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Pharmacomicrobiomics in inflammatory arthritis: gut microbiome as modulator of therapeutic response

Abstract

In the past three decades, extraordinary advances have been made in the understanding of the pathogenesis of, and treatment options for, inflammatory arthritides, including rheumatoid arthritis and spondyloarthritis. The use of methotrexate and subsequently biologic therapies (such as TNF inhibitors, among others) and oral small molecules have substantially improved clinical outcomes for many patients with inflammatory arthritis; for others, however, these agents do not substantially improve their symptoms. The emerging field of pharmacomicrobiomics, which investigates the effect of variations within the human gut microbiome on drugs, has already provided important insights into these therapeutics. Pharmacomicrobiomic studies have demonstrated that human gut microorganisms and their enzymatic products can affect the bioavailability, clinical efficacy and toxicity of a wide array of drugs through direct and indirect mechanisms. This discipline promises to facilitate the advent of microbiome-based precision medicine approaches in inflammatory arthritis, including strategies for predicting response to treatment and for modulating the microbiome to improve response to therapy or reduce drug toxicity.

Key points

  • Culture-independent, high-throughput DNA and RNA sequencing technologies —coupled with deeper insight into host mucosal immunology — have substantially advanced our understanding of the role of microorganisms in modulating health and disease.

  • Pharmacomicrobiomics, an emerging field that describes the complex interaction of drugs with the microbiome, is increasingly considered an important factor in the prediction of therapeutic responses in many medical subspecialties.

  • Multiple tools, including ex vivo cultures, metabolomics and gnotobiotic experiments, have enabled a deeper mechanistic understanding of host–microbial interactions in the pharmacokinetics of many available drugs.

  • Emerging evidence supports the notion that the bioavailability, clinical efficacy and toxicity of several drugs used to treat human inflammatory arthritis can be modulated by human gut microorganisms and their enzymatic products.

  • Pharmacomicrobiomics could potentially be incorporated into precision medicine approaches in rheumatology.

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Fig. 1: Gut microorganisms in drug metabolism and physiology.
Fig. 2: Mechanisms of gut microbiome modulation of anti-rheumatic drug disposition and response.
Fig. 3: Translational implications of pharmacomicrobiomic studies in rheumatic diseases.

References

  1. McInnes, I. B. & Schett, G. The pathogenesis of rheumatoid arthritis. N. Engl. J. Med. 365, 2205–2219 (2011).

    Article  CAS  PubMed  Google Scholar 

  2. Gladman, D. D., Antoni, C., Mease, P., Clegg, D. O. & Nash, P. Psoriatic arthritis: epidemiology, clinical features, course, and outcome. Ann. Rheum. Dis. 64, ii14–ii17 (2005).

    PubMed  PubMed Central  Google Scholar 

  3. Barnas, J. L. & Ritchlin, C. T. Etiology and pathogenesis of psoriatic arthritis. Rheum. Dis. Clin. North Am. 41, 643–663 (2015).

    Article  PubMed  Google Scholar 

  4. Taurog, J. D., Chhabra, A. & Colbert, R. A. Ankylosing spondylitis and axial spondyloarthritis. N. Engl. J. Med. 374, 2563–2574 (2016).

    Article  PubMed  Google Scholar 

  5. Keffer, J. et al. Transgenic mice expressing human tumour necrosis factor: a predictive genetic model of arthritis. EMBO J. 10, 4025–4031 (1991).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. McInnes, I. B. et al. Secukinumab, a human anti-interleukin-17A monoclonal antibody, in patients with psoriatic arthritis (FUTURE 2): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 386, 1137–1146 (2015).

    Article  CAS  PubMed  Google Scholar 

  7. Mease, P. J. et al. Adalimumab for the treatment of patients with moderately to severely active psoriatic arthritis: results of a double-blind, randomized, placebo-controlled trial. Arthritis Rheum. 52, 3279–3289 (2005).

    Article  CAS  PubMed  Google Scholar 

  8. Emery, P. et al. Comparison of methotrexate monotherapy with a combination of methotrexate and etanercept in active, early, moderate to severe rheumatoid arthritis (COMET): a randomised, double-blind, parallel treatment trial. Lancet 372, 375–382 (2008).

