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jem Home » 2018 Archive » 5 February » 215 (2): 423
Article

Cardiac macrophages promote diastolic dysfunction

View ORCID ProfileMaarten Hulsmans, Hendrik B. Sager, Jason D. Roh, View ORCID ProfileMaría Valero-Muñoz, Nicholas E. Houstis, Yoshiko Iwamoto, Yuan Sun, Richard M. Wilson, View ORCID ProfileGregory Wojtkiewicz, Benoit Tricot, Michael T. Osborne, Judy Hung, View ORCID ProfileClaudio Vinegoni, Kamila Naxerova, David E. Sosnovik, Michael R. Zile, Amy D. Bradshaw, Ronglih Liao, Ahmed Tawakol, Ralph Weissleder, Anthony Rosenzweig, View ORCID ProfileFilip K. Swirski, Flora Sam, View ORCID ProfileMatthias Nahrendorf  Correspondence email
Maarten Hulsmans
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Hendrik B. Sager
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Jason D. Roh
Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MADivision of Cardiology and Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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María Valero-Muñoz
Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA
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  • ORCID record for María Valero-Muñoz
Nicholas E. Houstis
Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MADivision of Cardiology and Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Yoshiko Iwamoto
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Yuan Sun
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Richard M. Wilson
Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA
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Gregory Wojtkiewicz
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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  • ORCID record for Gregory Wojtkiewicz
Benoit Tricot
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Michael T. Osborne
Division of Cardiology and Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, Boston, MACardiac MR PET CT Program, Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Judy Hung
Division of Cardiology and Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Claudio Vinegoni
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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  • ORCID record for Claudio Vinegoni
Kamila Naxerova
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MADivision of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
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David E. Sosnovik
Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MADivision of Cardiology and Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, Boston, MACardiac MR PET CT Program, Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MAAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Michael R. Zile
Gazes Cardiac Research Institute, Medical University of South Carolina, Charleston, SC
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Amy D. Bradshaw
Gazes Cardiac Research Institute, Medical University of South Carolina, Charleston, SC
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Ronglih Liao
Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
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Ahmed Tawakol
Division of Cardiology and Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, Boston, MACardiac MR PET CT Program, Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Ralph Weissleder
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MADepartment of Systems Biology, Harvard Medical School, Boston, MA
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Anthony Rosenzweig
Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MADivision of Cardiology and Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Filip K. Swirski
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Flora Sam
Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA
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Matthias Nahrendorf
Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MACardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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  • ORCID record for Matthias Nahrendorf
  • For correspondence: mnahrendorf@mgh.harvard.edu
DOI: 10.1084/jem.20171274 | Published January 16, 2018
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    Figure 1.

    Cardiac macrophage expansion in diastolic dysfunction. (A) Experimental outline. Left: Mice were exposed to SAUNA; right: 18- and 30-mo-old C57BL/6 mice were used to study macrophages in aging. (B) Flow cytometric quantification of myeloid cell populations in hearts from control, SAUNA-exposed, and aged mice. Top: Representative flow cytometry plots; bottom: number of cell populations per milligram of heart tissue. Data are pooled from two (aging) to seven (SAUNA) independent experiments (n = 8–47 mice per group). Lin, lineage; mo, months; Mono/Macs, monocytes/macrophages. (C) Immunohistochemical analysis of macrophages in hearts from control, SAUNA-exposed, and aged mice. Left: Representative images; right: bar graph shows percentage of positive staining per ROI. Data are pooled from two independent experiments (n = 7–12 mice per group). Bar, 25 µm. Results are shown as mean ± SD. For statistical analysis, one-way ANOVA followed by Tukey’s test was performed for multiple comparisons. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

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    Figure 2.

