Abstract
After myocardial infarction (MI), emergency hematopoiesis produces inflammatory myeloid cells that accelerate atherosclerosis and promote heart failure. Because the balance between glycolysis and mitochondrial metabolism regulates hematopoietic stem cell homeostasis, metabolic cues may influence emergency myelopoiesis. Here we show, in humans and female mice, that hematopoietic progenitor cells increase fatty acid metabolism after MI. Blockade of fatty acid oxidation by deleting carnitine palmitoyltransferase (Cpt1a) in hematopoietic cells of Vav1Cre/+Cpt1afl/fl mice limited hematopoietic progenitor proliferation and myeloid cell expansion after MI. We also observed reduced bone marrow adiposity in humans, pigs and mice after MI. Inhibiting lipolysis in adipocytes using AdipoqCreERT2Atglfl/fl mice or local depletion of bone marrow adipocytes in AdipoqCreERT2iDTR mice also curbed emergency hematopoiesis. Furthermore, systemic and regional sympathectomy prevented bone marrow adipocyte shrinkage after MI. These data establish a critical role for fatty acid metabolism in post-MI emergency hematopoiesis.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Galkina, E. & Ley, K. Immune and inflammatory mechanisms of atherosclerosis (*). Annu. Rev. Immunol. 27, 165–197 (2009).
Moore, K. J. & Tabas, I. Macrophages in the pathogenesis of atherosclerosis. Cell 145, 341–355 (2011).
Patel, A. A. et al. The fate and lifespan of human monocyte subsets in steady state and systemic inflammation. J. Exp. Med. 214, 1913–1923 (2017).
Dutta, P. et al. Myocardial infarction activates CCR2+ hematopoietic stem and progenitor cells. Cell Stem Cell 16, 477–487 (2015).
Dutta, P. et al. Myocardial infarction accelerates atherosclerosis. Nature 487, 325–329 (2012).
Nahrendorf, M. et al. The healing myocardium sequentially mobilizes two monocyte subsets with divergent and complementary functions. J. Exp. Med. 204, 3037–3047 (2007).
Sager, H. B. et al. Proliferation and recruitment contribute to myocardial macrophage expansion in chronic heart failure. Circ. Res. 119, 853–864 (2016).
Swirski, F. K. & Nahrendorf, M. Cardioimmunology: the immune system in cardiac homeostasis and disease. Nat. Rev. Immunol. 18, 733–744 (2018).
Emami, H. et al. Splenic metabolic activity predicts risk of future cardiovascular events: demonstration of a cardiosplenic axis in humans. JACC Cardiovasc. Imaging 8, 121–130 (2015).
Engstrom, G., Melander, O. & Hedblad, B. Leukocyte count and incidence of hospitalizations due to heart failure. Circ. Heart Fail. 2, 217–222 (2009).
Ernst, E., Hammerschmidt, D. E., Bagge, U., Matrai, A. & Dormandy, J. A. Leukocytes and the risk of ischemic diseases. JAMA 257, 2318–2324 (1987).
Madjid, M., Awan, I., Willerson, J. T. & Casscells, S. W. Leukocyte count and coronary heart disease: implications for risk assessment. J. Am. Coll. Cardiol. 44, 1945–1956 (2004).
Maekawa, Y. et al. Prognostic significance of peripheral monocytosis after reperfused acute myocardial infarction:a possible role for left ventricular remodeling. J. Am. Coll. Cardiol. 39, 241–246 (2002).
Ito, K. et al. A PML–PPAR-δ pathway for fatty acid oxidation regulates hematopoietic stem cell maintenance. Nat. Med. 18, 1350–1358 (2012).
Takubo, K. et al. Regulation of glycolysis by Pdk functions as a metabolic checkpoint for cell cycle quiescence in hematopoietic stem cells. Cell Stem Cell 12, 49–61 (2013).
