Abstract

Improving prediction of disease outcome for inflammatory bowel disease: progress through systems medicine

Expert Rev Clin Immunol. 2021 Jun 18. doi: 10.1080/1744666X.2021.1945442.Online ahead of print.

Federica Giachero 1, Andreas Jenke 1 2, Matthias Zilbauer 1 3 4

 
     

Author information

  • 1University of Witten/Herdecke, Germany.
  • 2Children´s Hospital Kassel, Department of Neonatology and Paediatric Gastroenterology, Klinikum Kassel, Germany.
  • 3Department of Paediatrics, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
  • 4Department of Paediatric Gastroenterology, Hepatology and Nutrition, Cambridge, University Hospitals, Addenbrooke's, Cambridge, UK.

Abstract

Introduction: - Inflammatory bowel diseases (IBDs) are lifelong conditions causing relapsing inflammation of the intestine. In the absence of a cure, clinical management of IBDs is extremely challenging since they present with a wide range of phenotypes and disease behaviors. Hence, there is an urgent need for markers that could guide physicians in making the right choice of the rapidly growing treatment options towards a personalized care that could improve the overall outcome.

Areas covered: - In this review, the authors summarize existing biomarkers in IBD, discuss the challenges with the development of prognostic biomarkers and propose alternative options such as focusing on the prediction of the response to individual treatments, i.e. predictive biomarkers. The problems related to developing disease prognostic and predictive biomarkers in the field of IBDs are discussed including the difficulties in dealing with phenotypic heterogeneity particularly when performing studies in a real-life setting. The authors reviewed literature from PubMed.

Expert opinion: - Systems biology provides potential solutions to this problem by offering an unbiased, holistic approach to adjusting for variation in larger datasets thereby increasing the chances of identifying true associations between molecular profiles and clinical phenotypes.

 

 

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