    Article  CAS  PubMed  Google Scholar 

  9. Liu, W. et al. Efficacy and safety of TNF-alpha inhibitors for active ankylosing spondylitis patients: multiple treatment comparisons in a network meta-analysis. Sci. Rep. 6, 32768 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Baeten, D. et al. Secukinumab, an interleukin-17A inhibitor, in ankylosing spondylitis. N. Engl. J. Med. 373, 2534–2548 (2015).

    Article  CAS  PubMed  Google Scholar 

  11. Lee, E. B. et al. Tofacitinib versus methotrexate in rheumatoid arthritis. N. Engl. J. Med. 370, 2377–2386 (2014).

    Article  PubMed  CAS  Google Scholar 

  12. Gladman, D. et al. Tofacitinib for psoriatic arthritis in patients with an inadequate response to TNF inhibitors. N. Engl. J. Med. 377, 1525–1536 (2017).

    Article  CAS  PubMed  Google Scholar 

  13. Kavanaugh, A. et al. Treatment of psoriatic arthritis in a phase 3 randomised, placebo-controlled trial with apremilast, an oral phosphodiesterase 4 inhibitor. Ann. Rheum. Dis. 73, 1020–1026 (2014).

    Article  CAS  PubMed  Google Scholar 

  14. Abdollahi-Roodsaz, S., Abramson, S. B. & Scher, J. U. The metabolic role of the gut microbiota in health and rheumatic disease: mechanisms and interventions. Nat. Rev. Rheumatol. 12, 446–455 (2016).

    Article  CAS  PubMed  Google Scholar 

  15. Curtis, J. R. et al. Use of a validated algorithm to estimate the annual cost of effective biologic treatment for rheumatoid arthritis. J. Med. Econ. 17, 555–566 (2014).

    Article  PubMed  Google Scholar 

  16. Scher, J. U. & Abramson, S. B. The microbiome and rheumatoid arthritis. Nat. Rev. Rheumatol. 7, 569–578 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Scher, J. U. et al. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2, e01202 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Scher, J. U. et al. Decreased bacterial diversity characterizes the altered gut microbiota in patients with psoriatic arthritis, resembling dysbiosis in inflammatory bowel disease. Arthritis Rheumatol. 67, 128–139 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Koppel, N., Maini Rekdal V. & Balskus E. P. Chemical transformation of xenobiotics by the human gut microbiota. Science 356, eaag2770 (2017).

    Article  PubMed  CAS  Google Scholar 

  20. Saad, R., Rizkallah, M. R. & Aziz, R. K. Gut pharmacomicrobiomics: the tip of an iceberg of complex interactions between drugs and gut-associated microbes. Gut Pathog. 4, 16 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Doestzada, M. et al. Pharmacomicrobiomics: a novel route towards personalized medicine? Protein Cell 9, 432–445 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Rizkallah M. S. R. & Aziz, R. K. The Human Microbiome Project, personalized medicine and the birth of pharmacomicrobiomics. Curr. Pharmacogenomics Person. Med. 8, 182–193 (2010).

    Article  CAS  Google Scholar 

  23. JeT, Tréfouël, Nitti, F. & Bovet, D. Activité du p-aminophénylsulfamide surl’infection streptococcique expérimentar de la souris et du lapin. CR Soc. Biol. 120, 23 (1935).

    Google Scholar 

  24. Butler, V., Neu, H. & Lindenbaum, J. Digoxin-inactivating bacteria: identification in human gut flora. Science 220, 325–327 (1983).

    Article  PubMed  Google Scholar 

  25. Jobin, C. Precision medicine using microbiota. Science 359, 32–34 (2018).

    Article  CAS  PubMed  Google Scholar 

  26. Kuntz, T. M. & Gilbert, J. A. Introducing the microbiome into precision medicine. Trends Pharmacol. Sci. 38, 81–91 (2017).

    Article  CAS  PubMed  Google Scholar 

  27. Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222–227 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Gensollen, T., Iyer, S. S., Kasper, D. L. & Blumberg, R. S. How colonization by microbiota in early life shapes the immune system. Science 352, 539–544 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009).

    Article  CAS  PubMed  Google Scholar 

  30. Nicholson, J. K. et al. Host-gut microbiota metabolic interactions. Science 336, 1262–1267 (2012).

    Article  CAS  PubMed  Google Scholar 

  31. Honda, K. & Littman, D. R. The microbiome in infectious disease and inflammation. Annu. Rev. Immunol. 30, 759–795 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sousa, T. et al. The gastrointestinal microbiota as a site for the biotransformation of drugs. Int. J. Pharm. 363, 1–25 (2008).

