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Inflammation across tissues: can shared cell biology help design smarter trials?

An Author Correction to this article was published on 26 October 2023

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Abstract

Immune-mediated inflammatory diseases (IMIDs) are responsible for substantial global disease burden and associated health-care costs. Traditional models of research and service delivery silo their management within organ-based medical disciplines. Very often patients with disease in one organ have comorbid involvement in another, suggesting shared pathogenic pathways. Moreover, different IMIDs are often treated with the same drugs (including glucocorticoids, immunoregulators and biologics). Unlocking the cellular basis of these diseases remains a major challenge, leading us to ask why, if these diseases have so much in common, they are not investigated in a common manner. A tissue-based, cellular understanding of inflammation might pave the way for cross-disease, cross-discipline basket trials (testing one drug across two or more diseases) to reduce the risk of failure of early-phase drug development in IMIDs. This new approach will enable rapid assessment of the efficacy of new therapeutic agents in cross-disease translational research in humans.

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Fig. 1: Organ-based and molecular taxonomies of immune-mediated inflammatory diseases.
Fig. 2: The current approach to trials of new therapies in immune-mediated inflammatory diseases.

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References

  1. Netea, M. G. et al. A guiding map for inflammation. Nat. Immunol. 18, 826–831 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. El-Gabalawy, H., Guenther, L. C. & Bernstein, C. N. Epidemiology of immune-mediated inflammatory diseases: incidence, prevalence, natural history, and comorbidities. J. Rheumatol. Suppl. 85, 2–10 (2010).

    Article  PubMed  Google Scholar 

  3. Ng, S. C. et al. Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies. Lancet 390, 2769–2778 (2017).

    Article  PubMed  Google Scholar 

  4. Conrad, N. et al. Incidence, prevalence, and co-occurrence of autoimmune disorders over time and by age, sex, and socioeconomic status: a population-based cohort study of 22 million individuals in the UK. Lancet 401, 1878–1890 (2023).

    Article  PubMed  Google Scholar 

  5. Hemminki, K., Li, X., Sundquist, K. & Sundquist, J. Shared familial aggregation of susceptibility to autoimmune diseases. Arthritis Rheum. 60, 2845–2847 (2009).

    Article  PubMed  Google Scholar 

  6. Bernstein, C. N., Wajda, A. & Blanchard, J. F. The clustering of other chronic inflammatory diseases in inflammatory bowel disease: a population-based study. Gastroenterology 129, 827–836 (2005).

    Article  PubMed  Google Scholar 

  7. Thjodleifsson, B., Geirsson, A. J., Björnsson, S. & Bjarnason, I. A common genetic background for inflammatory bowel disease and ankylosing spondylitis: a genealogic study in Iceland. Arthritis Rheum. 56, 2633–2639 (2007).

    Article  PubMed  Google Scholar 

  8. Kuo, C. F. et al. Familial aggregation of systemic lupus erythematosus and coaggregation of autoimmune diseases in affected families. JAMA Intern. Med. 175, 1518–1526 (2015).

    Article  PubMed  Google Scholar 

  9. Cotsapas, C. et al. Pervasive sharing of genetic effects in autoimmune disease. PLoS Genet. 7, e1002254 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Shirai, Y. et al. Multi-trait and cross-population genome-wide association studies across autoimmune and allergic diseases identify shared and distinct genetic component. Ann. Rheum. Dis. 81, 1301–1312 (2022).

    Article  CAS  PubMed  Google Scholar 

  11. Li, Y. R. et al. Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases. Nat. Med. 21, 1018–1027 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Savic, S., Caseley, E. A. & McDermott, M. F. Moving towards a systems-based classification of innate immune-mediated diseases. Nat. Rev. Rheumatol. 16, 222–237 (2020).

    Article  PubMed  Google Scholar 

  13. Schett, G., McInnes, I. B. & Neurath, M. F. Reframing immune-mediated inflammatory diseases through signature cytokine hubs. N. Engl. J. Med. 385, 628–639 (2021).

    Article  CAS  PubMed  Google Scholar 

  14. McInnes, I. B. & Gravallese, E. M. Immune-mediated inflammatory disease therapeutics: past, present and future. Nat. Rev. Immunol. 21, 680–686 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Baeten, D. et al. Risankizumab, an IL-23 inhibitor, for ankylosing spondylitis: results of a randomised, double-blind, placebo-controlled, proof-of-concept, dose-finding phase 2 study. Ann. Rheum. Dis. 77, 1295–1302 (2018).

