Letter | Published:

Hepatocyte-secreted DPP4 in obesity promotes adipose inflammation and insulin resistance

Nature volume 555, pages 673677 (29 March 2018) | Download Citation


Obesity-induced metabolic disease involves functional integration among several organs via circulating factors, but little is known about crosstalk between liver and visceral adipose tissue (VAT)1. In obesity, VAT becomes populated with inflammatory adipose tissue macrophages (ATMs)2,3. In obese humans, there is a close correlation between adipose tissue inflammation and insulin resistance4,5, and in obese mice, blocking systemic or ATM inflammation improves insulin sensitivity6,7,8. However, processes that promote pathological adipose tissue inflammation in obesity are incompletely understood. Here we show that obesity in mice stimulates hepatocytes to synthesize and secrete dipeptidyl peptidase 4 (DPP4), which acts with plasma factor Xa to inflame ATMs. Silencing expression of DPP4 in hepatocytes suppresses inflammation of VAT and insulin resistance; however, a similar effect is not seen with the orally administered DPP4 inhibitor sitagliptin. Inflammation and insulin resistance are also suppressed by silencing expression of caveolin-1 or PAR2 in ATMs; these proteins mediate the actions of DPP4 and factor Xa, respectively. Thus, hepatocyte DPP4 promotes VAT inflammation and insulin resistance in obesity, and targeting this pathway may have metabolic benefits that are distinct from those observed with oral DPP4 inhibitors.

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  1. 1.

    et al. NF-κB mediates lipid-induced fetuin-A expression in hepatocytes that impairs adipocyte function effecting insulin resistance. Biochem. J. 429, 451–462 (2010)

  2. 2.

    et al. Obesity is associated with macrophage accumulation in adipose tissue. J. Clin. Invest. 112, 1796–1808 (2003)

  3. 3.

    et al. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J. Clin. Invest. 112, 1821–1830 (2003)

  4. 4.

    et al. Body mass index-independent inflammation in omental adipose tissue associated with insulin resistance in morbid obesity. Surg. Obes. Relat. Dis. 7, 60–67 (2011)

  5. 5.

    Adipose tissue inflammation: a cause or consequence of obesity-related insulin resistance? Clin. Sci. (Lond.) 130, 1603–1614 (2016)

  6. 6.

    , & Adipose expression of tumor necrosis factor-α: direct role in obesity-linked insulin resistance. Science 259, 87–91 (1993)

  7. 7.

    & Inflammatory links between obesity and metabolic disease. J. Clin. Invest. 121, 2111–2117 (2011)

  8. 8.

    et al. Gene silencing in adipose tissue macrophages regulates whole-body metabolism in obese mice. Proc. Natl Acad. Sci. USA 110, 8278–8283 (2013)

  9. 9.

    et al. Calcium signaling through CaMKII regulates hepatic glucose production in fasting and obesity. Cell Metab. 15, 739–751 (2012)

  10. 10.

    et al. Activation of calcium/calmodulin-dependent protein kinase II in obesity mediates suppression of hepatic insulin signaling. Cell Metab. 18, 803–815 (2013)

  11. 11.

    et al. Hepatocyte DACH1 is increased in obesity via nuclear exclusion of HDAC4 and promotes hepatic insulin resistance. Cell Reports 15, 2214–2225 (2016)

  12. 12.

    & The multifunctional or moonlighting protein CD26/DPPIV. Eur. J. Cell Biol. 82, 53–73 (2003)

  13. 13.

    , , , & Plasma dipeptidyl peptidase 4 activity correlates with body mass index and the plasma adiponectin concentration in healthy young people. Endocr. J. 59, 949–953 (2012)

  14. 14.

    et al. Dipeptidyl peptidase 4 is a novel adipokine potentially linking obesity to the metabolic syndrome. Diabetes 60, 1917–1925 (2011)

  15. 15.

    & The incretin system: glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors in type 2 diabetes. Lancet 368, 1696–1705 (2006)

  16. 16.

    , , & Adipocyte dysfunctions linking obesity to insulin resistance and type 2 diabetes. Nat. Rev. Mol. Cell Biol. 9, 367–377 (2008)

  17. 17.

