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

Kuvaus

Abstract 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.
Näytä enemmän

Julkaisuvuosi

2016

Aineiston tyyppi

Tekijät

Department of Computer Science

Abhiram Srivatsa - Muu tekijä

Aleksandar D. Kostic - Muu tekijä

Archana Kumar - Muu tekijä

Cary Sauer - Muu tekijä

Glen A. Satten - Muu tekijä

Jarod Prince - Muu tekijä

Jennifer G. Mulle - Muu tekijä

Kelly A. Shaw - Muu tekijä

Madeline Bertha - Muu tekijä

Michael E. Zwick - Muu tekijä

Pankaj Chopra - Muu tekijä

Ramnik J. Xavier - Muu tekijä

Subra Kugathasan - Muu tekijä

Tatyana Hofmekler - Muu tekijä

Tommi Vatanen - Tekijä

Centers for Disease Control and Prevention - Muu tekijä

Children's Healthcare of Atlanta - Muu tekijä

Emory University - Muu tekijä

Harvard University - Muu tekijä

Massachusetts General Hospital - Muu tekijä

Xavier Lab in the Broad Institute - Muu tekijä

figshare - Julkaisija

Projekti

Muut tiedot

Tieteenalat

Tietojenkäsittely ja informaatiotieteet

Kieli

Saatavuus

Avoin

Lisenssi

Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)

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Asiasanat

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