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Eosinophils regulate adipose tissue inflammation and sustain physical and immunological fitness in old age

Nature Metabolism volume 2, pages 688–702 (2020)Cite this article

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Abstract

Adipose tissue eosinophils (ATEs) are important in the control of obesity-associated inflammation and metabolic disease. However, the way in which ageing impacts the regulatory role of ATEs remains unknown. Here, we show that ATEs undergo major age-related changes in distribution and function associated with impaired adipose tissue homeostasis and systemic low-grade inflammation in both humans and mice. We find that exposure to a young systemic environment partially restores ATE distribution in aged parabionts and reduces adipose tissue inflammation. Approaches to restore ATE distribution using adoptive transfer of eosinophils from young mice into aged recipients proved sufficient to dampen age-related local and systemic low-grade inflammation. Importantly, restoration of a youthful systemic milieu by means of eosinophil transfers resulted in systemic rejuvenation of the aged host, manifesting in improved physical and immune fitness that was partially mediated by eosinophil-derived IL-4. Together, these findings support a critical function of adipose tissue as a source of pro-ageing factors and uncover a new role of eosinophils in promoting healthy ageing by sustaining adipose tissue homeostasis.

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Fig. 1: Age-related changes in the plasma proteome of humans and mice.
Fig. 2: Age-related changes in innate immune cell distribution of WAT in humans and mice.
Fig. 3: Heterochronic parabiosis restores ATE/ATM ratios and limits WAT inflammation.
Fig. 4: Transfer of eosinophils from young donors reverses ageing signatures in WAT and limits systemic inflammation.
Fig. 5: Eosinophils from young donors improve physical fitness in aged hosts.
Fig. 6: Eosinophil homing to WAT lowers age-related adipose tissue inflammation and improves physical fitness in aged recipients.
Fig. 7: Transfer of eosinophils into aged mice transiently alters HSC numbers and age-related myeloid skewing.
Fig. 8: Transfer of eosinophils into aged mice is associated with improved immunological fitness.
Fig. 9: Schematic representation illustrating the rejuvenating potential of young donor eosinophils in the aged host.

Data availability

Additional data that support the findings of this study are available from the corresponding authors upon reasonable request. Source data for Extended Data Fig. 1 are available online.

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Acknowledgements

We thank past and present members of the Noti, Eggel and Wyss-Coray laboratories for discussions and valuable input; A.-L. Huguenin, U. Lüthi and C. Krüger for technical support; J. J. Lee and H.-U. Simon for providing IL-5 transgenic mice; M. Fux, A. Odermatt and the DBMR FACSlab for technical support with cell sorting; the staff and animal caretakers of the Central Animal Facility in Bern for their advice and support; K. Rufibach for valuable discussions; and H. Maeker and the Stanford Human Immune Monitoring Center for their help with qPCR multiplex array. J.A. is supported by grants from École Polytechnique Fédérale de Lausanne, the Swiss National Science Foundation (no. 31003A-140780), the AgingX programme of the Swiss Initiative for Systems Biology (no. 51RTP0-151019) and the NIH (no. R01AG043930). This work was funded by the National Institute on Aging (no. R01AG053382 to S.A.V. and nos. AG045034 and DP1AG053015 to T.W.-C.), the Department of Veterans Affairs (to T.W.-C.), the Glenn Center for the Biology of Aging (to T.W.-C.), a Novartis grant for Medical-Biological Research (no. 15B100 to M.N.), a FreeNovation Novartis grant (to M.N) and by grants from the Fondation Acteria (to A.E. and M.N.) and Velux Stiftung (no. 1095 to A.E.).

Author information

Author notes

  1. Kira I. Mosher

    Present address: Department of Chemical and Biological Engineering, University of California, Berkeley, CA, USA

  2. Alicia Shiu

    Present address: Amplitude Analytics Inc., San Francisco, CA, USA

  3. Zhaoqing Ding

    Present address: Johnson & Johnson Pharmaceutical Research & Development, L.L.C., San Diego, CA, USA

  4. Federico Storni

    Present address: Department for Visceral Surgery and Medicine, Bern University Hospital, University of Bern, Bern, Switzerland

  5. Markus Britschgi

    Present address: Roche Pharma Research and Early Development, Neuroscience Discovery, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland

  6. Mario Noti

    Present address: Department of Gastrointestinal Health, Immunology, Nestlé Research, Lausanne, Switzerland

  7. These authors contributed equally: Mario Noti, Alexander Eggel.

Authors and Affiliations

  1. Department of Rheumatology, Immunology and Allergology, Bern University Hospital, University of Bern, Bern, Switzerland

    Daniel Brigger, Robin van Brummelen, Noemi Zbären, Pascal Gasser, Pascal Guntern, Federico Storni, Peter M. Villiger & Alexander Eggel