    Article  CAS  PubMed  Google Scholar 

  33. Birer, C. & Wright, E. S. Capturing the complex interplay between drugs and the intestinal microbiome. Clin. Pharmacol. Ther. 106, 501–504 (2019).

    Article  PubMed  Google Scholar 

  34. Maini Rekdal, V., Bess, E. N., Bisanz, J. E., Turnbaugh, P. J. & Balskus, E. P. Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism. Science 364, eaau6323 (2019).

    Article  PubMed  Google Scholar 

  35. Peppercorn, M. A. & Goldman, P. The role of intestinal bacteria in the metabolism of salicylazosulfapyridine. J. Pharmacol. Exp. Ther. 181, 555–562 (1972).

    CAS  PubMed  Google Scholar 

  36. Nayak, R. R. & Turnbaugh, P. J. Mirror, mirror on the wall: which microbiomes will help heal them all? BMC Med. 14, 72 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Sharma, A. K., Jaiswal, S. K., Chaudhary, N. & Sharma, V. K. A novel approach for the prediction of species-specific biotransformation of xenobiotic/drug molecules by the human gut microbiota. Sci. Rep. 7, 9751 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Spanogiannopoulos, P., Bess, E. N., Carmody, R. N. & Turnbaugh, P. J. The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism. Nat. Rev. Microbiol. 14, 273–287 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Gill, S. R. et al. Metagenomic analysis of the human distal gut microbiome. Science 312, 1355 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Human Microbiome Project. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

    Article  CAS  Google Scholar 

  41. Holmes, E. et al. Therapeutic modulation of microbiota-host metabolic interactions. Sci. Transl Med. 4, 137rv136 (2012).

    Article  CAS  Google Scholar 

  42. Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. & Goodman, A. L. Mapping human microbiome drug metabolism by gut bacteria and their genes. Nature 570, 462–467 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Couteau, D., McCartney, A. L., Gibson, G. R., Williamson, G. & Faulds, C. B. Isolation and characterization of human colonic bacteria able to hydrolyse chlorogenic acid. J. Appl. Microbiol. 90, 873–881 (2001).

    Article  CAS  PubMed  Google Scholar 

  44. Lindenbaum, J., Rund, D. G., Butler, V. P. Jr., Tse-Eng, D. & Saha, J. R. Inactivation of digoxin by the gut flora: reversal by antibiotic therapy. N. Engl. J. Med. 305, 789–794 (1981).

    Article  CAS  PubMed  Google Scholar 

  45. Haiser, H. J. et al. Predicting and manipulating cardiac drug inactivation by the human gut bacterium Eggerthella lenta. Science 341, 295–298 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Haiser, H. J., Seim, K. L., Balskus, E. P. & Turnbaugh, P. J. Mechanistic insight into digoxin inactivation by Eggerthella lenta augments our understanding of its pharmacokinetics. Gut Microbes 5, 233–238 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Koppel, N., Bisanz, J. E., Pandelia, M. E., Turnbaugh, P. J. & Balskus, E. P. Discovery and characterization of a prevalent human gut bacterial enzyme sufficient for the inactivation of a family of plant toxins. eLife 7, e33953 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Niehues, M. & Hensel, A. In-vitro interaction of L-dopa with bacterial adhesins of Helicobacter pylori: an explanation for clinicial differences in bioavailability? J. Pharm. Pharmacol. 61, 1303–1307 (2009).

    CAS  PubMed  Google Scholar 

  49. LoGuidice, A., Wallace, B. D., Bendel, L., Redinbo, M. R. & Boelsterli, U. A. Pharmacologic targeting of bacterial beta-glucuronidase alleviates nonsteroidal anti-inflammatory drug-induced enteropathy in mice. J. Pharmacol. Exp. Ther. 341, 447–454 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Bjorkholm, B. et al. Intestinal microbiota regulate xenobiotic metabolism in the liver. PLoS One 4, e6958 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Wang, Z. et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472, 57–63 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Tang, W. H. et al. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. N. Engl. J. 368, 1575–1584 (2013).

