Personalised medicine in IBD

Behrooz Alizadeh, EpiCom Member

Behrooz Alizadeh 

Inflammatory Bowel Disease (IBD) is a chronic relapsing and remitting disease of the gut. IBD has a lifelong adverse impact on quality of life and imposes a significant burden on health care [1, 2]. The pathogenesis and course of IBD involve pathogenomic crosstalk among several complex internal components [3, 4], namely the genome [5], epigenome [3, 4], metabolome [3, 4, 6], immunome and microbiome [6–9]; this crosstalk is generally triggered through a set of external complex interactions among the exposome [10–13], dietome [14, 15], lifestyle, social and behavioural factors [16]. While some of these multi-level interactions trigger the disease, others drive the disease course. Therefore, in each IBD patient the disease arises through a (unique) combination of pathogenenomic (risk) factors or pathway that yield a specific set of disease manifestations and a specific disease course. In this context, an “individualized” therapy is required [17–19].

The current “one size fits all” accelerated approaches entail the use of a combination of pharmacological immunomodulatory therapies such as biologics (mAbs) and immunosuppressants, dietary modifications (anti-inflammatory diet, vitamins), lifestyle adjustments (smoking, sporting activity and high-risk jobs) and management of psychological distress (stress management) [18, 20]. These modalities are evidenced based, but they are approved on the basis of the “group-level” patients response, whereas unique pathogenomic pathways arerelevant only at the individual level. Furthermore, the “one size fits all” approaches exclude monitoring of patients outside of clinics, whereas in fact patients are constantly exposed to an extensive number of factors in the community that modify their risk with regard to disease course and adherence to interventions. Frankly, the caregivers receive few clues to what is going on ”outside”. 

While multidisciplinary approaches have been gaining attention in IBD clinics because it is claimed that they can deliver individualised care and efficacious management, improve quality of life and reduce disease burden, in reality “one size fits all” guidelines are still applied by these multidisciplinary approaches. Therefore, It is not surprising that “one size fits all” approaches are only partially effective and that the outcome remains unfavourable in many patients. Put simply, the treatment does not fully match the underlying disease mechanism in any given patient even in multidisciplinary managment. Patients continue to experience debilitating symptoms, such as general pain, fatigue, bloody diarrhoea and cachexia, with deteriorating health and well-being. Moreover, this deterioration is accompanied by long-term complications such as fistulas, bowel stenosis, bowel obstructions, perforations, arthropathies, skin erythema, gangrenous dermatitis, neuropsychological distress, colon cancer, surgical resections, social exclusion, job loss, etc. and, ultimately, early mortality. Given the lifelong complications, the side effects of long-term immunosuppressive treatment, the increasing cost of medications and the increasing disease burden on health care, effective disease management in IBD is an urgent necessity [1, 18, 21].

Against this background, the role of personalised medicine (PM) in the treatment of IBD has recently attracted much attention [18, 22, 23]. PM may be defined as, “Tailoring of medical treatment to the individual characteristics of each patient to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment” [24]. Generally, PM uses comprehensive pathogenically relevant information to prevent, diagnose and treat IBD through the provision of optimal medical care which is customised to meet the needs of each patient [24]. In this context, multidisciplinary multicentre initiatives are being developed to integrate multi-layer multi-omics and multi-level live data obtained from continuous monitoring of each IBD patient [4, 25, 26]; By using a so-called system biological approach that is boosted by rapidly expanding network platforms [4, 19, 29–31].  It is now feasible to integrate patient’s (i.) multi-omics-biomedical-clinical data into the currently available analytical platforms [3, 4, 19, 26–28] along with (ii.) data obtained from monitoring systems (i.e. telemedicine and patient-reported outcomes) and (iii.) patient’s hospital records (i.e. EPIC) [4, 19, 25]. Statistical modules and machine learning algorithms are in place which infer, visualize, and present the results  into a set of meaningful clinical indicators of IBD rerponse for treating physicians. Sooner rather than later, these complex analyses are expected to result in a detailed understanding of the biological, environmental and societal factors and their interactions that exert a significant impact on the disease course and outcomes. These data will assist in accurate differentiation of patients from each other and in matching each patient to a specific underlying disease cause (i.e. risk stratification) and disease course (i.e. personalised prognosis). Treating physicians should be able to distinguish promptly the patient who is at risk of severe disease progression and thus start with top-down modalities (combination therapies with the appropriate dosing); on the other hand, in those who are identified as being at low risk of a severe disease course, an “accelerated step-up approach” treatment strategy can be adopted, with modest interventions and no or limited lifestyle modifications. In addition, doctors will be able to select the type of medicine and lifestyle modifications which are the most effective for particular patient (e.g. adjustment of the dose of azathioprine in carriers of mutations in the TPMT gene).