    , , & Improved glycaemic control with dipeptidyl peptidase-4 inhibition in patients with type 2 diabetes: vildagliptin (LAF237) dose response. Diabetes Obes. Metab. 7, 692–698 (2005)

  18. 18.

    et al. Effect of the dipeptidyl peptidase-4 inhibitor sitagliptin as monotherapy on glycemic control in patients with type 2 diabetes. Diabetes Care 29, 2632–2637 (2006)

  19. 19.

    et al. Efficacy and safety of the dipeptidyl peptidase-4 inhibitor sitagliptin as monotherapy in patients with type 2 diabetes mellitus. Diabetologia 49, 2564–2571 (2006)

  20. 20.

    & Alogliptin as an initial therapy in patients with newly diagnosed, drug naïve type 2 diabetes: a randomized, control trial. Endocrine 41, 435–441 (2012)

  21. 21.

    & Efficacy, safety and dose-response relationship of teneligliptin, a dipeptidyl peptidase-4 inhibitor, in Japanese patients with type 2 diabetes mellitus. Diabetes Obes. Metab. 15, 810–818 (2013)

  22. 22.

    et al. A randomized, double-blind, placebo-controlled, phase II clinical trial to investigate the efficacy and safety of oral DA-1229 in patients with type 2 diabetes mellitus who have inadequate glycaemic control with diet and exercise. Diabetes Metab. Res. Rev. 31, 295–306 (2015)

  23. 23.

    et al. Cellular sites and mechanisms linking reduction of dipeptidyl peptidase-4 activity to control of incretin hormone action and glucose homeostasis. Cell Metab. 25, 152–165 (2017)

  24. 24.

    et al. Factor Xa induces cytokine production and expression of adhesion molecules by human umbilical vein endothelial cells. J. Immunol. 161, 4318–4324 (1998)

  25. 25.

    et al. Coagulation factor Xa stimulates interleukin-8 release in endothelial cells and mononuclear leukocytes: implications in acute myocardial infarction. Arterioscler. Thromb. Vasc. Biol. 25, 461–466 (2005)

  26. 26.

    , , & Initiation of the extrinsic pathway of coagulation by human and rabbit alveolar macrophages: a kinetic study. Blood 74, 1583–1590 (1989)

  27. 27.

    et al. CD26 mediates dissociation of Tollip and IRAK-1 from caveolin-1 and induces upregulation of CD86 on antigen-presenting cells. Mol. Cell. Biol. 25, 7743–7757 (2005)

  28. 28.

    et al. Factor Xa induces pro-inflammatory cytokine expression in RAW 264.7 macrophages via protease-activated receptor-2 activation. Am. J. Transl. Res. 7, 2326–2334 (2015)

  29. 29.

    et al. Dipeptidyl peptidase IV inhibitor sitagliptin reduces local inflammation in adipose tissue and in pancreatic islets of obese mice. Am. J. Physiol. Endocrinol. Metab. 300, E410–E421 (2011)

  30. 30.

    et al. A major role of insulin in promoting obesity-associated adipose tissue inflammation. Mol. Metab. 4, 507–518 (2015)

  31. 31.

    et al. A highly durable RNAi therapeutic inhibitor of PCSK9. N. Engl. J. Med. 376, 41–51 (2017)

  32. 32.

    et al. Selection and evaluation of clinically relevant AAV variants in a xenograft liver model. Nature 506, 382–386 (2014)

  33. 33.

    et al. Stress-induced skeletal muscle Gadd45a expression reprograms myonuclei and causes muscle atrophy. J. Biol. Chem. 287, 27290–27301 (2012)

  34. 34.

    et al. Hepatocellular carcinoma originates from hepatocytes and not from the progenitor/biliary compartment. J. Clin. Invest. 125, 3891–3903 (2015)

  35. 35.

    et al. Overproduction of cholesterol and fatty acids causes massive liver enlargement in transgenic mice expressing truncated SREBP-1a. J. Clin. Invest. 98, 1575–1584 (1996)

  36. 36.