    Article  CAS  Google Scholar 

  53. Craciun, S. & Balskus, E. P. Microbial conversion of choline to trimethylamine requires a glycyl radical enzyme. Proc. Natl Acad. Sci. USA 109, 21307–21312 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Nakayama, H. et al. Intestinal anaerobic bacteria hydrolyse sorivudine, producing the high blood concentration of 5-(E)-(2-bromovinyl)uracil that increases the level and toxicity of 5-fluorouracil. Pharmacogenetics 7, 35–43 (1997).

    Article  CAS  PubMed  Google Scholar 

  55. Aziz, R. K., Hegazy, S. M., Yasser, R., Rizkallah, M. R. & ElRakaiby, M. T. Drug pharmacomicrobiomics and toxicomicrobiomics: from scattered reports to systematic studies of drug-microbiome interactions. Expert. Opin. Drug. Metab. Toxicol. 14, 1043–10553 (1918).

    Article  CAS  Google Scholar 

  56. Wallace, B. D. et al. Alleviating cancer drug toxicity by inhibiting a bacterial enzyme. Science 330, 831–8353 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Saha, J. R., Butler, V. P. Jr., Neu, H. C. & Lindenbaum, J. Digoxin-inactivating bacteria: identification in human gut flora. Science 220, 325–3273 (1983).

    Article  CAS  PubMed  Google Scholar 

  58. Bisanz, J. E., Spanogiannopoulos, P., Pieper, L. M., Bustion, A. E. & Turnbaugh, P. J. How to determine the role of the microbiome in drug disposition. Drug. Metab. Dispos. 46, 1588–1595 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Nguyen, T. L., Vieira-Silva, S., Liston, A. & Raes, J. How informative is the mouse for human gut microbiota research? Dis. Model. Mech. 8, 1–16 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Faith, J. J. et al. Creating and characterizing communities of human gut microbes in gnotobiotic mice. ISME J. 4, 1094–1098 (2010).

    Article  PubMed  Google Scholar 

  61. Turnbaugh, P. J. et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 1027–1031 (2006).

    Article  PubMed  Google Scholar 

  62. Svartz, N. Treatment of rheumatoid arthritis with salicylazosulfapyridine. Acta Med. Scand. Suppl. 341, 247–254 (1958).

    CAS  PubMed  Google Scholar 

  63. Svartz, N. The treatment of rheumatic polyarthritis with acid azo compounds. Rheumatism 4, 180–185 (1948).

    CAS  PubMed  Google Scholar 

  64. Das, K. M. & Dubin, R. Clinical pharmacokinetics of sulphasalazine. Clin. Pharmacokinet. 1, 406–425 (1976).

    Article  CAS  PubMed  Google Scholar 

  65. Sousa, T. et al. On the colonic bacterial metabolism of azo-bonded prodrugs of 5-aminosalicylic acid. J. Pharm. Sci. 103, 3171–3175 (2014).

    Article  CAS  PubMed  Google Scholar 

  66. Valerino, D. M., Johns, D. G., Zaharko, D. S. & Oliverio, V. T. Studies of the metabolism of methotrexate by intestinal flora—I: Identification and study of biological properties of the metabolite 4-amino-4-deoxy-N 10-methylpteroic acid. Biochem. Pharmacol. 21, 821–831 (1972).

    Article  CAS  PubMed  Google Scholar 

  67. Zaharko, D. S., Bruckner, H. & Oliverio, V. T. Antibiotics alter methotrexate metabolism and excretion. Science 166, 887–888 (1969).

    Article  CAS  PubMed  Google Scholar 

  68. Viaud, S. et al. The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science 342, 971–976 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Iida, N. et al. Commensal bacteria control cancer response to therapy by modulating the tumor microenvironment. Science 342, 967–970 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Dubin, K. et al. Intestinal microbiome analyses identify melanoma patients at risk for checkpoint-blockade-induced colitis. Nat. Commun. 7, 10391 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Chaput, N. et al. Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab. Ann. Oncol. 28, 1368–1379 (2017).

    Article  CAS  PubMed  Google Scholar 

  72. Gopalakrishnan, V. et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 359, 97–103 (2018).

    Article  CAS  PubMed  Google Scholar 

  73. Routy, B. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359, 91–97 (2018).

    Article  CAS  PubMed  Google Scholar 

  74. Matson, V. et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 359, 104–108 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Vetizou, M. et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 350, 1079–1084 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Wang, Y. et al. Fecal microbiota transplantation for refractory immune checkpoint inhibitor-associated colitis. Nat. Med. 24, 1804–1808 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Smith, M. H. & Bass A. R. Arthritis after cancer immunotherapy: symptom duration and treatment response. Arthritis Care Res. 71, 362–366 (2017).