Yu, W. M. et al. Metabolic regulation by the mitochondrial phosphatase PTPMT1 is required for hematopoietic stem cell differentiation. Cell Stem Cell 12, 62–74 (2013).
Crane, G. M., Jeffery, E. & Morrison, S. J. Adult haematopoietic stem cell niches. Nat. Rev. Immunol. 17, 573–590 (2017).
Pinho, S. & Frenette, P. S. Haematopoietic stem cell activity and interactions with the niche. Nat. Rev. Mol. Cell Biol. 20, 303–320 (2019).
Itkin, T. et al. Distinct bone marrow blood vessels differentially regulate haematopoiesis. Nature 532, 323–328 (2016).
Naveiras, O. et al. Bone-marrow adipocytes as negative regulators of the haematopoietic microenvironment. Nature 460, 259–263 (2009).
Li, Z. et al. Lipolysis of bone marrow adipocytes is required to fuel bone and the marrow niche during energy deficits. eLife 11, e78496 (2022).
Zhang, Z. et al. Bone marrow adipose tissue-derived stem cell factor mediates metabolic regulation of hematopoiesis. Haematologica 104, 1731–1743 (2019).
Zhou, B. O. et al. Bone marrow adipocytes promote the regeneration of stem cells and haematopoiesis by secreting SCF. Nat. Cell Biol. 19, 891–903 (2017).
Virani, S. S. et al. Heart disease and stroke statistics—2020 update: a report from the American Heart Association. Circulation 141, e139–e596 (2020).
Ito, K. & Suda, T. Metabolic requirements for the maintenance of self-renewing stem cells. Nat. Rev. Mol. Cell Biol. 15, 243–256 (2014).
Kohli, L. & Passegué, E. Surviving change: the metabolic journey of hematopoietic stem cells. Trends Cell Biol. 24, 479–487 (2014).
Heyde, A. et al. Increased stem cell proliferation in atherosclerosis accelerates clonal hematopoiesis. Cell 184, 1348–1361 (2021).
Pang, W. W. et al. Hematopoietic stem cell and progenitor cell mechanisms in myelodysplastic syndromes. Proc. Natl Acad. Sci. USA 110, 3011–3016 (2013).
Rohde, D. et al. Bone marrow endothelial dysfunction promotes myeloid cell expansion in cardiovascular disease. Nat. Cardiovasc. Res. 1, 28–44 (2022).
Ansó, E. et al. The mitochondrial respiratory chain is essential for haematopoietic stem cell function. Nat. Cell Biol. 19, 614–625 (2017).
Dempster, J. M. et al. Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects. Genome Biol. 22, 343 (2021).
Scheller, E. L. et al. Region-specific variation in the properties of skeletal adipocytes reveals regulated and constitutive marrow adipose tissues. Nat. Commun. 6, 7808 (2015).
Shen, W. et al. MRI-measured bone marrow adipose tissue is inversely related to DXA-measured bone mineral in Caucasian women. Osteoporos. Int. 18, 641–647 (2007).
Li, Y., Meng, Y. & Yu, X. The unique metabolic characteristics of bone marrow adipose tissue. Front. Endocrinol. (Lausanne) 10, 69 (2019).
Bani Hassan, E. et al. Bone marrow adipose tissue quantification by imaging. Curr. Osteoporos. Rep. 17, 416–428 (2019).
Schoiswohl, G. et al. Impact of reduced ATGL-mediated adipocyte lipolysis on obesity-associated insulin resistance and inflammation in male mice. Endocrinology 156, 3610–3624 (2015).
Zeng, W. et al. Sympathetic neuro-adipose connections mediate leptin-driven lipolysis. Cell 163, 84–94 (2015).
Takubo, K. et al. Regulation of the HIF-1α level is essential for hematopoietic stem cells. Cell Stem Cell 7, 391–402 (2010).
Simsek, T. et al. The distinct metabolic profile of hematopoietic stem cells reflects their location in a hypoxic niche. Cell Stem Cell 7, 380–390 (2010).