    Article  CAS  PubMed  Google Scholar 

  16. Deodhar, A. et al. Three multicenter, randomized, double-blind, placebo-controlled studies evaluating the efficacy and safety of ustekinumab in axial spondyloarthritis. Arthritis Rheumatol. 71, 258–270 (2019).

    Article  CAS  PubMed  Google Scholar 

  17. Targan, S. R. et al. A randomized, double-blind, placebo-controlled phase 2 study of brodalumab in patients with moderate-to-severe Crohn’s disease. Am. J. Gastroenterol. 111, 1599–1607 (2016).

    Article  CAS  PubMed  Google Scholar 

  18. Hueber, W. et al. Secukinumab, a human anti-IL-17A monoclonal antibody, for moderate to severe Crohn’s disease: unexpected results of a randomised, double-blind placebo-controlled trial. Gut 61, 1693–1700 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Lee, J. S. et al. Interleukin-23-independent IL-17 production regulates intestinal epithelial permeability. Immunity 43, 727–738 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Uzzan, M. et al. Ulcerative colitis is characterized by a plasmablast-skewed humoral response associated with disease activity. Nat. Med. 28, 766–779 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Parikh, K. et al. Colonic epithelial cell diversity in health and inflammatory bowel disease. Nature 567, 49–55 (2019).

    Article  CAS  PubMed  Google Scholar 

  22. Kinchen, J. et al. Structural remodeling of the human colonic mesenchyme in inflammatory bowel disease. Cell 175, 372–386.e17 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Huang, B. et al. Mucosal profiling of pediatric-onset colitis and IBD reveals common pathogenics and therapeutic pathways. Cell 179, 1160–1176.e24 (2019).

    Article  CAS  PubMed  Google Scholar 

  24. Corridoni, D. et al. Single-cell atlas of colonic CD8+ T cells in ulcerative colitis. Nat. Med. 26, 1480–1490 (2020).

    Article  CAS  PubMed  Google Scholar 

  25. Smillie, C. S. et al. Intra- and inter-cellular rewiring of the human colon during ulcerative colitis. Cell 178, 714–730.e22 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Elmentaite, R. et al. Cells of the human intestinal tract mapped across space and time. Nature 597, 250–255 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Wei, K. et al. Notch signalling drives synovial fibroblast identity and arthritis pathology. Nature 582, 259–264 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Zhang, F. et al. Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nat. Immunol. 20, 928–942 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Croft, A. P. et al. Distinct fibroblast subsets drive inflammation and damage in arthritis. Nature 570, 246–251 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Alivernini, S. et al. Distinct synovial tissue macrophage subsets regulate inflammation and remission in rheumatoid arthritis. Nat. Med. 26, 1295–1306 (2020).

    Article  CAS  PubMed  Google Scholar 

  31. Martin, J. C. et al. Single-cell analysis of Crohn’s disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy. Cell 178, 1493–1508.e20 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Friedrich, M. et al. IL-1-driven stromal-neutrophil interactions define a subset of patients with inflammatory bowel disease that does not respond to therapies. Nat. Med. 27, 1970–1981 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zhang, F. et al. Cellular deconstruction of inflamed synovium defines diverse inflammatory phenotypes in rheumatoid arthritis. bioRxiv Preprint at https://doi.org/10.1101/2022.02.25.481990v1 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Macnair, W. et al. Single nuclei RNAseq stratifies multiple sclerosis patients into three distinct white matter glia responses. bioRxiv Preprint at https://doi.org/10.1101/2022.04.06.487263v1 (2021).

    Article  Google Scholar 

  35. Korsunsky, I. et al. Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases. Med 3, 481–518.e14 (2022).

    Article  CAS  PubMed  Google Scholar 

  36. Zhang, F. et al. IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation. Genome Med. 13, 64 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Mulder, K. et al. Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease. Immunity 54, 1883–1990.e5 (2021).

    Article  CAS  PubMed  Google Scholar 

  38. Rivellese, F. et al. Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial. Nat. Med. 28, 1256–1268 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Humby, F. et al. Rituximab versus tocilizumab in anti-TNF inadequate responder patients with rheumatoid arthritis (R4RA): 16-week outcomes of a stratified, biopsy-driven, multicentre, open-label, phase 4 randomised controlled trial. Lancet 397, 305–317 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Agrawal, M., Allin, K. H., Petralia, F., Colombel, J. F. & Jess, T. Multiomics to elucidate inflammatory bowel disease risk factors and pathways. Nat. Rev. Gastroenterol. Hepatol. 19, 399–407 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Morgan, P. et al. Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving phase II survival. Drug. Discov. Today 17, 419–424 (2012).