    Article  CAS  Google Scholar 

  78. Cappelli, L. C. et al. Clinical presentation of immune checkpoint inhibitor-induced inflammatory arthritis differs by immunotherapy regimen. Semin. Arthritis Rheum. 48, 553–557 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Paramsothy, S., Rosenstein, A. K., Mehandru, S. & Colombel, J. F. The current state of the art for biological therapies and new small molecules in inflammatory bowel disease. Mucosal Immunol. 11, 1558–1570 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Magnusson, M. K. et al. Anti-TNF therapy response in patients with ulcerative colitis is associated with colonic antimicrobial peptide expression and microbiota composition. J. Crohns Colitis 10, 943–952 (2016).

    Article  PubMed  Google Scholar 

  81. Ananthakrishnan, A. N. et al. Gut microbiome function predicts response to anti-integrin biologic therapy in inflammatory bowel diseases. Cell Host Microbe 21, 603–610 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Sandborn, W. J. et al. Ustekinumab induction and maintenance therapy in refractory Crohn’s disease. N. Engl. J. Med. 367, 1519–1528 (2012).

    Article  CAS  PubMed  Google Scholar 

  83. Clayton, T. A., Baker, D., Lindon, J. C., Everett, J. R. & Nicholson, J. K. Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism. Proc. Natl Acad. Sci. USA 106, 14728–14733 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Wilson, I. D. Drugs, bugs, and personalized medicine: pharmacometabonomics enters the ring. Proc. Natl Acad. Sci. USA 106, 14187–14188 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Haiser, H. J. & Turnbaugh, P. J. Developing a metagenomic view of xenobiotic metabolism. Pharmacol. Res. 69, 21–31 (2013).

    Article  CAS  PubMed  Google Scholar 

  86. Ryan, A. Azoreductases in drug metabolism. Br. J. Pharmacol. 174, 2161–2173 (2017).

    Article  CAS  PubMed  Google Scholar 

  87. Morrison, J. M., Wright, C. M. & John, G. H. Identification, isolation and characterization of a novel azoreductase from clostridium perfringens. Anaerobe 18, 229–234 (2012).

    Article  CAS  PubMed  Google Scholar 

  88. Chen, H., Wang, R. F. & Cerniglia, C. E. Molecular cloning, overexpression, purification, and characterization of an aerobic FMN-dependent azoreductase from Enterococcus faecalis. Protein Expr. Purif. 34, 302–310 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Delomenie, C. et al. Identification and functional characterization of arylamine N-acetyltransferases in eubacteria: evidence for highly selective acetylation of 5-aminosalicylic acid. J. Bacteriol. 183, 3417–3427 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Sim, E., Abuhammad, A. & Ryan, A. Arylamine N-acetyltransferases: from drug metabolism and pharmacogenetics to drug discovery. Br. J. Pharmacol. 171, 2705–2725 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Bazin, T. et al. Microbiota composition may predict anti-TNF alpha response in spondyloarthritis patients: an exploratory study. Sci. Rep. 8, 5446 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  92. Kim, D. et al. Optimizing methods and dodging pitfalls in microbiome research. Microbiome 5, 52 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Rehaume, L. M. et al. IL-23 favours outgrowth of spondyloarthritis-associated pathobionts and suppresses host support for homeostatic microbiota. Ann. Rheum. Dis. 78, 494–503 (2019).

    Article  CAS  PubMed  Google Scholar 

  94. Manasson, J. et al. IL-17 inhibition in spondyloarthritis associates with subclinical gut microbiome perturbations and a distinctive IL-25-driven intestinal inflammation. Arthritis Rheumatol. https://doi.org/10.1002/art.41169 (2019).

  95. Saunte, D. M., Mrowietz, U., Puig, L. & Zachariae, C. Candida infections in patients with psoriasis and psoriatic arthritis treated with interleukin-17 inhibitors and their practical management. Br. J. Dermatol. 177, 47–62 (2017).

    Article  CAS  PubMed  Google Scholar 

  96. Gerard, R., Sendid, B., Colombel, J. F., Poulain, D. & Jouault, T. An immunological link between Candida albicans colonization and Crohn’s disease. Crit. Rev. Microbiol. 41, 135–139 (2015).

