. e. Correlation between the insulin-mediated response in adipocyte EdU incorporation (by comparing the ratio of EdU positive adipocytes when cultured with exogenous insulin to cultures without) and clinical parameters using two-sided Spearman correlation. f. Quantification of western blot shown in Fig. 4i. g. Quantification of western blots shown in Fig. 4j.

Extended Data Fig. 6 Adipocyte senescence is induced by obesity and insulin resistance.

a. Correlation bewteen adipocyte Ki-67 (left) and PCNA (right) positivity assessed by IHC, and individual C-peptide using two-sided Spearman correlation. For panels a, d, e, g–i, each dot represents one individual. b. Top 10 enriched pathways of genes significantly correlated with CCND1 (Cyclin D1) expression using two-sided pairwise Spearman correlation, sorted by descending significance. Senescence-associated pathways are highlighted in bold. c. Representative IHC images of human adipose tissue stained for galactosidase beta 1 (GLB1) (upper panel). Scale bar, 50 µm. Detail of an adipocyte nucleus enlarged for clarity (below, scale bar 10 µm). Experiment was repeated twice independently for 13 individuals with similar results. d. Correlation between the percentage of SABG positive adipocytes and clinical parameters using two-sided Spearman correlation. e. BMI distribution for the three different patient groups analysed in Fig. 5e. Individual number (n), is indicated for each plot. Mean ± SEM analyzed by one-way ANOVA, followed with Holm-Sidak’s multiple comparison test. f. Contribution of each predictor (clinical parameter) to the SABG regression model shown in Fig. 5f. A positive value means that the predictor improves the goodness-of-fit when it is added last to a model containing all the other predictors. g. Age distribution for the three different patient groups analysed in Fig. 5e. Individual number (n) is indicated for each plot. Mean ± SEM analyzed by Kruskai-Wallis, followed with Dunn’s multiple comparison test. h. Representative images of adipocytes labelled by ICC with senescence marker HMGB1. Individual positive and negative adipocytes are indicated by white circles. Scale bar, 50 µm. Correlation between the percentage of HMGB1 negative adipocytes and SABG positivity analyzed by two-sided Spearman is shown to the right. i. Relative mRNA expression of SASP-associated transcripts in mature adipocytes from WOB, OB/NI and OB/HI individuals (n = 4 per group). Mean ± SD, analyzed by one-way ANOVA, followed with Holm-Sidak’s multiple comparison test.

Extended Data Fig. 7 Statistical analysis of the correlations between senescence-related markers and individual clinical parameters.

Correlation between the percentage of adipocytes positive for senescence-related markers (SABG, p16, γΗ2ΑΧ) as determined by ICC and clinical parameters. Data was analysed with two-sided Spearman correlation analysis, with individual number (n) indicated for each block. Blocks highlighted in light red indicate a significant correlation (p < 0.05); blocks highlighted in dark red indicate a highly significant correlation (p < 0.0001).

Extended Data Fig. 8 Cell cycle entry or arrest governs adipocyte senescence.

a. Percentage of EdU positive adipocytes cultured with exogenous insulin for 4 or 7 days. Individual number (n), is indicated for each plot. Mean ± SEM, analyzed using two-sided Mann Whitney test. For panels a–c, each dot represents one individual. b. RNA-Seq data showing expression of cell death related transcripts in adipocytes cultured with or without insulin for 7 days. N = 3, mean ± SD analyzed with two-way ANOVA with Dunnett’s multiple comparison test. c. Correlation between individual serum insulin levels and the percentage of SABG positive adipocytes after treatment with insulin and palbociclib for 7 days, analyzed by two-sided Spearman correlation. d. Quantification of secreted SASP-proteins from adipocytes cultured with insulin and palbociclib, normalized to cultures with insulin only. Statistics were performed using paired t-tests with a FDR multiple testing correction set to 10% (N = 8 except for TIMP1 (n=10), MMP19, ADAMTS4, IP10 (n= 7), CTGF and IL-6 (n= 6) due to missing samples, mean ± SD). e, f. Western blots (e) and quantifications (f) showing the effect of palbociclib and metformin on the phosphorylation status of p70S6K and AKT in two different individuals. Actin was used as a loading control. g. Correlation between individual serum insulin levels and the percentage of SABG positive adipocytes after treatment with insulin and metformin using two-sided Spearman correlation. h. Quantification of secreted adiponectin from adipocytes cultured for 7 days as in Fig. 6. Data is shown normalized to INS cultures. N = 10 except for INS + Met and INS + Palbo (n= 9) due to missing samples. Mean ± SD analyzed by ANOVA followed with Holm-Sidak’s multiple comparison test. i. LDH-cytotoxicity test showing no detection of released cytoplasmic content to the culture media after any of the indicated treatments, with the lower limit for cell death detection noted by the red line (no statistical test used). As a positive control, adipocytes were lysed on day 1 (d1) or d3 of culture, and media harvested at d7 along with the other samples (n = 3 for each treatment, mean ± SD).