    Article  CAS  PubMed  Google Scholar 

  42. Cook, D. et al. Lessons learned from the fate of AstraZeneca’s drug pipeline: a five-dimensional framework. Nat. Rev. Drug. Discov. 13, 419–431 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. Ringel, M., Tollman, P., Hersch, G. & Schulze, U. Does size matter in R&D productivity? If not, what does. Nat. Rev. Drug. Discov. 12, 901–902 (2013).

    Article  CAS  PubMed  Google Scholar 

  44. Woodcock, J. & LaVange, L. M. Master protocols to study multiple therapies, multiple diseases, or both. N. Engl. J. Med. 377, 62–70 (2017).

    Article  CAS  PubMed  Google Scholar 

  45. Fountzilas, E., Tsimberidou, A. M., Vo, H. H. & Kurzrock, R. Clinical trial design in the era of precision medicine. Genome Med. 14, 101 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Pitzalis, C., Choy, E. H. S. & Buch, M. H. Transforming clinical trials in rheumatology: towards patient-centric precision medicine. Nat. Rev. Rheumatol. 16, 590–599 (2020).

    Article  PubMed  Google Scholar 

  47. Janiaud, P., Serghiou, S. & Ioannidis, J. P. A. New clinical trial designs in the era of precision medicine: an overview of definitions, strengths, weaknesses, and current use in oncology. Cancer Treat. Rev. 73, 20–30 (2019).

    Article  PubMed  Google Scholar 

  48. Lu, C. C. et al. Practical considerations and recommendations for master protocol framework: basket, umbrella and platform trials. Ther. Innov. Regul. Sci. 55, 1145–1154 (2021).

    Article  PubMed  Google Scholar 

  49. Collignon, O. et al. Current statistical considerations and regulatory perspectives on the planning of confirmatory basket, umbrella, and platform trials. Clin. Pharmacol. Ther. 107, 1059–1067 (2020).

    Article  PubMed  Google Scholar 

  50. Park, J. J. H. et al. Systematic review of basket trials, umbrella trials, and platform trials: a landscape analysis of master protocols. Trials 20, 572 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Hirakawa, A., Asano, J., Sato, H. & Teramukai, S. Master protocol trials in oncology: review and new trial designs. Contemp. Clin. Trials Commun. 12, 1–8 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Beckman, R. A., Antonijevic, Z., Kalamegham, R. & Chen, C. Adaptive design for a confirmatory basket trial in multiple tumor types based on a putative predictive biomarker. Clin. Pharmacol. Ther. 100, 617–625 (2016).

    Article  CAS  PubMed  Google Scholar 

  53. Heinrich, M. C. et al. Phase II, open-label study evaluating the activity of imatinib in treating life-threatening malignancies known to be associated with imatinib-sensitive tyrosine kinases. Clin. Cancer Res. 14, 2717–2725 (2008).

    Article  CAS  PubMed  Google Scholar 

  54. Hyman, D. M. et al. Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. N. Engl. J. Med. 373, 726–736 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Thall, P. F. et al. Hierarchical Bayesian approaches to phase II trials in diseases with multiple subtypes. Stat. Med. 22, 763–780 (2003).

    Article  PubMed  Google Scholar 

  56. Chu, Y. & Yuan, Y. A. Bayesian basket trial design using a calibrated Bayesian hierarchical model. Clin. Trials 15, 149–158 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Zheng, H., Grayling, M. J., Mozgunov, P., Jaki, T. & Wason, J. M. S. Bayesian sample size determination in basket trials borrowing information between subsets. Biostatistics https://doi.org/10.1093/biostatistics/kxac033 (2022).

  58. Ruberg, S. J. et al. Application of Bayesian approaches in drug development: starting a virtuous cycle. Nat. Rev. Drug. Discov. 22, 235–250 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Meyer, E. L. et al. The evolution of master protocol clinical trial designs: a systematic literature review. Clin. Ther. 42, 1330–1360 (2020).

    Article  PubMed  Google Scholar 

  60. Park, J. J. H., Hsu, G., Siden, E. G., Thorlund, K. & Mills, E. J. An overview of precision oncology basket and umbrella trials for clinicians. CA Cancer J. Clin. 70, 125–137 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  61. FDA Master Protocols: Efficient Clinical Trial Design Strategies to Expedite Development of Oncology Drugs and Biologics Guidance for Industry. U.S. Food & Drug Administration [online], https://www.fda.gov/regulatory-information/search-fda-guidance-documents/master-protocols-efficient-clinical-trial-design-strategies-expedite-development-oncology-drugs-and (2022).