    Article  CAS  PubMed  Google Scholar 

  97. Colombel, J. F., Sendid, B., Jouault, T. & Poulain, D. Secukinumab failure in Crohn’s disease: the yeast connection? Gut 62, 800–801 (2013).

    Article  CAS  PubMed  Google Scholar 

  98. Favalli, E. G., Biggioggero, M. & Meroni, P. L. Methotrexate for the treatment of rheumatoid arthritis in the biologic era: still an “anchor” drug? Autoimmun. Rev. 13, 1102–1108 (2014).

    Article  CAS  PubMed  Google Scholar 

  99. Aletaha, D. & Smolen, J. S. Diagnosis and management of rheumatoid arthritis: a review. JAMA 320, 1360–1372 (2018).

    Article  PubMed  Google Scholar 

  100. Singh, J. A. et al. 2015 American College of Rheumatology guideline for the treatment of rheumatoid arthritis. Arthritis Rheumatol. 68, 1–26 (2016).

    PubMed  Google Scholar 

  101. Smolen, J. S. et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Ann. Rheum. Dis https://doi.org/10.1136/annrheumdis-2019-216655 (2020).

    Article  PubMed  Google Scholar 

  102. Detert, J. et al. Induction therapy with adalimumab plus methotrexate for 24 weeks followed by methotrexate monotherapy up to week 48 versus methotrexate therapy alone for DMARD-naive patients with early rheumatoid arthritis: HIT HARD, an investigator-initiated study. Ann. Rheum. Dis. 72, 844–850 (2013).

    Article  CAS  PubMed  Google Scholar 

  103. Hughes, C. D., Scott, D. L. & Ibrahim, F. Titrate Programme Investigators. Intensive therapy and remissions in rheumatoid arthritis: a systematic review. BMC Musculoskelet. Disord. 19, 389 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Smolen, J. S. et al. Adjustment of therapy in rheumatoid arthritis on the basis of achievement of stable low disease activity with adalimumab plus methotrexate or methotrexate alone: the randomised controlled OPTIMA trial. Lancet 383, 321–332 (2014).

    Article  CAS  PubMed  Google Scholar 

  105. Goodman, S. M., Cronstein, B. N. & Bykerk, V. P. Outcomes related to methotrexate dose and route of administration in patients with rheumatoid arthritis: a systematic literature review. Clin. Exp. Rheumatol. 33, 272–278 (2015).

    PubMed  Google Scholar 

  106. Lebbe, C., Beyeler, C., Gerber, N. J. & Reichen, J. Intraindividual variability of the bioavailability of low dose methotrexate after oral administration in rheumatoid arthritis. Ann. Rheum. Dis. 53, 475–477 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. van Roon, E. N. & van de Laar, M. A. Methotrexate bioavailability. Clin. Exp. Rheumatol. 28, S27–32 (2010).

    PubMed  Google Scholar 

  108. Halilova, K. I. et al. Markers of treatment response to methotrexate in rheumatoid arthritis: where do we stand? Int. J. Rheumatol. 2012, 978396 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  109. Angelis-Stoforidis, P., Vajda, F. J. & Christophidis, N. Methotrexate polyglutamate levels in circulating erythrocytes and polymorphs correlate with clinical efficacy in rheumatoid arthritis. Clin. Exp. Rheumatol. 17, 313–320 (1999).

    CAS  PubMed  Google Scholar 

  110. Dervieux, T. et al. Polyglutamation of methotrexate with common polymorphisms in reduced folate carrier, aminoimidazole carboxamide ribonucleotide transformylase, and thymidylate synthase are associated with methotrexate effects in rheumatoid arthritis. Arthritis Rheum. 50, 2766–2774 (2004).

    Article  CAS  PubMed  Google Scholar 

  111. Danila, M. I. et al. Measurement of erythrocyte methotrexate polyglutamate levels: ready for clinical use in rheumatoid arthritis? Curr. Rheumatol. Rep. 12, 342–347 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Stamp, L. K. et al. Methotrexate polyglutamate concentrations are not associated with disease control in rheumatoid arthritis patients receiving long-term methotrexate therapy. Arthritis Rheum. 62, 359–368 (2010).

