Metabonomics and the Gut Microbiome Associated With Primary Response to Anti-TNF Therapy in Crohn's Disease.


Journal

Journal of Crohn's & colitis
ISSN: 1876-4479
Titre abrégé: J Crohns Colitis
Pays: England
ID NLM: 101318676

Informations de publication

Date de publication:
07 Sep 2020
Historique:
pubmed: 3 3 2020
medline: 15 7 2021
entrez: 3 3 2020
Statut: ppublish

Résumé

Anti-tumour necrosis factor [anti-TNF] therapy is indicated for treatment of moderate to severe inflammatory bowel disease [IBD], but has a primary non-response rate of around 30%. We aim to use metabonomic and metataxonomic profiling to identify predictive biomarkers of anti-TNF response in Crohn's disease. Patients with luminal Crohn's disease, commencing anti-TNF therapy, were recruited with urine, faeces, and serum samples being collected at baseline and 3-monthly. Primary response was defined according to a combination of clinical and objective markers of inflammation. Samples were measured using three UPLC-MS assays: lipid, bile acid, and Hydrophillic Interaction Liquid Chromatography [HILIC] profiling with 16S rRNA gene sequencing of faeces. Samples were collected from 76 Crohn's disease patients who were anti-TNF naïve and from 13 healthy controls. There were 11 responders, 37 non-responders, and 28 partial responders in anti-TNF-treated Crohn's patients. Histidine and cysteine were identified as biomarkers of response from polar metabolite profiling [HILIC] of serum and urine. Lipid profiling of serum and faeces found phosphocholines, ceramides, sphingomyelins, and triglycerides, and bile acid profiling identified primary bile acids to be associated with non-response to anti-TNF therapy, with higher levels of phase 2 conjugates in non-responders. Receiver operating curves for treatment response demonstrated 0.94 +/ -0.10 [faecal lipid], 0.81 +/- 0.17 [faecal bile acid], and 0.74 +/- 0.15 [serum bile acid] predictive ability for anti-TNF response in Crohn's disease. This prospective, longitudinal cohort study of metabonomic and 16S rRNA gene sequencing analysis demonstrates that a range of metabolic biomarkers involving lipid, bile acid, and amino acid pathways may contribute to prediction of response to anti-TNF therapy in Crohn's disease. This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast.

Sections du résumé

BACKGROUND AND AIMS OBJECTIVE
Anti-tumour necrosis factor [anti-TNF] therapy is indicated for treatment of moderate to severe inflammatory bowel disease [IBD], but has a primary non-response rate of around 30%. We aim to use metabonomic and metataxonomic profiling to identify predictive biomarkers of anti-TNF response in Crohn's disease.
METHODS METHODS
Patients with luminal Crohn's disease, commencing anti-TNF therapy, were recruited with urine, faeces, and serum samples being collected at baseline and 3-monthly. Primary response was defined according to a combination of clinical and objective markers of inflammation. Samples were measured using three UPLC-MS assays: lipid, bile acid, and Hydrophillic Interaction Liquid Chromatography [HILIC] profiling with 16S rRNA gene sequencing of faeces.
RESULTS RESULTS
Samples were collected from 76 Crohn's disease patients who were anti-TNF naïve and from 13 healthy controls. There were 11 responders, 37 non-responders, and 28 partial responders in anti-TNF-treated Crohn's patients. Histidine and cysteine were identified as biomarkers of response from polar metabolite profiling [HILIC] of serum and urine. Lipid profiling of serum and faeces found phosphocholines, ceramides, sphingomyelins, and triglycerides, and bile acid profiling identified primary bile acids to be associated with non-response to anti-TNF therapy, with higher levels of phase 2 conjugates in non-responders. Receiver operating curves for treatment response demonstrated 0.94 +/ -0.10 [faecal lipid], 0.81 +/- 0.17 [faecal bile acid], and 0.74 +/- 0.15 [serum bile acid] predictive ability for anti-TNF response in Crohn's disease.
CONCLUSIONS CONCLUSIONS
This prospective, longitudinal cohort study of metabonomic and 16S rRNA gene sequencing analysis demonstrates that a range of metabolic biomarkers involving lipid, bile acid, and amino acid pathways may contribute to prediction of response to anti-TNF therapy in Crohn's disease.
PODCAST UNASSIGNED
This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast.

Identifiants

pubmed: 32119090
pii: 5771407
doi: 10.1093/ecco-jcc/jjaa039
doi:

Substances chimiques

Bile Acids and Salts 0
Biomarkers, Pharmacological 0
RNA, Ribosomal, 16S 0
Tumor Necrosis Factor Inhibitors 0
Histidine 4QD397987E
Infliximab B72HH48FLU
Adalimumab FYS6T7F842
Cysteine K848JZ4886

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1090-1102

Subventions

Organisme : Medical Research Council
ID : MR/P028225/1
Pays : United Kingdom

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of European Crohn’s and Colitis Organisation. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

N S Ding (NS)

St Vincent's Hospital, Inflammatory Bowel Disease, Melbourne, VIC, Australia.
St Mark's Hospital, Inflammatory Bowel Disease Unit, London, UK.
Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.

J A K McDonald (JAK)

Division of Digestive Diseases, Department of Surgery and Cancer, St Mary's Hospital, Imperial College London, London, UK.

A Perdones-Montero (A)

Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.

Douglas N Rees (DN)

Division of Digestive Diseases, Department of Surgery and Cancer, St Mary's Hospital, Imperial College London, London, UK.

S O Adegbola (SO)

St Mark's Hospital, Inflammatory Bowel Disease Unit, London, UK.
Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.

R Misra (R)

St Mark's Hospital, Inflammatory Bowel Disease Unit, London, UK.
Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.

P Hendy (P)

St Mark's Hospital, Inflammatory Bowel Disease Unit, London, UK.

L Penez (L)

St Mark's Hospital, Inflammatory Bowel Disease Unit, London, UK.

J R Marchesi (JR)

School of Biosciences, Cardiff University, Cardiff, UK.
Division of Digestive Diseases, Department of Surgery and Cancer, St Mary's Hospital, Imperial College London, London, UK.

E Holmes (E)

Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.
Institute of Health Futures, Murdoch University, Perth, WA, Australia.

M H Sarafian (MH)

Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.

A L Hart (AL)

St Mark's Hospital, Inflammatory Bowel Disease Unit, London, UK.
Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.

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Classifications MeSH