  62. De Benedetti, F. et al. Canakinumab for the treatment of autoinflammatory recurrent fever syndromes. N. Engl. J. Med. 378, 1908–1919 (2018).

    Article  PubMed  Google Scholar 

  63. Tao, J. J., Schram, A. M. & Hyman, D. M. Basket studies: redefining clinical trials in the era of genome-driven oncology. Ann. Rev. Med. 69, 319–331 (2018).

    Article  CAS  PubMed  Google Scholar 

  64. Subbiah, V. et al. Efficacy of vemurafenib in patients with non-small-cell lung cancer with BRAF V600 mutation: an open-label, single-arm cohort of the histology-independent VE-BASKET study. JCO Precis. Oncol. 3, 266 (2019). PO.18.00266.

    Google Scholar 

  65. Mazieres, J. et al. Vemurafenib in non-small-cell lung cancer patients with BRAFV600 and BRAFnonV600 mutations. Ann. Oncol. 31, 289–294 (2020).

    Article  CAS  PubMed  Google Scholar 

  66. Liu, F., Li, N., Li, W. & Chen, C. Impact of clinical center variation on efficiency of exploratory umbrella design. Stat. Biosci. 12, 196–215 (2020).

    Article  Google Scholar 

  67. Diamond, E. L. et al. Vemurafenib for BRAF V600-mutant Erdheim-Chester disease and Langerhans cell histiocytosis: analysis of data from the histology-independent, phase 2, open-label VE-BASKET study. JAMA Oncol. 4, 384–388 (2018).

    Article  PubMed  Google Scholar 

  68. Trigo, J. et al. Lurbinectedin as second-line treatment for patients with small-cell lung cancer: a single-arm, open-label, phase 2 basket trial. Lancet Oncol. 21, 645–654 (2020).

    Article  CAS  PubMed  Google Scholar 

  69. Drilon, A. et al. Efficacy of larotrectinib in TRK fusion-positive cancers in adults and children. N. Engl. J. Med. 378, 731–739 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Rosenzwajg, M. et al. Immunological and clinical effects of low-dose interleukin-2 across 11 autoimmune diseases in a single, open clinical trial. Ann. Rheum. Dis. 78, 209–217 (2019).

    Article  CAS  PubMed  Google Scholar 

  71. He, J. et al. Efficacy and safety of low-dose interleukin 2 for primary Sjögren syndrome: a randomized clinical trial. JAMA Netw. Open. 5, e2241451 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Wang, J. et al. The numbers of peripheral regulatory T cells are reduced in patients with psoriatic arthritis and are restored by low-dose interleukin-2. Ther. Adv. Chronic Dis. 11, 2040622320916014 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Miao, M., Li, Y., Huang, B., He, J. & Li, Z. Hypomyopathic dermatomyositis with refractory dermatitis treated by low-dose IL-2. Dermatol. Ther. 10, 1181–1184 (2020).

    Article  Google Scholar 

  74. Zhang, X. et al. Efficacy and safety of low-dose interleukin-2 in combination with methotrexate in patients with active rheumatoid arthritis: a randomized, double-blind, placebo-controlled phase 2 trial. Signal. Transduct. Target. Ther. 7, 67 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Humrich, J. Y. et al. Low-dose interleukin-2 therapy in active systemic lupus erythematosus (LUPIL-2): a multicentre, double-blind, randomised and placebo-controlled phase II trial. Ann. Rheum. Dis. 81, 1685–1694 (2022).

    Article  CAS  PubMed  Google Scholar 

  76. Lähnemann, D. et al. Eleven grand challenges in single-cell data science. Genome Biol. 21, 31 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Tang, L. Sequencing single cells without killing. Nat. Methods 19, 1166 (2022).

    Article  CAS  PubMed  Google Scholar 

  78. Qiu, P. Embracing the dropouts in single-cell RNA-seq analysis. Nat. Commun. 11, 1169 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Kharchenko, P. V., Silberstein, L. & Scadden, D. T. Bayesian approach to single-cell differential expression analysis. Nat. Methods 11, 740–742 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Li, J., Zhang, Y., Yang, C. & Rong, R. Discrepant mRNA and protein expression in immune cells. Curr. Genomics 21, 560–563 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Trzupek, D. et al. Discovery of CD80 and CD86 as recent activation markers on regulatory T cells by protein-RNA single-cell analysis. Genome Med. 12, 55 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Bolton, C. et al. An integrated taxonomy for monogenic inflammatory bowel disease. Gastroenterology 162, 859–876 (2022).