Fritsche, K. Fatty acids as modulators of the immune response. Annu. Rev. Nutr. 26, 45–73 (2006).
Tcheng, M. et al. Very long chain fatty acid metabolism is required in acute myeloid leukemia. Blood 137, 3518–3532 (2021).
Cai, L., Sutter, B. M., Li, B. & Tu, B. P. Acetyl-CoA induces cell growth and proliferation by promoting the acetylation of histones at growth genes. Mol. Cell 42, 426–437 (2011).
Mews, P. et al. Acetyl-CoA synthetase regulates histone acetylation and hippocampal memory. Nature 546, 381–386 (2017).
Mistry, J. J. et al. Free fatty-acid transport via CD36 drives β-oxidation-mediated hematopoietic stem cell response to infection. Nat. Commun. 12, 7130 (2021).
Zhang, S. et al. Immunometabolism of phagocytes and relationships to cardiac repair. Front. Cardiovasc. Med. 6, 42 (2019).
Ambrosi, T. H. et al. Adipocyte accumulation in the bone marrow during obesity and aging impairs stem cell-based hematopoietic and bone regeneration. Cell Stem Cell 20, 771–784 (2017).
Yin, W., Li, Z. & Zhang, W. Modulation of bone and marrow niche by cholesterol. Nutrients 11, 1394 (2019).
Nagareddy, P. R. et al. Hyperglycemia promotes myelopoiesis and impairs the resolution of atherosclerosis. Cell Metab. 17, 695–708 (2013).
Nagareddy, P. R. et al. Adipose tissue macrophages promote myelopoiesis and monocytosis in obesity. Cell Metab. 19, 821–835 (2014).
Shillingford, J. P. The red bone marrow in heart failure. J. Clin. Pathol. 3, 24–39 (1950).
Schoors, S. et al. Fatty acid carbon is essential for dNTP synthesis in endothelial cells. Nature 520, 192–197 (2015).
Heidt, T. et al. Chronic variable stress activates hematopoietic stem cells. Nat. Med. 20, 754–758 (2014).
Scheller, E. L. et al. Use of osmium tetroxide staining with microcomputerized tomography to visualize and quantify bone marrow adipose tissue in vivo. Methods Enzymol. 537, 123–139 (2014).
Galvez-Monton, C. et al. Comparison of two preclinical myocardial infarct models: coronary coil deployment versus surgical ligation. J. Transl. Med. 12, 137 (2014).
Lee, S. H., Erber, W. N., Porwit, A., Tomonaga, M. & Peterson, L. C. ICSH guidelines for the standardization of bone marrow specimens and reports. Int. J. Lab. Hematol. 30, 349–364 (2008).
Torlakovic, E. E. et al. ICSH guidelines for the standardization of bone marrow immunohistochemistry. Int. J. Lab. Hematol. 37, 431–449 (2015).
van der Laan, A. M. et al. Monocyte subset accumulation in the human heart following acute myocardial infarction and the role of the spleen as monocyte reservoir. Eur. Heart J. 35, 376–385 (2014).
Hirsch, A. et al. Intracoronary infusion of autologous mononuclear bone marrow cells or peripheral mononuclear blood cells after primary percutaneous coronary intervention: rationale and design of the HEBE trial—a prospective, multicenter, randomized trial. Am. Heart J. 152, 434–441 (2006).
Argüello, R. J. et al. SCENITH: a flow cytometry-based method to functionally profile energy metabolism with single-cell resolution. Cell Metab. 32, 1063–1075 (2020).
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).
Soneson, C., Love, M. I. & Robinson, M. D. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res. 4, 1521 (2015).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Mootha, V. K. et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).