    Ccr2-dependent monocyte recruitment contributes to cardiac macrophage expansion associated with diastolic dysfunction. (A) Flow cytometric quantification of monocytes and neutrophils in blood from control, SAUNA-exposed, and aged mice. Left: Representative flow cytometry plots; right: number of leukocytes and myeloid cells per milliliter of blood. Data are pooled from 2 (aging) to 11 (SAUNA) independent experiments (n = 8–89 mice per group). (B) Relative expression levels of different chemokines and adhesion molecules by qPCR in hearts from control, SAUNA-exposed, and aged mice. Data are pooled from two (aging) to four (SAUNA) independent experiments (n = 10–33 mice per group). (C) Flow cytometric quantification of myeloid cell populations in hearts from control and C57BL/6 and Ccr2−/− SAUNA-exposed mice. Left: Representative flow cytometry plots; right: number of cell populations per milligram of heart tissue. Data are pooled from three independent experiments (n = 14–15 mice per group). (D) Immunohistochemical analysis of macrophages in hearts from control and C57BL/6 and Ccr2−/− SAUNA-exposed mice. Left: Representative images; right: bar graph shows percentage of positive staining per ROI. Data are pooled from two independent experiments (n = 5–12 mice per group). Bar, 25 µm. (E) Relative Anp and Bnp expression levels by qPCR in hearts from control and C57BL/6 and Ccr2−/− SAUNA-exposed mice. Data are pooled from two independent experiments (n = 8–12 mice per group). (F) Lung wet-to-dry weight ratio in control and C57BL/6 and Ccr2−/− SAUNA-exposed mice. Data are pooled from two independent experiments (n = 4 mice per group). Results are shown as mean ± SD. For statistical analysis, one-way ANOVA followed by Tukey’s test was performed for multiple comparisons. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

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    Figure 3.

    SAUNA increases bone marrow hematopoiesis. (A) Flow cytometric quantification of HSPCs in bone marrow from control and SAUNA-exposed mice. Left: Representative flow cytometry plots; right: number of HSPCs per femur. Data are pooled from at least two independent experiments (n = 10–36 mice per group). (B) BrdU pulse-chase experiment. Mice were exposed to BrdU in drinking water for 2 wk, which led to >70% BrdU labeling of HSCs (day 1). Additional cohorts of mice were exposed to SAUNA for 30 d or remained unexposed after BrdU labeling. The lower panel shows representative dot plots, and the bar graph shows quantification of BrdU retention in HSCs (day 30). Data are pooled from two independent experiments (n = 10 mice per group). (C) Number of leukocytes and myeloid cells per femur from control and SAUNA-exposed mice. Data are pooled from five independent experiments (n = 27–42 mice per group). (D) Retention factor expression by qPCR in bone marrow from control and SAUNA-exposed mice. Data are pooled from two independent experiments (n = 9–14 mice per group). (E) Blood CFU assay in control and SAUNA-exposed mice. Data are pooled from two independent experiments (n = 10–16 mice per group). Results are shown as mean ± SD. For statistical analysis, a two-tailed unpaired t test was performed to compare two groups. *, P < 0.05; ****, P < 0.0001.

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    Figure 4.

    Aging expands bone marrow HSCs. Flow cytometric quantification of HSPCs in bone marrow from control and aged mice. Left: Representative flow cytometry plots; right: number of HSPCs per femur. Data are pooled from two independent experiments (n = 8–10 mice per group). Results are shown as mean ± SD. For statistical analysis, one-way ANOVA followed by Tukey’s test was performed for multiple comparisons. *, P < 0.05; ***, P < 0.001.

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    Figure 5.

    SAUNA induces splenic myelopoiesis. (A) Flow cytometric quantification of HSPCs in spleens from control and SAUNA-exposed mice. Left: Representative flow cytometry plots; right: number of HSPCs per spleen. Data are pooled from five independent experiments (n = 25–39 mice per group). (B) Number of splenic myeloid cells and lymphocytes in control and SAUNA-exposed mice. Data are pooled from five independent experiments (n = 27–42 mice per group). (C) Spleen weight in control and SAUNA-exposed mice. Data are pooled from 15 independent experiments (n = 102–103 mice per group). Results are shown as mean ± SD. For statistical analysis, a two-tailed unpaired t test was performed to compare two groups. *, P < 0.05; **, P < 0.01; ****, P < 0.0001.