    Article  CAS  PubMed  Google Scholar 

  83. Menis, J., Hasan, B. & Besse, B. New clinical research strategies in thoracic oncology: clinical trial design, adaptive, basket and umbrella trials, new end-points and new evaluations of response. Eur. Respir. Rev. 23, 367–378 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Dooley, A. J., Gupta, A. & Middleton, M. R. Ongoing response in BRAF V600E-mutant melanoma after cessation of intermittent vemurafenib therapy: a case report. Target. Oncol. 11, 557–563 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Sandri, S. et al. Vemurafenib resistance increases melanoma invasiveness and modulates the tumor microenvironment by MMP-2 upregulation. Pharmacol. Res. 111, 523–533 (2016).

    Article  CAS  PubMed  Google Scholar 

  86. Sands, B. et al. OP40 PRA023 demonstrated efficacy and favorable safety as induction therapy for moderately to severely active UC: phase 2 ARTEMIS-UC study results. European Crohn’s and Colitis Organisation [online], https://www.ecco-ibd.eu/publications/congress-abstracts/item/op40-pra023-demonstrated-efficacy-and-favorable-safety-as-induction-therapy-for-moderately-to-severely-active-uc-phase-2-artemis-uc-study-results.html (2023).

  87. Alsoud, D., Verstockt, B., Fiocchi, C. & Vermeire, S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol. Hepatol. 6, 589–595 (2021).

    Article  PubMed  Google Scholar 

  88. Kaizer, A., Zabor, E., Nie, L. & Hobbs, B. Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: a comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets. PLoS One 17, e0272367 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

S.P.L.T., H.H.U. and C.D.B. are supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford. H.H.U. is supported by The Leona M. and Harry B. Helmsley Charitable Trust.

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Correspondence to Christopher Dominic Buckley.

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T.T. has received grants and research support from Celsius Therapeutics, and consulting fees from AbbVie and ZuraBio, and has been an employee of Janssen. H.H.U. has received research support and/or consultancy fees from BMS, Eli Lilly, Janssen, Mestag, OMass and UCB Pharma. S.P.L.T. has received grants and/or research support from AbbVie, Buhlmann, Celgene, Celsius Therapeutics, ECCO, Helmsley Trust, IOIBD, Janssen, Lilly, Pfizer, Takeda, UCB, UKIERI, Vifor and the Norman Collisson Foundation, and consulting fees from Abacus, AbbVie, Actial, ai4gi, Alcimed, Allergan, Amgen, Apexian, Aptel, Arena, Asahi, Aspen, Astellas, Atlantic, AstraZeneca, Bioclinica, Biogen, Boehringer Ingelheim, BMS, Buhlmann, Calcico, Celgene, Cellerix, Cerimon, ChemoCentryx, CisBio, Clario, Coronado, Cosmo, Dynavax, Enterome, EQrX, Equillium, Falk, Ferring, Galapagos, Genentech/Roche, Genzyme, Gilead, GSK, Immunocore, Immunometabolism, Janssen, Lilly, Medarex, Merck, Mestag, Neovacs, Novartis, Novo Nordisk, Otsuka, Pentax, Pfizer, Phesi, Phillips, Protagonist, Proximagen, Resolute, Sandoz, Sanofi, Satisfai, Sorriso, Syndermix, Synthon, Takeda, Theravance, Tigenix, Tillotts, Topivert, TxCell, UCB Pharma, Vertex, VHsquared, Vifor, Warner Chilcott and Zeria, and speaker fees from AbbVie, Amgen, Biogen, BMS, Falk, Ferring, Janssen, Lilly, Pfizer, Shire, Takeda and UCB. No stocks or shares. C.D.B. has received research support and/or consultancy fees from Janssen, GSK, BMS, Celsius, Novartis and Roche, and has stocks or share options for Mestag. T.H. and R.R. declare no competing interests.

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Hosack, T., Thomas, T., Ravindran, R. et al. Inflammation across tissues: can shared cell biology help design smarter trials?. Nat Rev Rheumatol 19, 666–674 (2023). https://doi.org/10.1038/s41584-023-01007-2

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