Fibrosis is a common pathology in cardiovascular disease1. In the heart, fibrosis causes mechanical and electrical dysfunction1,2 and in the kidney, it predicts the onset of renal failure3. Transforming growth factor β1 (TGFβ1) is the principal pro-fibrotic factor4,5, but its inhibition is associated with side effects due to its pleiotropic roles6,7. We hypothesized that downstream effectors of TGFβ1 in fibroblasts could be attractive therapeutic targets and lack upstream toxicity. Here we show, using integrated imaging–genomics analyses of primary human fibroblasts, that upregulation of interleukin-11 (IL-11) is the dominant transcriptional response to TGFβ1 exposure and required for its pro-fibrotic effect. IL-11 and its receptor (IL11RA) are expressed specifically in fibroblasts, in which they drive non-canonical, ERK-dependent autocrine signalling that is required for fibrogenic protein synthesis. In mice, fibroblast-specific Il11 transgene expression or Il-11 injection causes heart and kidney fibrosis and organ failure, whereas genetic deletion of Il11ra1 protects against disease. Therefore, inhibition of IL-11 prevents fibroblast activation across organs and species in response to a range of important pro-fibrotic stimuli. These results reveal a central role of IL-11 in fibrosis and we propose that inhibition of IL-11 is a potential therapeutic strategy to treat fibrotic diseases.

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We thank all patients for taking part in this research, which was performed with approval from the SingHealth Centralised IRB Review Board (CIRB; 2013/103/C). The research was supported by the National Medical Research Council (NMRC) Singapore STaR award (S.A.C.) (NMRC/STaR/0011/2012), the NMRC Centre Grant to the National Heart Centre Singapore (NHCS), Goh Foundation, Tanoto Foundation, NHLBI 5R01HL080494 (J.G.S., C.E.S.), HHMI (C.E.S.) and a grant from the Fondation Leducq (N.H., J.G.S., C.E.S., S.C.). We thank I. Kamer and R. Plehm, Max-Delbrück-Center for Molecular Medicine (MDC), for expert technical help with telemetry blood pressure measurements.

Author information

Author notes

    • Sebastian Schafer
    • , Sivakumar Viswanathan
    •  & Anissa A. Widjaja

    These authors contributed equally to this work.


  1. National Heart Centre Singapore, Singapore

    • Sebastian Schafer
    • , Wei-Wen Lim
    • , Benjamin Ng
    • , Kingsley Chow
    • , Jessie Tan
    • , Lei Ye
    • , Chee Jian Pua
    • , Nicole T. G. Zhen
    • , Chen Xie
    • , Shiqi Lim
    • , See L. Lim
    • , Jia L. Soon
    • , Victor T. T. Chao
    • , Yeow L. Chua
    • , Teing E. Tan
    • , Yee J. Loh
    • , Muhammad H. Jamal
    • , Kim K. Ong
    • , Kim C. Chua
    • , Boon-Hean Ong
    • , Mathew J. Chakaramakkil
    • , Kenny Y. K. Sin
    •  & Stuart A. Cook
  2. Duke–National University of Singapore Medical School, Singapore

    • Sebastian Schafer
    • , Sivakumar Viswanathan
    • , Anissa A. Widjaja
    • , Aida Moreno-Moral
    • , Ester Khin
    • , Sonia P. Chothani
    • , Owen J. L. Rackham
    • , Nicole S. J. Ko
    • , Norliza E. Sahib
    • , Mao Wang
    • , Enrico Petretto
    • , Kristmundur Sigmundsson
    • , Jia L. Soon
    • , Victor T. T. Chao
    • , Kenny Y. K. Sin
    •  & Stuart A. Cook
  3. Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA

    • Daniel M. DeLaughter
    • , Hiroko Wakimoto
    • , Jonathan G. Seidman
    •  & Christine E. Seidman
  4. Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rossle Strasse 10, 13125 Berlin, Germany

    • Giannino Patone
    • , Henrike Maatz
    • , Kathrin Saar
    • , Susanne Blachut
    • , Sabine Schmidt
    • , Sebastiaan van Heesch
    •  & Norbert Hubner
  5. Inflammation Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia

    • Tracy Putoczki
  6. Department of Medical Biology, The University of Melbourne, Parkville, Victoria 3050, Australia