  2. Department for BioMedical Research, University of Bern, Bern, Switzerland

    Daniel Brigger, Robin van Brummelen, Noemi Zbären, Pascal Gasser, Pascal Guntern, Federico Storni, Mark Siegrist, Willy Hofstetter, Peter M. Villiger & Alexander Eggel

  3. Tumor Immunology, Department for BioMedical Reserach, University of Bern, Bern, Switzerland

    Carsten Riether & Magdalena Hinterbrandner

  4. Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

    Carsten Riether & Magdalena Hinterbrandner

  5. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA

    Kira I. Mosher, Alicia Shiu, Zhaoqing Ding, Hanadie Yousef, Markus Britschgi & Tony Wyss-Coray

  6. Nash Family Department of Neuroscience, Department of Neurology, Friedman Brain Institute, Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Joseph M. Castellano

  7. Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA

    Neill Graff-Radford

  8. Institute for Infectious Diseases, University of Bern, Bern, Switzerland

    Denis Grandgirard & Stephen L. Leib

  9. Laboratory of Integrative and Systems Physiology, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Norman Moullan & Johan Auwerx

  10. Department of Anatomy, University of California San Francisco, San Francisco, CA, USA

    Saul A. Villeda

  11. Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA

    Tony Wyss-Coray

  12. Institute of Pathology, Division of Experimental Pathology, University of Bern, Bern, Switzerland

    Mario Noti

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Contributions

M.N. and A.E. designed the project. D.B., C.R., R.v.B., K.I.M., A.S., Z.D., N.Z., P. Gasser, P. Guntern, H.Y., J.M.C., M.B., M.H., D.G., M.S., N.M., S.A.V., M.N. and A.E. performed the experiments. F.S. and N.G.-R. provided human samples. W.H., S.L.L., P.M.V., J.A., S.A.V. and T.W.-C. provided important advice. D.B., M.N. and A.E. analysed the data and wrote the manuscript.

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Correspondence to Mario Noti or Alexander Eggel.

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Extended data

Extended Data Fig. 1 Tissue screens for CCL11 and CCL2 protein expression in young and aged mice.

a, Comparison of CCL11 and CCL2 protein expression in muscle, spleen, brain, kidney, thymus, liver, lung, skin, mesenteric lymph nodes (MLN), colon, subcutaneous WAT (scWAT) and epidydimal WAT (eWAT) of young (Y, 2-3 months) and aged mice (A, 18-20 months) as assessed by western blot. Tissues of three biologically independent animals were pooled. HSP90 served as loading control. Quantification of b, CCL11 and c, CCL2 protein levels normalized to HSP90 in indicated tissues of young (Y, 2-3 months) and aged mice (A, 18-20 months) by ImageJ. One out of two independently performed experiments is shown. d, Comparison of CCL11 and CCL2 mRNA expression levels in indicated tissues of aged mice (18-20 months) as assessed by qPCR (n=4). e, CCL2 and CCL11 protein levels were assessed by western blot (n=4). One out of 3 independently performed experiments is shown. f, Quantification of CCL11 and CCL2 protein levels normalized to HSP90 in indicated tissues of young (Y, 2-3 months, n=4) and aged mice (A, 18-20 months, n=4). HSP90 served as loading control. Protein levels from total eWAT was calculated. Statistical significance was calculated by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against eWAT (d) or by unpaired two-tailed Student’s t test between young and aged samples (f). Data are shown as individual data points with mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001. ns, not significant. Uncropped western blots are provided in the Source Data File.

Source data

Extended Data Fig. 2 Gating strategies for human and mouse ATEs and age-related adipose tissue hypertrophy.

a, Gating strategy for human omental adipose tissue eosinophils. b, Representative images of H&E stained human omental adipose tissue from young and aged donors of indicated age. Scale bar: 100 μm. c, Quantification of adipocyte size in H&E stained sections from human omental adipose tissue (n=17 biologically independent human donors) by ImageJ. d, Representative gating strategy for ATE (F4/80int, SiglecF+) and ATM (F4/80+, SiglecF-) in mouse visceral adipose tissue of young (3 months) and aged mice (20 months). e, Absolute eosinophil and macrophage numbers per gram eWAT of young (3 months, n=10) and aged mice (20 months, n=10). This experiment was done once. f, Representative photographs of H&E stained histological eWAT sections of indicated treatment groups. g, Quantification of adipocyte hypertrophy in young (n=20), Aged-PBS (n=19), Aged-yEOS (n=22) and Aged-yEOSIL-4-/- (n=20) biologically independent mice by ImageJ. Statistical significance was calculated by unpaired two-tailed Student’s t test (e), the Pearson correlation coefficient between adipocyte size and age (c) or by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the aged-PBS treated group (g). Data are shown as individual data points with mean bars ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001. ns, not significant.