Acknowledgements
This work was funded, in part, by the National Institutes of Health (NIH) (HL142494, HL139598, HL125428, NS108419 and T32HL076136), the Massachusetts General Hospital (MGH) Research Scholar Program, the Deutsche Forschungsgemeinschaft (RO5071/1-1 to D.R. and SCHL 2221/1-1 to M.J.S.), the Italian Ministry of Health ‘Ricerca Corrente’ (to D.C.) and Siemens Healthineers. J.G. was supported by the German Centre for Cardiovascular Research (DZHK) and the German Research Foundation (DFG, SFB 1470 subproject A4, GR 5261/1-1). The authors thank the MGH Mouse Imaging Program for assistance with imaging, the Center for Skeletal Research Core (NIH P30 AR066261) for histological processing and micro-CT imaging, the Harvard Stem Cell Institute–Center for Regenerative Medicine Flow Cytometry Core for assistance with flow sorting, the Harvard Center for Mass Spectrometry for metabolomics and K. Joyes (Center for Systems Biology) for editing the manuscript. We acknowledge BioRender (BE261P1NT4) for the cartoon component.
Author information
Authors and Affiliations
Contributions
S.Z., D.R., S.C., M.H., I.-H. L., J.G., L.H., Y.I., M.J.S., K.M., A.P., Y.Z., F.P., R.C., S.P., M.A.B., C.B., B.G., V.T., A.M.v.d.L., J.J.P., H.W.M.N. and D.C. designed, performed and analyzed experiments. I.-H.L. and K.N. analyzed and processed RNA sequencing data. S.Z., D.R., S.C., M.H., A.P., M.A.B., M.A.M., D.C., D.S., F.K.S., K.N. and M.N. discussed results and strategy. O.I.-E., C.G.-M. and A.B.-G. collected and provided human and swine bone marrow specimens. C.V. and S.A.T. performed and analyzed mass spectrometry experiments. S.Z., A.P., D.R. and M.N. wrote the manuscript, with input from all authors.
Corresponding author
Ethics declarations
Competing interests
M.N. has been a paid consultant or received research support from Takeda, Novartis, GlaxoSmithKline, Medtronic, Verseaux, Sigilon, Alnylam, IFM Therapeutics, Pfizer, Bitteroot and Molecular Imaging. All other authors declare no conflicts of interest, financial or otherwise.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Glucose uptake capacity of bone marrow GMP post MI and baseline phenotype in Vav1iCre+Cpt1afl/fl mice.
a, Representative flow cytometry plots, showing the gating strategy on GMP. b, Flow histograms and c, statistical analysis of 2-NBD glucose fluorescence in GMP isolated from naive controls and mice on day 1 and 3 post MI. Data are displayed as mean ± s.e.m. (n = 8 per time, Brown-Forsythe and Welsh Anova with Dunnett’s T3 multiple comparison, two independent experiments) d, Experimental design. e, Gating strategy for blood leukocytes. f, Quantification of blood leukocytes in naive Cpt1afl/fl controls and Vav1iCre+Cpt1Afl/fl mice (n = 8 Cpt1afl/fl, n = 7 Vav1Cre+Cpt1afl/fl, two-tailed Welch’s t test, two independent experiments). g, Quantification of HSPC numbers and proliferation in naive Cpt1afl/fl controls and Vav1iCre+Cpt1afl/fl mice (n = 8 Cpt1afl/fl, n = 8 Vav1iCre+Cpt1afl/fl, two-tailed Welch’s t test, two independent experiments). h, Representative flow cytometry plot, gating strategy on GMP and histogram for puromycin quantification. i, GMP glucose dependency and FAO capacity (n = 5 Cpt1afl/fl n = 6 Vav1iCre+Cpt1afl/fl, two-tailed unpaired t-test, two independent experiments). Data are displayed as mean ± SEM.
