Abstract

Irritable bowel syndrome and microbiome; Switching from conventional diagnosis and therapies to personalized interventions

J Transl Med. 2022 Apr 11;20(1):173. doi: 10.1186/s12967-022-03365-z.

 

Pouyan Ghaffari 1 2Saeed Shoaie 3 4Lars K Nielsen 5 6

 
     

Author information

1Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2970, Hørsholm, Denmark.

2Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, SE1 9RT, UK.

3Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, SE1 9RT, UK. saeed.shoaie@kcl.ac.uk.

4Science for Life Laboratory, KTH - Royal Institute of Technology, 171 21, Stockholm, Sweden. saeed.shoaie@kcl.ac.uk.

5Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2970, Hørsholm, Denmark. lars.nielsen@uq.edu.au.

6Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, St. Lucia, 4072, Australia. lars.nielsen@uq.edu.au.

Abstract

The human microbiome has been linked to several diseases. Gastrointestinal diseases are still one of the most prominent area of study in host-microbiome interactions however the underlying microbial mechanisms in these disorders are not fully established. Irritable bowel syndrome (IBS) remains as one of the prominent disorders with significant changes in the gut microbiome composition and without definitive treatment. IBS has a severe impact on socio-economic and patient's lifestyle. The association studies between the IBS and microbiome have shed a light on relevance of microbial composition, and hence microbiome-based trials were designed. However, there are no clear evidence of potential treatment for IBS. This review summarizes the epidemiology and socioeconomic impact of IBS and then focus on microbiome observational and clinical trials. At the end, we propose a new perspective on using data-driven approach and applying computational modelling and machine learning to design microbiome-aware personalized treatment for IBS.

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