  • Figure 6.
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    Figure 6.

    Aging expands splenic HSCs. (A) Flow cytometric quantification of HSPCs in spleens from control and aged mice. Left: Representative flow cytometry plots; right: number of HSPCs per spleen. Data are pooled from two independent experiments (n = 8–10 mice per group). (B) Number of splenic myeloid cells and lymphocytes in control and aged mice. Data are pooled from two independent experiments (n = 8–10 mice per group). (C) Spleen weight in control and aged mice. Data are pooled from two independent experiments (n = 8–10 mice per group). Results are shown as mean ± SD. For statistical analysis, one-way ANOVA followed by Tukey’s test was performed for multiple comparisons. *, P < 0.05; **, P < 0.01.

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    Figure 7.

    Identification and validation of Il10 produced by cardiac macrophages as gene of interest. (A) Workflow and FACS gating strategy to purify macrophages from heart tissue. (B) Heat map of expression values (2-ΔCt) of fibrosis-related genes by qPCR in FACS-purified cardiac macrophages from control and SAUNA-exposed mice (n = 4 mice per group). (C) Relative Il10 expression levels by qPCR in macrophages FACS-sorted from a second, independent cohort of control and SAUNA-exposed mice (n = 8–9 mice per group). (D) Left: Il10 expression by qPCR in left ventricle and FACS-purified cardiac macrophages, fibroblasts, and endothelial cells from C57BL/6 mice (n = 6–9 mice per group); right: FACS gating strategy to purify macrophages, fibroblasts, and endothelial cells from heart tissue. (E) Relative Il10 expression levels by qPCR in hearts from control and aged mice. Data are pooled from two independent experiments (n = 7–9 mice per group). (F) Relative Il10 expression levels by qPCR in hearts and kidneys from control and SAUNA-exposed mice. Data are pooled from two independent experiments (n = 7–15 mice per group). (G) PCR analysis of FACS-purified Cx3cr1wt/wt and Cx3cr1wt/CreER cardiac macrophages 7 d after tamoxifen treatment for the presence of wild-type (Il10wt) and conditional undeleted (Il10fl) or deleted (Il10Δ) Il10 alleles. Results are shown as mean ± SD. For statistical analysis, a two-tailed unpaired t test was performed to compare two groups, and one-way ANOVA followed by Tukey’s test was performed for multiple comparisons. *, P < 0.05; **, P < 0.01.

  • Figure 8.
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    Figure 8.

    Macrophage-restricted IL-10 deletion in SAUNA-exposed mice improves diastolic function. (A) Experimental outline of the SAUNA protocol applied on mice lacking IL-10. (B) Flow cytometric quantification of neutrophils and macrophages in hearts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Left: Representative flow cytometry plots; right: number of neutrophils and macrophages per milligram of heart tissue. The pie charts indicate the percentage of MHCIIlow (orange) and MHCIIhigh (purple) cardiac macrophages. Data are pooled from two independent experiments (n = 14–16 mice per group). (C) Immunohistochemical analysis of macrophages in hearts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Left: Representative images; right: bar graph shows percentage of positive staining per ROI. Data are pooled from two independent experiments (n = 6–7 mice per group). Bar, 25 µm. (D) Hemodynamic parameters by pressure–volume catherization of hearts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Data are pooled from two independent experiments (n = 7–11 mice per group). (E) Serum creatinine levels in littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Data are pooled from two independent experiments (n = 6 mice per group). (F) Systolic blood pressure in littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Data are pooled from six independent experiments (n = 38–46 mice per group). (G) Relative Anp and Bnp expression levels by qPCR in hearts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Data are pooled from four independent experiments (n = 27 mice per group). (H) Lung wet-to-dry weight ratio in littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Data are pooled from five independent experiments (n = 32–39 mice per group). Results are shown as mean ± SD. For statistical analysis, a two-tailed unpaired t test was performed to compare two groups. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

  • Figure 9.
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    Figure 9.