Extended Data Fig. 2 Hematopoietic Cpt1a deficiency reduces hematopoiesis.
a, Quantification of blood leukocytes in Cpt1afl/fl controls and Vav1iCre+Cpt1afl/fl mice on day 3 after MI (n = 6 Cpt1afl/fl, n = 7 Vav1iCre+Cpt1afl/fl, two-tailed Welch’s t test, three independent experiments). b, Bone marrow SLAM-LSK numbers and proliferation and leukocyte numbers in Cpt1afl/fl controls and Vav1iCre+Cpt1afl/fl mice on day 3 after MI (n = 6 Cpt1afl/fl, n = 8 Vav1iCre+Cpt1afl/fl, two-tailed Welch’s t test, three independent experiments). Data are displayed as mean ± SEM. c, Gene essentiality (Chronos) scores for CPT1A (red curve) and F13B (blue, a control gene expressed in hematopoietic cells).
Extended Data Fig. 3 Deletion of Cpt1a from HSPC and their progeny does not change post-MI outcomes 3 weeks later.
a, Experimental Outline. b, Left ventricular morphology and function measured by cardiac magnetic resonance imaging (MRI) 3 weeks after coronary ligation in Cpt1afl/fl controls and Vav1iCre+Cpt1afl/fl mice (n = 7 and 13, two-tailed unpaired t-tests, three independent experiments). Data are displayed as mean ± s.e.m.
Extended Data Fig. 4 Expanded proliferation of hematopoietic stem and progenitor cells in the adipocyte-rich metaphysis after myocardial infarction.
a, Quantification of adipocytes in femur diaphysis versus metaphysis (n = 9 mice, two-tailed paired t test, three independent experiments). Data are displayed as mean ± SEM.b, Immunofluorescent staining of adipocytes in femur. c, Flow plots of BrdU incorporation into GMP, LSK and SLAM-LSK in the femur diaphysis versus metaphysis in mice on day 3 after MI. d, Quantification of GMP, LSK and SLAM-LSK proliferation in femur diaphysis versus metaphysis (n = 10 mice for diaphysis, n = 10 mice for metaphysis, two-tailed Welch’s t test, three independent experiments). Data are displayed as mean ± SEM e, Quantification of adipocytes number and size on indicated days after surgery (n = 5-6 per time, One-way ANOVA with Tukey’s multiple comparison tests, two independent experiments) Data are displayed as mean ± SEM f, Hematoxylin and eosin (H&E) stain for subcutaneous adipocytes in control mice and on day 3 after MI. g, Quantification of subcutaneous adipocyte size in control mice and on day 3 after MI (n = 20 fields of view for 3control mice, n = 20 fields of view for3 mice with MI, two-tailed Welch’s t test). Data are displayed as mean ± SEM h, H&E stain for visceral adipocytes in control mice and on day 3 after MI. h, Quantification of visceral adipocyte size in control mice and on day 3 after MI (n = 20 fields of view for 3 control mice, n = 20 fields of view for 3 mice with MI, two-tailed Welch’s t test). Data are displayed as mean ± SEM. j, Percentage of counted labeled cells in the respective distance range of a bone marrow adipocyte in control and MI mice (77 cells counted in control and 61 in MI mice, three independent experiments).
Extended Data Fig. 5 Baseline hematopoiesis and leukocyte profile in AdipoqCreERT2Atglfl/fl mice.
a, Schematic depiction of ATGL-mediated lipolysis and experimental design. b, Quantification of blood leukocytes in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice (n = 8 Atglfl/fl, n = 7 AdipoqCreERT2Atglfl/fl, two-tailed Welch’s t test, two independent experiments). c, Quantification of bone marrow SLAM-LSK, LSK, CMP and GMP numbers in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice (n = 8 Atglfl/fl, n = 7 AdipoqCreERT2Atglfl/fl, two-tailed Welch’s t test, two independent experiments). d, Flow plots of Brdu incorporation into LSK, SLAM-LSK, CMP and GMP in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice. e, Quantification of LSK, SLAM-LSK, CMP and GMP proliferation in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice (n = 8 Atglfl/fl, n = 7 AdipoqCreERT2Atglfl/fl, two-tailed Welch’s t test, two independent experiments). Data are displayed as mean ± SEM.