    Article  CAS  PubMed  Google Scholar 

  113. Hornung, N., Ellingsen, T., Attermann, J., Stengaard-Pedersen, K. & Poulsen, J. H. Patients with rheumatoid arthritis treated with methotrexate (methotrexate): concentrations of steady-state erythrocyte methotrexate correlate to plasma concentrations and clinical efficacy. J. Rheumatol. 35, 1709–1715 (2008).

    CAS  PubMed  Google Scholar 

  114. Bluett, J. et al. Risk factors for oral methotrexate failure in patients with inflammatory polyarthritis: results from a UK prospective cohort study. Arthritis Res. Ther. 20, 50 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  115. Dekkers, J. S. et al. Autoantibody status is not associated with early treatment response to first-line methotrexate in patients with early rheumatoid arthritis. Rheumatology 58, 149–153 (2019).

    Article  CAS  PubMed  Google Scholar 

  116. Hider, S. L. et al. Can clinical factors at presentation be used to predict outcome of treatment with methotrexate in patients with early inflammatory polyarthritis? Ann. Rheum. Dis. 68, 57–62 (2009).

    Article  CAS  PubMed  Google Scholar 

  117. Sergeant, J. C. et al. Prediction of primary non-response to methotrexate therapy using demographic, clinical and psychosocial variables: results from the UK Rheumatoid Arthritis Medication Study (RAMS). Arthritis Res. Ther. 20, 147 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  118. Gupta, V., Katiyar, S., Singh, A., Misra, R. & Aggarwal, A. CD39 positive regulatory T cell frequency as a biomarker of treatment response to methotrexate in rheumatoid arthritis. Int. J. Rheum. Dis. 21, 1548–1556 (2018).

    Article  CAS  PubMed  Google Scholar 

  119. Lopez-Rodriguez, R. et al. Replication study of polymorphisms associated with response to methotrexate in patients with rheumatoid arthritis. Sci. Rep. 8, 7342 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  120. de Rotte, M. et al. Development and validation of a prognostic multivariable model to predict insufficient clinical response to methotrexate in rheumatoid arthritis. PLoS One 13, e0208534 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  121. Plant D. et al. Gene expression profiling identifies classifier of methotrexate non-response in patients with rheumatoid arthritis. Arthritis Rheum. https://doi.org/10.1002/art.40810 (2019).

  122. Wessels, J. A. et al. A clinical pharmacogenetic model to predict the efficacy of methotrexate monotherapy in recent-onset rheumatoid arthritis. Arthritis Rheum. 56, 1765–1775 (2007).

    Article  CAS  PubMed  Google Scholar 

  123. Eektimmerman, F. et al. Validation of a clinical pharmacogenetic model to predict methotrexate nonresponse in rheumatoid arthritis patients. Pharmacogenomics 20, 85–93 (2019).

    Article  CAS  PubMed  Google Scholar 

  124. Jenko, B. et al. Clinical pharmacogenetic models of treatment response to methotrexate monotherapy in Slovenian and Serbian rheumatoid arthritis patients: differences in patient’s management may preclude generalization of the models. Front. Pharmacol. 9, 20 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  125. Lopez-Rodriguez, R. et al. Evaluation of a clinical pharmacogenetics model to predict methotrexate response in patients with rheumatoid arthritis. Pharmacogenomics J. 18, 539–545 (2018).

    Article  CAS  PubMed  Google Scholar 

  126. Zhang, X. et al. The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment. Nat. Med. 21, 895–905 (2015).

    Article  CAS  PubMed  Google Scholar 

  127. Isaac, S. et al. Short- and long-term effects of oral vancomycin on the human intestinal microbiota. J. Antimicrob. Chemother. 72, 128–136 (2017).

    Article  CAS  PubMed  Google Scholar 

  128. Nayak, R. R. et al. Perturbation of the human gut microbiome by a non-antibiotic drug contributes to the resolution of autoimmune disease. bioRxiv https://doi.org/10.1101/600155 (2019).

    Article  Google Scholar 

  129. Isaac, S. et al. The pre-treatment gut microbiome predicts early response to methotrexate in rheumatoid arthritis [abstract]. Arthritis Rheumatol. 71, 2769 (2019).