    IL-10 produced by cardiac macrophages indirectly activates fibroblasts. (A) Mean fluorescence intensities (MFI) indicating ROS production in cardiac fibroblasts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Data are pooled from two independent experiments (n = 11 mice per group). (B) Flow cytometric quantification of fibroblasts in hearts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Left: Representative flow cytometry plots; right: number of fibroblasts per milligram of heart tissue. Data are pooled from two independent experiments (n = 11–15 mice per group). RMCs, resident mesenchymal cells. (C) Relative Opn expression levels by qPCR in control and rIL-10–exposed FACS-purified cardiac macrophages. Data are pooled from two independent experiments (n = 10 per group). (D) Relative Col1a2 and Fn1 expression levels by qPCR in FACS-purified cardiac fibroblasts incubated with rIL-10, control macrophage (mac) medium or rIL-10–exposed mac medium with and without OPN or TGFβ neutralizing antibody (Ab). Data are pooled from two independent experiments (n = 4–7 per group). (E) Left: Representative immunofluorescence images of FACS-purified cardiac fibroblasts incubated with control or rIL-10–exposed mac medium, and stained with α-SMA (green), Phalloidin to identify actin filaments (red), and DAPI (blue); right: bar graphs show percentage of positive α-SMA or actin staining per ROI. Data are pooled from two independent experiments (n = 7 per group). Bar, 50 µm. (F) Relative Opn and Tgfb1 expression levels by qPCR in hearts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Data are pooled from at least two independent experiments (n = 8–15 mice per group). (G) Histological analysis of collagen deposition (PicroSirius Red) in hearts from littermate and Cx3cr1 Il10−/− SAUNA-exposed mice. Left: Representative images; right: bar graph shows percentage of positive staining per ROI. Data are pooled from two independent experiments (n = 6 mice per group). Bar, 50 µm. Results are shown as mean ± SD. For statistical analysis, a two-tailed unpaired t test was performed to compare two groups, and one-way ANOVA followed by Tukey’s test was performed for multiple comparisons. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

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    Figure 10.

    Summary cartoon. Systemic inflammation and impaired LV diastolic function are seen in both hypertension and physiological aging. Circulating monocytes and myocardial macrophage density are increased in diastolic dysfunction, and the macrophage expansion is partially driven by monocyte recruitment. Blood monocytosis derives from increased production in the bone marrow and spleen. Mechanistically, cardiac macrophages produce more IL-10 leading to their autocrine activation toward a fibrogenic phenotype. A profibrotic macrophage subset secretes more OPN and fewer proteases and MMPs, contributing to fibroblast activation, collagen deposition, and subsequently increased myocardial stiffness and diastolic dysfunction.

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Cardiac macrophages promote diastolic dysfunction
Maarten Hulsmans, Hendrik B. Sager, Jason D. Roh, María Valero-Muñoz, Nicholas E. Houstis, Yoshiko Iwamoto, Yuan Sun, Richard M. Wilson, Gregory Wojtkiewicz, Benoit Tricot, Michael T. Osborne, Judy Hung, Claudio Vinegoni, Kamila Naxerova, David E. Sosnovik, Michael R. Zile, Amy D. Bradshaw, Ronglih Liao, Ahmed Tawakol, Ralph Weissleder, Anthony Rosenzweig, Filip K. Swirski, Flora Sam, Matthias Nahrendorf
Journal of Experimental Medicine Feb 2018, 215 (2) 423-440; DOI: 10.1084/jem.20171274

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The Journal of Experimental Medicine: 216 (2)

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February 4, 2019
Volume 216, No. 2

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