The implementation of PM is a continuous process. It has the aim of delivering and optimizing the right treatment to the right target at the right moment. It is based on the “multi-omics individual approach”. Alongside PM integrates medical monitoring information (such as the results of therapeutic drug monitoring, biomarker measurements, and clinical, radiological, endoscopic and histological investigations) with social and behavioural components (such as work satisfaction, social inclusion and personal lifestyle) which are monitored using digital health technologies, including telemedicine. For example, MyIBDcoach is a patient-centred application which offers the possibility of a multidisciplinary approach. It is a validated telemedicine tool for the safe monitoring of IBD disease activity [32, 33] – enables baseline and clinical data collection, therapeutic drug monitoring, and lifestyle and behavioural management. It is connected to hospital records and interlinked with genomics [33, 34] and (in subsamples) multi-omics data [35].

In conclusion, PM is still under development and a fuller understanding of pathogenically relevant factors is still required. I consider that the concept of PM, and its implementation, extends beyond simply choosing the best-fit drug for a particular patient. PM is a health care process that aims to replace less effective, costly and lengthy traditional disease management strategies with more effective and efficient ones, eventually reducing the burden on the health care system. PM includes patient-tailored care, but it also demands and will lead to changes in medical guidelines and health care processes. Implementation of PM will extend itself from the monitoring and management of care in clinics to modifications of patients’ daily activities at home, at work and in the community. As we are currently observing through the MyIBDcoach initiative, PM can bridge the gap between the molcular biology, clinic and society. However, it remains to be seen whether PM will deliver on its promises.  


