Cargando…

Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease

The role of intestinal bacterial microbiota has been described as key in the pathophysiology of Crohn’s disease (CD). CD is characterized by frequent relapses after periods of remission which are not entirely understood. In this paper, we investigate whether the heterogeneity in microbiota profiles...

Descripción completa

Detalles Bibliográficos
Autores principales: Buffet-Bataillon, Sylvie, Bouguen, Guillaume, Fleury, François, Cattoir, Vincent, Le Cunff, Yann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9675750/
https://www.ncbi.nlm.nih.gov/pubmed/36402792
http://dx.doi.org/10.1038/s41598-022-23757-x
_version_ 1784833437768613888
author Buffet-Bataillon, Sylvie
Bouguen, Guillaume
Fleury, François
Cattoir, Vincent
Le Cunff, Yann
author_facet Buffet-Bataillon, Sylvie
Bouguen, Guillaume
Fleury, François
Cattoir, Vincent
Le Cunff, Yann
author_sort Buffet-Bataillon, Sylvie
collection PubMed
description The role of intestinal bacterial microbiota has been described as key in the pathophysiology of Crohn’s disease (CD). CD is characterized by frequent relapses after periods of remission which are not entirely understood. In this paper, we investigate whether the heterogeneity in microbiota profiles in CD patients could be a suitable predictor for these relapses. This prospective observational study involved 259 CD patients, in which 41 provided an additional total of 62 consecutive fecal samples, with an average interval of 25 weeks in between each of these samples. Fecal microbiota was analyzed by massive genomic sequencing through 16 S rRNA amplicon sampling. We found that our 259 CD patients could be split into three distinct subgroups of microbiota (G1, G2, G3). From G1 to G3, we noticed a progressive decrease in alpha diversity (p ≤ 0.0001) but no change in the fecal calprotectin (FC) level. Focusing on the 103 consecutive samples from 41 CD patients, we showed that the patients microbiota profiles were remarkably stable over time and associated with increasing symptom severity. Investigating further this microbiota/severity association revealed that the first signs of aggravation are (1) a loss of the main anti-inflammatory Short-Chain Fatty Acids (SCFAs) Roseburia, Eubacterium, Subdoligranumum, Ruminococcus (P < 0.05), (2) an increase in pro-inflammatory pathogens Proteus, Finegoldia (P < 0.05) while (3) an increase of other minor SCFA producers such as Ezakiella, Anaerococcus, Megasphaera, Anaeroglobus, Fenollaria (P < 0.05). Further aggravation of clinical signs is significantly linked to the subsequent loss of these minor SCFAs species and to an increase in other proinflammatory Proteobacteria such as Klebsiella, Pseudomonas, Salmonella, Acinetobacter, Hafnia and proinflammatory Firmicutes such as Staphylococcus, Enterococcus, Streptococcus. (P < 0.05). To our knowledge, this is the first study (1) specifically identifying subgroups of microbiota profiles in CD patients, (2) relating these groups to the evolution of symptoms over time and (3) showing a two-step process in CD symptoms’ worsening. This paves the way towards a better understanding of patient-to-patient heterogeneity, as well as providing early warning signals of future aggravation of the symptoms and eventually adapting empirically treatments.
format Online
Article
Text
id pubmed-9675750
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-96757502022-11-21 Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease Buffet-Bataillon, Sylvie Bouguen, Guillaume Fleury, François Cattoir, Vincent Le Cunff, Yann Sci Rep Article The role of intestinal bacterial microbiota has been described as key in the pathophysiology of Crohn’s disease (CD). CD is characterized by frequent relapses after periods of remission which are not entirely understood. In this paper, we investigate whether the heterogeneity in microbiota profiles in CD patients could be a suitable predictor for these relapses. This prospective observational study involved 259 CD patients, in which 41 provided an additional total of 62 consecutive fecal samples, with an average interval of 25 weeks in between each of these samples. Fecal microbiota was analyzed by massive genomic sequencing through 16 S rRNA amplicon sampling. We found that our 259 CD patients could be split into three distinct subgroups of microbiota (G1, G2, G3). From G1 to G3, we noticed a progressive decrease in alpha diversity (p ≤ 0.0001) but no change in the fecal calprotectin (FC) level. Focusing on the 103 consecutive samples from 41 CD patients, we showed that the patients microbiota profiles were remarkably stable over time and associated with increasing symptom severity. Investigating further this microbiota/severity association revealed that the first signs of aggravation are (1) a loss of the main anti-inflammatory Short-Chain Fatty Acids (SCFAs) Roseburia, Eubacterium, Subdoligranumum, Ruminococcus (P < 0.05), (2) an increase in pro-inflammatory pathogens Proteus, Finegoldia (P < 0.05) while (3) an increase of other minor SCFA producers such as Ezakiella, Anaerococcus, Megasphaera, Anaeroglobus, Fenollaria (P < 0.05). Further aggravation of clinical signs is significantly linked to the subsequent loss of these minor SCFAs species and to an increase in other proinflammatory Proteobacteria such as Klebsiella, Pseudomonas, Salmonella, Acinetobacter, Hafnia and proinflammatory Firmicutes such as Staphylococcus, Enterococcus, Streptococcus. (P < 0.05). To our knowledge, this is the first study (1) specifically identifying subgroups of microbiota profiles in CD patients, (2) relating these groups to the evolution of symptoms over time and (3) showing a two-step process in CD symptoms’ worsening. This paves the way towards a better understanding of patient-to-patient heterogeneity, as well as providing early warning signals of future aggravation of the symptoms and eventually adapting empirically treatments. Nature Publishing Group UK 2022-11-19 /pmc/articles/PMC9675750/ /pubmed/36402792 http://dx.doi.org/10.1038/s41598-022-23757-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Buffet-Bataillon, Sylvie
Bouguen, Guillaume
Fleury, François
Cattoir, Vincent
Le Cunff, Yann
Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease
title Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease
title_full Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease
title_fullStr Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease
title_full_unstemmed Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease
title_short Gut microbiota analysis for prediction of clinical relapse in Crohn’s disease
title_sort gut microbiota analysis for prediction of clinical relapse in crohn’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9675750/
https://www.ncbi.nlm.nih.gov/pubmed/36402792
http://dx.doi.org/10.1038/s41598-022-23757-x
work_keys_str_mv AT buffetbataillonsylvie gutmicrobiotaanalysisforpredictionofclinicalrelapseincrohnsdisease
AT bouguenguillaume gutmicrobiotaanalysisforpredictionofclinicalrelapseincrohnsdisease
AT fleuryfrancois gutmicrobiotaanalysisforpredictionofclinicalrelapseincrohnsdisease
AT cattoirvincent gutmicrobiotaanalysisforpredictionofclinicalrelapseincrohnsdisease
AT lecunffyann gutmicrobiotaanalysisforpredictionofclinicalrelapseincrohnsdisease