Extended Data Fig. 3 Recruitment of sort-purified GFP+ eosinophils to WAT of aged mice.

Aged mice (18 months) were adoptively transferred with sort-purified GFP+ eosinophils derived from IL-5 transgenic mice on two subsequent days. The following day eosinophil recruitment into different tissues was assessed by flow cytometry. a, Representative flow plots of transferred GFP+ and endogenous GFP– tissue eosinophils in indicated tissues. b, Frequencies of transferred GFP+ and endogenous GFP– tissue eosinophils in indicated tissues. c, Siglec-F surface expression on adipose tissue eosinophils from Young, Aged-PBS and Aged-yEOS -treated mice as assessed by flow cytometry. d, Representative histograms of Siclec-F expression on ATEs of indicated groups. e, Quantification of Siglec-F surface expression (MFI) on adipose tissue eosinophils of Young (n=5), Aged-PBS (n=5) and Aged-yEOS (n=4) mice. The experiment was done once. Statistical significance was calculated by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the young group. ns, not significant. Data are representative of n=4 per group and are shown as mean ± SEM.

Extended Data Fig. 4 Transfer of neutrophils to aged mice does not alter WAT inflammation, hematopoetic stem cell pol or physical performance.

a, Experimental protocol. b, Frequencies of eosinophils, macrophages and calculated eosinophil:macrophage ratios in eWAT of Aged-PBS (n=8) and Aged-yNEU (n=9) mice. c, mRNA expression levels for Tnfα, Il1β and IL6 in eWAT of Aged-PBS (n=8) and Aged-yNEU mice (n=9). Data are presented as fold induction over Aged-PBS controls. d, Average time on Rotarod of Aged-PBS controls (n=8) and Aged-yNEU mice (n=9). e, Total numbers of lin–, Sca-1+, c-kit+ hematopoietic stem cells (LSKs) in Aged-PBS (n=4) and Aged-yNEU (n=4) mice. f, Numbers of common myeloid progenitors (CMP), common lymphoid progenitors (CLP), and granulocyte/monocyte progenitors (GMP) in the bone marrow of Aged-PBS (n=4) and Aged-yNEU (n=4) mice. g, Frequencies of neutrophils in eWAT of young (n=5), Aged-PBS (n=4) and Aged-yNeu (n=5) mice. h, Experimental protocol of bone marrow derived eosinophil (BMDE) transfers. i, Calculated ATE:ATM ratios in eWAT of Aged-PBS (n=5) and Aged-BMDE (n=4) mice as measured by flow cytometry. j, IL-6 protein levels in eWAT of Aged-PBS (n=6) and Aged-BMDE (n=5) mice. k, Pre- and post-treatment IL-6 plasma protein levels in Aged-PBS (n=6) and Aged-BMDE (n=5). l, Intra-group and m, inter-group comparison of pre- and post-treatment average time on wheel (Rotarod test) in Aged-PBS (n=6) and Aged-BMDE (n=5) mice. Delta in performances in (l) is calculated relative to baseline (post- minus pre-treatment results). Statistical significance was calculated by Wilcoxon matched pairs signed rank test (k, l), by unpaired two-tailed Student’s t test (b, c, d, e, f, I, j, m) or by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the aged-PBS treated group (g). Data are pooled from two independently performed experiments (except for (g-m) only one experiment has been performed) and shown as individual data points with mean ± SEM. Data are shown as mean ± SEM. *p < 0.05, **p < 0.01. ns, not significant.

Extended Data Fig. 5 Eosinophil transfers do not alter age-related changes in murine subcutaneous WAT.

a, Gating strategy for ATMs and ATEs in scWAT of young (3 months) and aged (20 months) mice. b, Calculated ATE:ATM ratio in scWAT of young (n=10), Aged-PBS (n=10), Aged-yEOS (n=6) and Aged-yEOSIL-4-/- (n=7) mice. c, Representative photographs of H&E stained histological scWAT sections of indicated treatment groups. d, Quantification of adipocyte hypertrophy in Young (n=11), Aged-PBS (n=10), Aged-yEOS (n=9) and Aged-yEOSIL-4-/- (n=12) mice by ImageJ. e, IL-6 and CCL2 protein levels in scWAT of Young (n=15), Aged-PBS (n=14), Aged-yEOS (n=12) and Aged-yEOSIL-4-/- (n=13) mice. Statistical significance was calculated by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the aged-PBS treated group. Data (e) are pooled from 2 independently performed experiments or performed once (a-d) and shown as individual data points with mean bars ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001. ns, not significant.