Extended Data Fig. 6 Reduced hematopoiesis and myocardial myeloid cell content in AdipoqCreERT2Atglfl/fl mice.
a, Bone marrow adipocyte immunofluorescence images stained with perilipin-1 in Atglfl/fl versus AdipoqCreERT2Atglfl/fl mice 3 days after MI. b, Quantification of adipocyte size (n = 4 Atglfl/fl, n = 6 AdipoqCreERT2Atglfl/fl, two-tailed Welch’s t test, three independent experiments). c, Quantification of blood leukocytes in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice 3 days after MI (n = 9 Atglfl/fl, n = 8 AdipoqCreERT2Atglfl/fl, two-tailed Welch’s t test, three independent experiments). d, Quantification of bone marrow leukocytes in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice 3 days after MI (n = 9 Atglfl/fl, n = 9 AdipoqCreERT2Atglfl/fl, two-tailed Welch’s t test, three independent experiments). e, Flow plots of infiltrated leukocytes in the hearts of Atglfl/fl controls and AdipoqCreERT2Atglfl/fl. f, Quantification of macrophages, monocytes and neutrophils in the myocardium of Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice 3 days after MI (n = 9 Atglfl/fl, n = 9 AdipoqCreERT2Atglfl/fl, two-tailed Welch’s t test, three independent experiments). Data are displayed as mean ± SEM.
Extended Data Fig. 7 Deletion of Atgl from adipocytes does not change 3 week post-MI outcomes.
a, Experimental Outline. b, Left ventricular morphology and function measured by cardiac magnetic resonance imaging (MRI) 3 weeks after coronary ligation in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice (n = 9 and 10, Unpaired t-tests, two independent experiments). c, Quantification of blood leukocytes, monocytes, neutrophils (PMN) and B cells by flow cytometry 3 weeks after coronary ligation in Atglfl/fl controls and AdipoqCreERT2Atglfl/fl mice. (n = 6 and 7, Unpaired t-tests). Data are displayed as mean ± SEM.
Supplementary information
Supplementary Table 1
Differentially regulated genes ordered by ascending P value in flow-sorted bone marrow GMPs isolated from controls and mice on day 2 after MI, as assessed by RNA-seq. A Wald test was performed, and the P value was adjusted for multiple multiple comparisons based on the Benjamini–Hochberg algorithm to control the FDR.
Supplementary Table 2
Mass spectrometry data for Fig. 1f.
Source data
Source Data Fig. 1
Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 3
Statistical source data.
Source Data Fig. 4
Statistical source data.
Source Data Fig. 5
Statistical source data.
Source Data Fig. 6
Statistical source data.
Source Data Fig. 7
Statistical source data.
Source Data Extended Data Fig./Table 1
Statistical source data.
Source Data Extended Data Fig./Table 2
Statistical source data.
Source Data Extended Data Fig./Table 3
Statistical source data.
Source Data Extended Data Fig./Table 4
Statistical source data.
Source Data Extended Data Fig./Table 5
Statistical source data.
Source Data Extended Data Fig./Table 6
Statistical source data.
Source Data Extended Data Fig./Table 7
Statistical source data.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhang, S., Paccalet, A., Rohde, D. et al. Bone marrow adipocytes fuel emergency hematopoiesis after myocardial infarction. Nat Cardiovasc Res 2, 1277–1290 (2023). https://doi.org/10.1038/s44161-023-00388-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s44161-023-00388-7
This article is cited by
-
Systemic and local regulation of hematopoietic homeostasis in health and disease
Nature Cardiovascular Research (2024)
-
Bone marrow adipocytes support fatty acid metabolism during MI-mediated emergency haematopoiesis
Nature Reviews Cardiology (2024)