Source data

Extended Data Fig. 9 Schematic and omental adipocytes display a lower incidence of cell cycle and senescence markers.

a. Schematic representation of the effects of modulating adipocyte cell cycle entry and block on senescence. (1) During short term culture (4 days) insulin acts as a mitogen promoting cell cycle activity. Endogenous cellular stressors, such as lipotoxicity or oxidative stress, activate a DDR, inducing (amongst others) p16/p21 and blocking cell cycle progression. Continued mitogenic stimulation (insulin, ‘accelerator’), countered by continued cell cycle block (‘brake’) can result in adipocytes becoming senescent (blue adipocytes) and exiting cell cycle. (2) In response to prolonged hyperinsulinemia (adipocytes cultured for 7 days with insulin), an increased number of adipocytes progress through cell cycle, resulting in an increase in the number of internal cell cycle:cell block conflicts, which in turn increases adipocyte senescence. (3) Mimicking endogenous p16/p21 activity by culturing with the CDK4/6 inhibitor, palbociclib, in combination with mitogenic stimulation (insulin) accentuates the internal cell cycle:cell block conflict, resulting in increased adipocyte senescence. (4) Blocking cell cycle entry with metformin significantly reduces adipocyte cell cycle progression and adipocyte senescence. b. Relative mRNA expression of PCNA, CCNA2 (cyclin A2) and CDC20 in paired samples of mature adipocytes isolated from subcutaneous (SC) and omental (OM) fat from WOB (n = 4), OB/NI (n = 4) and OB/HI (n = 4) individuals. Data are normalized to TBP expression. For panels b-h, each dot represents one individual, paired samples are indicated with a line and statistics analyzed using two-sided paired Student’s t tests, except in panel f where a two-sided Wilcoxon paired test was used. c. Percentage of cyclin A2 positive adipocytes in paired SC and OM fat samples from 1 lean individual and 5 individuals with obesity. d. Percentage of EdU positive omental adipocytes following 4 days of floating culture with or without exogenous insulin. e. Representative images of paired SC and OM samples of packed isolated mature human adipocytes stained using the SABG assay. Each tube contains isolated adipocytes from the respective depots of one individual. Green/blue staining indicates increased β-galactosidase activity. f. Percentage of SABG positive adipocytes in paired SC and OM samples. g. Relative mRNA expression of CCND1 (cyclin D1), CDKNA1 (p21) and CCL2 (MCP-1) in the same paired SC and OM samples as in a. Data are normalized to TBP expression. h. Percentage of p16 positive adipocytes in paired SC and OM fat samples from 5 individuals with obesity.

Extended Data Fig. 10 Inguinal hernia repair and gall bladder surgical biopsies display no significant differences in all studied cellular parameters.

Subgroup analysis of the cellular parameters measured for individuals using biopsies obtained from two types of surgeries: inguinal hernia repair (Hernia) and gallstone operations (Gallstone), show no significant difference in cell and nuclear size, the expression of cyclins E1, D1, A2, pHH3 (determined by ICC), the percentage of SABG positive adipocytes, or the level of EdU incorpation after suspension culture (cultured samples). Individual number (n), is indicated for each plot. Data is shown as mean ± SD. Statistics were performed using a two-sided Student’s t test, ns stands for non-significant difference.

Supplementary information

Supplementary Information

Supplementary Tables 1–13. A description of patient cohorts and reagents used in the study.

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Source Data Fig. 4

Images from unprocessed blots shown in Fig. 4i,j.

Source Data Extended Data Fig. 8

Images from unprocessed blots shown in Extended Data Fig. 8e.

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Li, Q., Hagberg, C.E., Silva Cascales, H. et al. Obesity and hyperinsulinemia drive adipocytes to activate a cell cycle program and senesce. Nat Med 27, 1941–1953 (2021). https://doi.org/10.1038/s41591-021-01501-8

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