Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel disease
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Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel disease

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Details:

  • Alternative Title:
    Genome Med
  • Personal Author:
  • Description:
    Background

    Gut microbiome dysbiosis has been demonstrated in subjects with newly diagnosed and chronic inflammatory bowel disease (IBD). In this study we sought to explore longitudinal changes in dysbiosis and ascertain associations between dysbiosis and markers of disease activity and treatment outcome.

    Methods

    We performed a prospective cohort study of 19 treatment-naïve pediatric IBD subjects and 10 healthy controls, measuring fecal calprotectin and assessing the gut microbiome via repeated stool samples. Associations between clinical characteristics and the microbiome were tested using generalized estimating equations. Random forest classification was used to predict ultimate treatment response (presence of mucosal healing at follow-up colonoscopy) or non-response using patients’ pretreatment samples.

    Results

    Patients with Crohn’s disease had increased markers of inflammation and dysbiosis compared to controls. Patients with ulcerative colitis had even higher inflammation and dysbiosis compared to those with Crohn’s disease. For all cases, the gut microbial dysbiosis index associated significantly with clinical and biological measures of disease severity, but did not associate with treatment response. We found differences in specific gut microbiome genera between cases/controls and responders/non-responders including Akkermansia, Coprococcus, Fusobacterium, Veillonella, Faecalibacterium, and Adlercreutzia. Using pretreatment microbiome data in a weighted random forest classifier, we were able to obtain 76.5 % accuracy for prediction of responder status.

    Conclusions

    Patient dysbiosis improved over time but persisted even among those who responded to treatment and achieved mucosal healing. Although dysbiosis index was not significantly different between responders and non-responders, we found specific genus-level differences. We found that pretreatment microbiome signatures are a promising avenue for prediction of remission and response to treatment.

    Electronic supplementary material

    The online version of this article (doi:10.1186/s13073-016-0331-y) contains supplementary material, which is available to authorized users.

  • Subjects:
  • Source:
    Genome Med. 8.
  • Pubmed ID:
    27412252
  • Pubmed Central ID:
    PMC4944441
  • Document Type:
    Journal Article
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Datasets

    • Additional file 3: of Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel disease
      Dataset Icon
      Cite
      Filetype[HTM]
      2016 | NCCDPHP
      12/14/2016
      Description:
      De novo and rarefy analysis. Contains a table that compares results from the generalized estimating equation (GEE) analysis performed in the paper (us...
      File Type:
      Filetype[HTM]
      File Type:
      Filetype[HTM]
      Additional file 1: of Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel disease
      Dataset Icon
      Cite
      Filetype[HTM]
      Personal Author:
      Bertha, Madeline ;
      Chopra, Pankaj
      ...
      2016 | NCCDPHP
      12/14/2016
      Description:
      Microbiome samples sequencing and analysis summary. Contains a table that summarizes total reads, reads passing QC, and reads successfully classified ...
      File Type:
      Filetype[HTM]
      File Type:
      Filetype[HTM]
      Additional file 1: of Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel disease
      Dataset Icon
      Cite
      Filetype[HTM]
      Personal Author:
      Bertha, Madeline ;
      Chopra, Pankaj
      ...
      2016 | NCCDPHP
      12/14/2016
      Description:
      Microbiome samples sequencing and analysis summary. Contains a table that summarizes total reads, reads passing QC, and reads successfully classified ...
      File Type:
      Filetype[HTM]
      File Type:
      Filetype[HTM]

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