Extended Data Fig. 6 Glucose metabolism in response to eosinophil transfers to aged mice.

a, Blood glucose levels in Aged-PBS (20 months, n=4) and Aged-yEOS (n=5) mice in response to i.p. glucose challenge over time. b, Calculated HOMA-IR for Aged-PBS (20 months, n=4) and Aged-yEOS (20 months, n=5) mice. Statistical significance was tested by unpaired two-tailed Student’s t-test. One out of 3 independently performed experiments is shown. Data are shown as individual data points with mean bars ± SEM. ns, not significant.

Extended Data Fig. 7 Open field activity tests.

a, Mean velocity, total distance, accumulative mobility- and immobility of Aged-PBS, Aged-yEOS and Aged-yNEU mice (n=4 per group). b, Representative heat maps for Aged-PBS, Aged-yEOS and Aged-yNEU mice demonstrating the animal’s position in the arena. The experiment was done once. Statistical significance was calculated by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the aged-PBS treated group. Data are shown as mean bars ± SEM. ns, not significant.

Extended Data Fig. 8 Transfer of young eosinophils is associated with alterations in muscle stem cell frequencies but not function.

a, Gating strategy and representative flow plots of CD31–, CD45–, Sca-1–, Vcam+ and integrin α7+ satellite cells in muscle of Young (n=13), Aged-PBS (n=17), Aged-yEOS, (n=17) and Aged-yEOSIL-4-/- (n=17) mice. b, Quantification of muscle stem cell frequencies in indicated groups. c, Representative photographs of immunofluorescent stained sort-purified and differentiated satellite cells. d, Quantification of cell colony formation of sort-purified muscle stem cells of Young (n=10), Aged-PBS (n=10), Aged-yEOS (n=8) and Aged-yEOSIL-4-/- (n=8) mice e, Representative H&E stained longitudinal and cross-sectional quadriceps femoris in indicated groups. f, Quantification of centrally nucleated myofibers in sections of Young (n=26), Aged-PBS (n=26), Aged-yEOS (n=18) and Aged-yEOSIL-4-/- (n=13) mice. g, Muscle weight (femur) was measured in Young (n=5), Aged-PBS (n=9), Aged-yEOS (n=8) and Aged-yEOSIL-4-/- (n=7) mice. Data (a-f) are pooled from 2 independently performed experiments except for g (one experiment has been performed). Statistical significance was calculated by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the aged-PBS treated group. Data are shown as individual data points with mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001. ns, not significant.

Extended Data Fig. 9 Eosinophil transfers reverse myeloid skewing in old age.

a, Gating strategy for the identification of LSK, HSC-SLAM, HSC-AD, CMP, CLP and GMP populations. b, Absolute numbers of CMP, CLP and GMP per mouse in Young (n=5), Aged-PBS (n=7) and Aged-yEOS (n=8) groups. c, Absolute numbers of CMP, CLP and GMP per mouse in Aged-PBS (n=8) and Aged-yEOSIL-4-/- (n=10) groups. One out of two independently performed experiments is shown. Statistical significance in (b) was calculated one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the aged-PBS treated group and (c) by two-tailed Student’s t-test. d, Gating strategy for the identification of germinal GCB. Data are shown as individual data points with mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001.

Extended Data Fig. 10 Eosinophils adopt a senescent-like inflammatory phenotype with age.

a, Heat map representing Ct values of p21, Vegfa, Il1b, Il6 and Tnfa in sort-purified, blood-derived eosinophils from aged WT (20 months), young WT (3 months) or young IL5 transgenic mice (3 months) as assessed by targeted fluidigm qPCR array. b, Relative expression levels of Tnfa, Il1b, Il6, p21 and Vegfa in sort-purified, blood-derived eosinophils from aged WT (20 months), young WT (3 months) or young IL5 transgenic mice (3 months) as assessed by fluidigm qPCR array. Eosinophils from 3 animals were pooled for each measurement (n=3 per group). The experiment was done once. c, Relative expression levels of TNFa, IL1b, IL6, p21 and VEGFA in human blood derived eosinophils from young (average age=34, n=8) and aged (average age=64, n=7) donors. Data in (b and c) are shown as individual data points with mean ± SEM and statistical significance was calculated by one-way ANOVA followed by two-tailed post-hoc Dunnett’s multiple comparison test against the young group (b) and two-tailed students t-test (c). *p < 0.05, **p < 0.01, ***p < 0.001. ns, not significant. ND, not detectable.

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Brigger, D., Riether, C., van Brummelen, R. et al. Eosinophils regulate adipose tissue inflammation and sustain physical and immunological fitness in old age. Nat Metab 2, 688–702 (2020). https://doi.org/10.1038/s42255-020-0228-3

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