RAID Prediction: Pilot Study of Fecal Microbial Signature With Capacity to Predict Response to Anti-TNF Treatment.


Journal

Inflammatory bowel diseases
ISSN: 1536-4844
Titre abrégé: Inflamm Bowel Dis
Pays: England
ID NLM: 9508162

Informations de publication

Date de publication:
15 11 2021
Historique:
received: 28 09 2021
entrez: 18 11 2021
pubmed: 19 11 2021
medline: 15 12 2021
Statut: ppublish

Résumé

Crohn's disease and ulcerative colitis evolve with alternate outbreaks and remissions of variable duration in both cases. Despite the advances, about 10-30% of patients do not respond to the treatment after the induction period. Besides, between 20% to 50% further patients need an optimization of the dose to respond the treatment. Recent studies have pointed gut microbiota can play a role in the anti-TNF treatment response. This study aimed to define a bacterial signature that could be used to predict the response of patients to anti-TNF treatment. There were obtained 38 stool samples from 38 IBD patients before starting anti-TNF treatments: Adalimumab, Golimumab or Infliximab. Patients were differentiated in 2 groups: responders and non-responders to biological treatment. From each sample, DNA was purified and used in a qPCR for the quantification of the 8 microbial markers. In this proof of concept, the predictive ability to identify anti-TNF treatment responders was analyzed. An algorithm consisting in the combination of 4 bacterial markers showed a high capacity to discriminate between responders and non- responders. The algorithm proved high sensitivity and specificity reporting values of 93.33% and 100% respectively, with a positive predictive value of 100% and a negative predictive value of 75% for predicting response to biologic treatment. A specific bacterial signature could beneficiate patients with inflammatory bowel disease predicting the therapeutic effectiveness of an anti-TNF treatment, leading to a personalized therapy, improving the patients' quality of life, saving costs and gaining time in patient improvement. This study aimed to define a microbial signature that could be used to predict the response of patients to anti-TNF treatment in inflammatory bowel disease. An algorithm consisting in the combination of 4 bacterial markers showed a high capacity to discriminate between responders and nonresponders.

Sections du résumé

BACKGROUND AND AIMS
Crohn's disease and ulcerative colitis evolve with alternate outbreaks and remissions of variable duration in both cases. Despite the advances, about 10-30% of patients do not respond to the treatment after the induction period. Besides, between 20% to 50% further patients need an optimization of the dose to respond the treatment. Recent studies have pointed gut microbiota can play a role in the anti-TNF treatment response. This study aimed to define a bacterial signature that could be used to predict the response of patients to anti-TNF treatment.
METHODS
There were obtained 38 stool samples from 38 IBD patients before starting anti-TNF treatments: Adalimumab, Golimumab or Infliximab. Patients were differentiated in 2 groups: responders and non-responders to biological treatment. From each sample, DNA was purified and used in a qPCR for the quantification of the 8 microbial markers.
RESULTS
In this proof of concept, the predictive ability to identify anti-TNF treatment responders was analyzed. An algorithm consisting in the combination of 4 bacterial markers showed a high capacity to discriminate between responders and non- responders. The algorithm proved high sensitivity and specificity reporting values of 93.33% and 100% respectively, with a positive predictive value of 100% and a negative predictive value of 75% for predicting response to biologic treatment.
CONCLUSIONS
A specific bacterial signature could beneficiate patients with inflammatory bowel disease predicting the therapeutic effectiveness of an anti-TNF treatment, leading to a personalized therapy, improving the patients' quality of life, saving costs and gaining time in patient improvement.
This study aimed to define a microbial signature that could be used to predict the response of patients to anti-TNF treatment in inflammatory bowel disease. An algorithm consisting in the combination of 4 bacterial markers showed a high capacity to discriminate between responders and nonresponders.

Autres résumés

Type: plain-language-summary (eng)
This study aimed to define a microbial signature that could be used to predict the response of patients to anti-TNF treatment in inflammatory bowel disease. An algorithm consisting in the combination of 4 bacterial markers showed a high capacity to discriminate between responders and nonresponders.

Identifiants

pubmed: 34791288
pii: 6428471
doi: 10.1093/ibd/izab273
doi:

Substances chimiques

Biomarkers 0
Tumor Necrosis Factor Inhibitors 0
Tumor Necrosis Factor-alpha 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

S63-S66

Informations de copyright

© 2021 Crohn’s & Colitis Foundation. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

David Busquets (D)

Servei Aparell Digestiu Hospital Universitari Dr. Josep Trueta, Girona, Spain.

Lia Oliver (L)

GoodGut S.L, Girona, Catalonia, Spain.

Joan Amoedo (J)

GoodGut S.L, Girona, Catalonia, Spain.

Sara Ramió-Pujol (S)

GoodGut S.L, Girona, Catalonia, Spain.

Marta Malagón (M)

GoodGut S.L, Girona, Catalonia, Spain.

Marta Serrano (M)

GoodGut S.L, Girona, Catalonia, Spain.

Anna Bahí (A)

Institut d'Investigació Biomèdica de Girona (IdIBGi), Girona, Catalonia, Spain.

Montse Capdevila (M)

Institut d'Investigació Biomèdica de Girona (IdIBGi), Girona, Catalonia, Spain.

Aleix Lluansí (A)

Institut d'Investigació Biomèdica de Girona (IdIBGi), Girona, Catalonia, Spain.

Leyanira Torrealba (L)

Servei Aparell Digestiu Hospital Universitari Dr. Josep Trueta, Girona, Spain.

Laia Peries (L)

Servei Aparell Digestiu Hospital Universitari Dr. Josep Trueta, Girona, Spain.

Rosa Chavero (R)

Servei Aparell Digestiu Hospital Universitari Dr. Josep Trueta, Girona, Spain.

Pau Gilabert (P)

Servei Aparell Digestiu Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Spain.

Miriam Sàbat (M)

Hospital de Santa Caterina, Girona, Catalonia, Spain.

Jordi Guardiola (J)

Servei Aparell Digestiu Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Spain.

Mariona Serra-Pagès (M)

GoodGut S.L, Girona, Catalonia, Spain.

Jesús Garcia-Gil (J)

GoodGut S.L, Girona, Catalonia, Spain.
Deparment of Biology, University of Girona, Girona, Catalonia, Spain.

Xavier Aldeguer (X)

Servei Aparell Digestiu Hospital Universitari Dr. Josep Trueta, Girona, Spain.
GoodGut S.L, Girona, Catalonia, Spain.
Institut d'Investigació Biomèdica de Girona (IdIBGi), Girona, Catalonia, Spain.

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Classifications MeSH