    , & Isolation of adipose tissue immune cells. J. Vis. Exp. 22, e50707 (2013)

  37. 37.

    et al. Inhibition of circulating dipeptidyl peptidase 4 activity in patients with metastatic prostate cancer. Mol. Cell. Proteomics 13, 3082–3096 (2014)

  38. 38.

    et al. Orally delivered siRNA targeting macrophage Map4k4 suppresses systemic inflammation. Nature 458, 1180–1184 (2009)

  39. 39.

    et al. Peptide- and amine-modified glucan particles for the delivery of therapeutic siRNA. Mol. Pharm. 13, 964–978 (2016)

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We thank F. S. Katz for assistance with FPLC; R. Kaufman for adeno-ATF4; C. Adams and S. Bullard for Atf4fl/fl mice; and A. Ferrante, S. Ramakrishnan, J. Weitz and T. McGraw for discussions. E.C. was supported by NIH grant 5P30CA013696-42. I.T. was funded by grants from the NIH (HL087123 and HL075662) and by a grant from the Merck Investigator Studies Program. L.O. was funded by the NIH grant DK106045 and a grant from the Columbia University Diabetes Research Center (P30 DK063608). Y.S., S.M.N. and M.P.C. were funded by NIH grant DK103047. M.B. was funded by the Deutsche Forschungsgemeinschaft grant SFB1052.

Author information


  1. Department of Medicine, Columbia University Medical Center, New York, New York 10032, USA

    • Devram S. Ghorpade
    • , Lale Ozcan
    • , Ze Zheng
    •  & Ira Tabas
  2. Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA

    • Sarah M. Nicoloro
    • , Yuefei Shen
    •  & Michael P. Czech
  3. Proteomics Shared Resource in the Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA

    • Emily Chen
  4. Herbert Irving Comprehensive Cancer Center Proteomics Shared Resource, Columbia University Medical Center, New York, New York 10032, USA

    • Emily Chen
  5. Department of Medicine, University of Leipzig, Leipzig 04103, Germany

    • Matthias Blüher
  6. Department of Pathology & Cell Biology and Department of Physiology, Columbia University Medical Center, New York, New York 10032, USA

    • Ira Tabas


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D.S.G., L.O. and I.T. designed the study, analysed data and wrote the manuscript. D.S.G., L.O. and Z.Z. conducted the experiments. S.M.N., Y.S. and M.P.C. made the glucan-encapsulated siRNA particles (GERPs) and helped design these experiments and analyse the data. E.C. conducted the LC–MS/MS studies and assisted with data analysis. M.B. helped with interpretation of data.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Lale Ozcan or Ira Tabas.

Reviewer Information Nature thanks P. Scherer and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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

Extended data

Supplementary information

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  1. 1.

    Life Sciences Reporting Summary

  2. 2.

    Supplementary Data

    This file contains Supplementary Figures 1-16: Uncropped versions of blots. Uncropped blots are shown for the indicated cropped blots in the main and Extended Data figures.

  3. 3.

    Supplementary Tables

    This file contains Supplementary Table 1: Gene primers used for RT-qPCR. Primer sets are shown for the R-qPCR assays used in the study. Supplementary Table 2: LC-MS/MS spectral analyses. Supplementary Table 2a shows the normalized LC-MS/MS spectral counts of selected FPLC fractions of plasma from DIO mice (see Extended Data Figure 2f). The first set of data show proteins with higher normalized spectral counts in FPLC fraction 44 (F44; active in inducing Mcp1 in macrophages) than in fractions F42 and F46, which were inactive in this assay. The second set of data show normalized spectral counts of other proteins identified fractions 42, 44, and/or 46. Supplementary Table 2b shows normalized LC-MS/MS spectral counts in selected FPLC fractions of plasma from DIO mice that was immunodepleted of DPP4 (see Extended Data Figure 7c). The first set of data show proteins with higher normalized spectral counts in FPLC fraction 44 (F44; active in inducing Mcp1 in macrophages) than in fractions F42 and F46, which were inactive in this assay. The second set of data show normalized spectral counts of other proteins identified fractions 42, 44, and/or 46.

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