    Google Scholar 

  130. Costello, S. P. et al. Effect of fecal microbiota transplantation on 8-week remission in patients with ulcerative colitis: a randomized clinical trial. JAMA 321, 156–164 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  131. Paramsothy, S. et al. Multidonor intensive faecal microbiota transplantation for active ulcerative colitis: a randomised placebo-controlled trial. Lancet 389, 1218–1228 (2017).

    Article  PubMed  Google Scholar 

  132. Kragsnaes, M. S. et al. Efficacy and safety of faecal microbiota transplantation in patients with psoriatic arthritis: protocol for a 6-month, double-blind, randomised, placebo-controlled trial. BMJ Open 8, e019231 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  133. Gjorevski, N., Ranga, A. & Lutolf, M. P. Bioengineering approaches to guide stem cell-based organogenesis. Development 141, 1794–1804 (2014).

    Article  CAS  PubMed  Google Scholar 

  134. Trietsch, S. J. et al. Membrane-free culture and real-time barrier integrity assessment of perfused intestinal epithelium tubes. Nat. Commun. 8, 262 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  135. Bhatia, S. N. & Ingber, D. E. Microfluidic organs-on-chips. Nat. Biotechnol. 32, 760–772 (2014).

    Article  CAS  PubMed  Google Scholar 

  136. Lagier, J. C. et al. Culture of previously uncultured members of the human gut microbiota by culturomics. Nat. Microbiol. 1, 16203 (2016).

    Article  CAS  PubMed  Google Scholar 

  137. Maier, L. et al. Extensive impact of non-antibiotic drugs on human gut bacteria. Nature 555, 623–628 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors are supported by the NIH (grants R03AR072182 and R01AR074500 to J.U.S.; R01HL122593 and R01AR074500 to P.J.T.; K08AR073930 to R.N.). J.U.S. is further supported by The Riley Family Foundation, The Beatriz Snyder Foundation, the Rheumatology Research Foundation, the National Psoriasis Foundation and The Judith and Stewart Colton Center for Autoimmunity. P.J.T. is a Chan Zuckerberg Biohub investigator and a Nadia’s Gift Foundation Innovator supported, in part, by the Damon Runyon Cancer Research Foundation (DRR-42-16) and the Searle Scholars Program (SSP-2016-1352). C.U. is supported by MINECO (SAF2017-90083-R).

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All authors researched data for the article and substantially contributed to discussion of content, writing and review/editing of the manuscript before submission.

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Correspondence to Jose U. Scher.

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Competing interests

J.U.S. declares that he has served as a consultant for Amgen, BMS, Janssen, Novartis, Sanofi and UCB, and has received funds from Novartis to NYU School of Medicine to conduct investigator-initiated studies. J.U.S. and S.B.A. have been granted USPTO patent no. 10011883 (“Causative agents and diagnostic methods relating to rheumatoid arthritis”). P.J.T. declares he is on the scientific advisory boards for Kaleido, Seres, SNIPRbiome, uBiome, and WholeBiome; there is no direct overlap between the current article and these consulting duties. R.R.N. and C.U. declare no competing interests.

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Glossary

Pharmacokinetics

The study of how an organism affects a drug, including absorption, distribution, bioavailability, metabolism and excretion.

Pharmacodynamics

The study of the biochemical, physiological and molecular effects of drugs on the body, including receptor binding, post-receptor effects and chemical interactions.

Xenobiotics

Chemical compounds (for example, drugs or pollutants) found within but not produced by living organisms.

Biotransformations

The processes by which a compound (for example, a drug) is transformed from one form to another by a chemical reaction within the body.

Microbial consortia

Two or more microbial groups living symbiotically.

Random forest

A data construct classifier applied to machine learning that develops large numbers of random decision trees that analyse multiple sets of variables.

Operons

Genetic regulatory systems found in bacteria and their viruses in which genes encoding functionally related proteins are clustered along the DNA.

Prebiotic

Non-digestible supplement that induces the growth (and/or activity) of commensal microorganisms.

Probiotic

Supplement containing live microorganisms that can alter the composition of microbiota and are supposed to provide health benefits to the host.

Bacterial culturomics

A method that allows for the description of the microbial composition by high-throughput culture platforms.

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Scher, J.U., Nayak, R.R., Ubeda, C. et al. Pharmacomicrobiomics in inflammatory arthritis: gut microbiome as modulator of therapeutic response. Nat Rev Rheumatol 16, 282–292 (2020). https://doi.org/10.1038/s41584-020-0395-3

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