Treatment-Specific Composition of the Gut Microbiota Is Associated With Disease Remission in a Pediatric Crohn's Disease Cohort.
Adolescent
Anti-Bacterial Agents
/ therapeutic use
Azithromycin
/ therapeutic use
Child
Child, Preschool
Crohn Disease
/ drug therapy
Drug Therapy, Combination
Female
Gastrointestinal Microbiome
/ drug effects
Humans
Male
Metronidazole
/ therapeutic use
RNA, Ribosomal, 16S
/ analysis
Remission Induction
Treatment Outcome
antibiotics
disease remission
microbiota
pediatric Crohn’s disease
random forest model
Journal
Inflammatory bowel diseases
ISSN: 1536-4844
Titre abrégé: Inflamm Bowel Dis
Pays: England
ID NLM: 9508162
Informations de publication
Date de publication:
14 11 2019
14 11 2019
Historique:
received:
03
03
2019
pubmed:
6
7
2019
medline:
25
6
2020
entrez:
6
7
2019
Statut:
ppublish
Résumé
The beneficial effects of antibiotics in Crohn's disease (CD) depend in part on the gut microbiota but are inadequately understood. We investigated the impact of metronidazole (MET) and metronidazole plus azithromycin (MET+AZ) on the microbiota in pediatric CD and the use of microbiota features as classifiers or predictors of disease remission. 16S rRNA-based microbiota profiling was performed on stool samples from 67 patients in a multinational, randomized, controlled, longitudinal, 12-week trial of MET vs MET+AZ in children with mild to moderate CD. Profiles were analyzed together with disease activity, and then used to construct random forest models to classify remission or predict treatment response. Both MET and MET+AZ significantly decreased diversity of the microbiota and caused large treatment-specific shifts in microbiota structure at week 4. Disease remission was associated with a treatment-specific microbiota configuration. Random forest models constructed from microbiota profiles before and during antibiotic treatment with metronidazole accurately classified disease remission in this treatment group (area under the curve [AUC], 0.879; 95% confidence interval, 0.683-0.9877; sensitivity, 0.7778; specificity, 1.000; P < 0.001). A random forest model trained on pre-antibiotic microbiota profiles predicted disease remission at week 4 with modest accuracy (AUC, 0.8; P = 0.24). MET and MET+AZ antibiotic regimens in pediatric CD lead to distinct gut microbiota structures at remission. It may be possible to classify and predict remission based in part on microbiota profiles, but larger cohorts will be needed to realize this goal.
Sections du résumé
BACKGROUND
The beneficial effects of antibiotics in Crohn's disease (CD) depend in part on the gut microbiota but are inadequately understood. We investigated the impact of metronidazole (MET) and metronidazole plus azithromycin (MET+AZ) on the microbiota in pediatric CD and the use of microbiota features as classifiers or predictors of disease remission.
METHODS
16S rRNA-based microbiota profiling was performed on stool samples from 67 patients in a multinational, randomized, controlled, longitudinal, 12-week trial of MET vs MET+AZ in children with mild to moderate CD. Profiles were analyzed together with disease activity, and then used to construct random forest models to classify remission or predict treatment response.
RESULTS
Both MET and MET+AZ significantly decreased diversity of the microbiota and caused large treatment-specific shifts in microbiota structure at week 4. Disease remission was associated with a treatment-specific microbiota configuration. Random forest models constructed from microbiota profiles before and during antibiotic treatment with metronidazole accurately classified disease remission in this treatment group (area under the curve [AUC], 0.879; 95% confidence interval, 0.683-0.9877; sensitivity, 0.7778; specificity, 1.000; P < 0.001). A random forest model trained on pre-antibiotic microbiota profiles predicted disease remission at week 4 with modest accuracy (AUC, 0.8; P = 0.24).
CONCLUSIONS
MET and MET+AZ antibiotic regimens in pediatric CD lead to distinct gut microbiota structures at remission. It may be possible to classify and predict remission based in part on microbiota profiles, but larger cohorts will be needed to realize this goal.
Identifiants
pubmed: 31276165
pii: 5528593
doi: 10.1093/ibd/izz130
pmc: PMC7185687
doi:
Substances chimiques
Anti-Bacterial Agents
0
RNA, Ribosomal, 16S
0
Metronidazole
140QMO216E
Azithromycin
83905-01-5
Types de publication
Journal Article
Multicenter Study
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
1927-1938Subventions
Organisme : NIDDK NIH HHS
ID : P30 DK034854
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007276
Pays : United States
Informations de copyright
Published by Oxford University Press on behalf of Crohn’s & Colitis Foundation 2019.
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