    • Tracy Putoczki
  7. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA

    • Nuno Guimarães-Camboa
    •  & Sylvia M. Evans
  8. Department of Medicine, University of California at San Diego, La Jolla, California 92093, USA

    • Sylvia M. Evans
  9. Department of Pharmacology, University of California at San Diego, La Jolla, California 92093, USA

    • Sylvia M. Evans
  10. Kandang Kerbau Women’s and Children’s Hospital, Singapore

    • Yee J. Loh
    •  & Kim K. Ong
  11. Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, Massachusettes 02115, USA

    • Christine E. Seidman
  12. Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA

    • Christine E. Seidman
  13. DZHK (German Centre for Cardiovascular Research), partner site, Berlin, Germany

    • Norbert Hubner
  14. Charité-Universitätsmedizin, Berlin, Germany

    • Norbert Hubner
  15. Berlin Institute of Health (BIH), Berlin, Germany

    • Norbert Hubner
  16. National Heart and Lung Institute, Imperial College London, London, UK

    • Stuart A. Cook
  17. MRC-London Institute of Medical Sciences, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK

    • Stuart A. Cook


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S.A.C. conceived, managed and arranged funding for the project. Wet lab experiments (cell culture, cell biology, molecular biology, RNA-seq) were carried out by S.V., A.A.W., W.-W.L., B.N., G.P., J.T., L.Y., N.E.S., C.J.P., C.X., M.W., S.L., K.Sa., S.B., S.Schm., T.P., N.G.-C., H.W., S.v.H. and K.Si. Single-cell studies were carried out by D.M.D., J.G.S. and C.E.S. In vivo gain-of-function and loss-of-function mouse experiments were performed by A.A.W., W.-W.L., B.N., J.T., E.K., L.Y., N.S.J.K., N.T.G.Z., D.M.D., G.P. and H.M. Data were analysed by S.Scha., S.V., A.A.W., A.M.-M., K.C., S.P.C., O.J.L.R., K.Sa., E.P., S.M.E., J.G.S., C.E.S. and N.H. Patient-based studies were carried out by S.L.L., J.L.S., V.T.T.C., Y.L.C., T.E.T., Y.J.L., M.H.J., K.K.O., K.C.C., B.-H.O., M.J.C. and K.Y.K.S. S.Scha., S.V., A.A.W. and S.A.C. designed experiments and prepared the manuscript with input from co-authors.

Competing interests

S.A.C. and S.Scha. are co-inventors of the patent application (WO2017103108) ‘Treatment of fibrosis’. S.A.C. and S.Scha. are co-founders and shareholders of Enleofen Bio PTE LTD, a company that develops therapeutics based on findings described in this manuscript.

Corresponding author

Correspondence to Stuart A. Cook.

Reviewer Information Nature thanks S. Friedman 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

PDF files

  1. 1.

    Supplementary Figure

    This file contains source data for all western blot experiments.

  2. 2.

    Life Sciences Reporting Summary

Excel files

  1. 1.

    Supplementary Table 1

    Detailed information about the quality of each RNA sample, RNA-seq library and sample information about each individual that has contributed primary cells for the therapeutic target discovery high-content imaging screening and transcriptome profiling.

  2. 2.

    Supplementary Table 2

    Therapeutic Target Screen results: 1) Differentially expressed genes between TGFB stimulated fibroblasts and non-stimulated fibroblasts, 2) Spearman correlation (SPcor) between delta of fibroblasts expression (stimulated/non-stimulated) and delta of SMA, 3) Jensen–Shannon divergence (JSD) between of each gene across all GTEx tissues and FANTOM primary cell types (see more details in methods), 4) Average expression levels (transcripts per million, TPM) in TGFB1 stimulated and non-stimulated (baseline only) fibroblasts. Log2 fold change, shrunken Log2-fold changes computed by DESeq2 package. BH adj.P, Benjamini-Hochberg (BH) adjusted p-value.

  3. 3.

    Supplementary Table 3

    Gene Ontology database gene set enrichment analysis (GSEA) results for the stimulated versus baseline fibroblasts (GSEA computed by ranking all the genes by DESeq output statistic). Only terms enriched with FDR < 0.05 are presented. NES denotes normalized enrichment score.

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