  1. Ananthakrishnan AN, Kaplan GG, Ng SC. Changing global epidemiology of inflammatory bowel diseases: Sustaining health care delivery into the 21st century. Clin Gastroenterol Hepatol. 2020;18:1252–60.
  2. Cosnes J, Gower-Rousseau C, Seksik P, Cortot A. Epidemiology and natural history of inflammatory bowel diseases. Gastroenterology. 2011;140:1785–94.
  3. de Souza HSP, Fiocchi C, Iliopoulos D. The IBD interactome: An integrated view of aetiology, pathogenesis and therapy. Nat Rev Gastroenterol Hepatol. 2017;14:739–49.
  4. Fiocchi C. Integrating omics: The future of IBD? Dig Dis. 2014;32 Suppl 1:96–102.
  5. Liu JZ, van Sommeren S, Huang H, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015;47:979–86.
  6. Franzosa EA, Sirota-Madi A, Avila-Pacheco J, et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat Microbiol. 2019;4:293–305.
  7. Collij V, Klaassen MAY, Weersma RK, Vila AV. Gut microbiota in inflammatory bowel diseases: Moving from basic science to clinical applications. Hum Genet. 2020 Aug 28. doi: 10.1007/s00439-020-02218-3. Online ahead of print.
  8. Imhann F, Vich Vila A, Bonder MJ, et al. Interplay of host genetics and gut microbiota underlying the onset and clinical presentation of inflammatory bowel disease. Gut. 2018;67:108–19.
  9. Ruigrok RAAA, Collij V, Sureda P, et al. The composition and metabolic potential of the human small intestinal microbiota within the context of inflammatory bowel disease. J Crohns Colitis. 2021 Jan 30 doi: 10.1093/ecco-jcc/jjab020.Online ahead of print.
  10. van den Heuvel TRA, Jeuring SFG, Zeegers MP, et al. A 20-year temporal change analysis in incidence, presenting phenotype and mortality, in the Dutch IBDSL cohort – can diagnostic factors explain the increase in IBD incidence? J Crohns Colitis. 2017;11:1169–79.
  11. van der Sloot KWJ, Geertsema P, Rijkmans HC, et al. Environmental factors associated with biological use and surgery in inflammatory bowel disease. J Gastroenterol Hepatol. 2020 Aug 24. doi: 10.1111/jgh.15223.Online ahead of print.
  12. van der Sloot KWJ, Weersma RK, Alizadeh BZ, Dijkstra G. Identification of environmental risk factors associated with the development of inflammatory bowel disease. J Crohns Colitis. 2020 Jun 23. doi: 10.1093/ecco-jcc/jjaa114.Online ahead of print.
  13. van der Sloot KWJ, Amini M, Peters V, Dijkstra G, Alizadeh BZ. Inflammatory bowel diseases: Review of known environmental protective and risk factors involved. Inflamm Bowel Dis. 2017;23:1499–509.
  14. Peters V, Spooren C, Pierik M, et al. Dietary intake pattern is associated with occurrence of flares in IBD patients. J Crohns Colitis. 2021 Jan 13. doi: 10.1093/ecco-jcc/jjab008.Online ahead of print.
  15. Ghosh TS, Rampelli S, Jeffery IB, et al. Mediterranean diet intervention alters the gut microbiome in older people reducing frailty and improving health status: The NU-AGE 1-year dietary intervention across five european countries. Gut. 2020;69:1218–28.
  16. Torres J, Ellul P, Langhorst J, et al. European Crohn's and Colitis Organisation topical review on complementary medicine and psychotherapy in inflammatory bowel disease. J Crohns Colitis. 2019;13:673–85e.
  17. Bangma A, Voskuil MD, Uniken Venema WTC, et al. Predicted efficacy of a pharmacogenetic passport for inflammatory bowel disease. Aliment Pharmacol Ther. 2020;51:1105–15.
  18. Colombel JF, Narula N, Peyrin-Biroulet L. Management strategies to improve outcomes of patients with inflammatory bowel diseases. Gastroenterology. 2017;152:351–361.e5.
  19. Fiocchi C, Iliopoulos D. What's new in IBD therapy: An "omics network" approach. Pharmacol Res. 2020;159:104886.
  20. Martins R, Carmona C, George B, Epstein J, Guideline Committee. Management of Crohn's disease: Summary of updated NICE guidance. BMJ. 2019;367:l5940.
  21. Torres J, Bonovas S, Doherty G, et al. ECCO guidelines on therapeutics in Crohn's disease: Medical treatment. J Crohns Colitis. 2020;14:4–22.
  22. Torres J, Halfvarson J, Rodriguez-Lago I, et al. Results of the Seventh Scientific Workshop of ECCO: Precision medicine in IBD – prediction and prevention of inflammatory bowel disease. J Crohns Colitis. 2021 Mar 17. doi: 10.1093/ecco-jcc/jjab048.Online ahead of print.
  23. Fiocchi C, Dragoni G, Iliopoulos D, et al. Results of the Seventh Scientific Workshop of ECCO: Precision medicine in IBD – what, why, and how. J Crohns Colitis. 2021 Mar 18. doi: 10.1093/ecco-jcc/jjab051.Online ahead of print.
  24. National Research Council (US) Committee on A Framework for Developing a New Taxonomy of Disease. 2011.
  25. Yadav A, Vidal M, Luck K. Precision medicine – networks to the rescue. Curr Opin Biotechnol. 2020;63:177–89.
  26. Heida A, Dijkstra A, Muller Kobold A, et al. Efficacy of home telemonitoring versus conventional follow-up: A randomized controlled trial among teenagers with inflammatory bowel disease. J Crohns Colitis. 2018;12:432–41.
  27. Doestzada M, Vila AV, Zhernakova A, et al. Pharmacomicrobiomics: A novel route towards personalised medicine? Protein Cell. 2018;9:432–45.
  28. Lynch SV, Ng SC, Shanahan F, Tilg H. Translating the gut microbiome: Ready for the clinic? Nat Rev Gastroenterol Hepatol. 2019;16:656–61.
  29. Cheng F, Kovacs IA, Barabasi AL. Network-based prediction of drug combinations. Nat Commun. 2019;10:1197-019-09186-x.
  30. Loscalzo J. Systems biology and personalised medicine: A network approach to human disease. Proc Am Thorac Soc. 2011;8:196–8.
  31. Chen R, Snyder M. Systems biology: Personalised medicine for the future? Curr Opin Pharmacol. 2012;12:623–8.
  32. de Jong M, van der Meulen-de Jong A, Romberg-Camps M, et al. Development and feasibility study of a telemedicine tool for all patients with IBD: MyIBDcoach. Inflamm Bowel Dis. 2017;23:485–93.
  33. de Jong MJ, van der Meulen-de Jong AE, Romberg-Camps MJ, et al. Telemedicine for management of inflammatory bowel disease (myIBDcoach): A pragmatic, multicentre, randomised controlled trial. Lancet. 2017;390(10098):959–68.
  34. Spekhorst LM, Imhann F, Festen EAM, et al. Cohort profile: Design and first results of the dutch IBD biobank: A prospective, nationwide biobank of patients with inflammatory bowel disease. BMJ Open. 2017;7:e016695-2017-016695.
  35. Imhann F, Van der Velde KJ, Barbieri R, et al. The 1000IBD project: Multi-omics data of 1000 inflammatory bowel disease patients; data release 1. BMC Gastroenterol. 2019;19:5-018-0917-5.



Posted in ECCO News, Committee News, EpiCom, Volume 16, Issue 2