Evaluation of Changes in Gut Microbiota in Patients with Crohn’s Disease after Anti-Tnfα Treatment: Prospective Multicenter Observational Study
Abstract
:1. Background
2. Methods
2.1. Ethics, Consent and Permission
2.2. Investigators
2.3. Study Objectives
2.4. Primary Study Variable
2.5. Secondary Study Variables
- ○
- Clinical remission: HBI ≤4 (Table 1)
- ○
- Clinically active disease: HBI >4
- ○
- Clinical response: when the HBI falls by three or more points.
- ○
- Relapse: increased activity assessed by clinical, laboratory, radiology or endoscopic findings leading to a change in treatment to control the disease or an HBI > 4.
- ○
- Biological remission: C-reactive protein (CRP) < 5 mg/L and (FC) < 250 μg/g.
- ○
- Active biological disease: CRP ≥ 5 mg/L and FC ≥ 250 μg/g.
- ○
- Overall response: the evaluation of clinical response will be established subjectively by the responsible physician according to clinical and analytical parameters, classifying patients as non-responders, responders without remission and responders in remission.
- ○
- Epidemiological characteristics: age, sex, smoking habits and body mass index.
- ○
- Clinical characteristics: date of diagnosis and disease pattern, Montreal classification, activity index, presence of extra-intestinal manifestations, pharmacological history, concomitant medication, adverse effects, presence/absence of initial and final overall response, and clinical decisions derived from this response.
- ○
- Anti-TNF treatment data: indication, type, start date, induction pattern, maintenance pattern, specify whether anti-TNF drugs were used prior to 24 weeks before inclusion and reason for discontinuation.
- ○
- Complementary examinations for each patient:
- -
- Laboratory tests: complete blood count, erythrocyte sedimentation rate, CRP, fibrinogen, ferritin, transferrin saturation index, total proteins, albumin, urea, creatinine, GOT/AST (Aspartate Aminotransferase), GPT/ALT (Alanine Aminotransferase), GGT (Gamma-glutamyl transpeptidase), ALP (Alkaline Phosphatase), cholesterol and triglycerides
- -
- FC
- -
- Stool culture, parasites and Clostridium difficile toxin in feces
- -
- Stool collection for microbiota analysis
- -
- Radiological (ultrasound/computerized tomography/magnetic resonance imaging) and/or endoscopic testing if available prior to treatment (at least 12 weeks prior to inclusion) or 6 months after treatment.
- -
- 72-h dietary record prior to stool sample collection for microbiota analysis. Patients will be provided with a daily survey in which they must record food and beverage intake, specifying characteristics, quantity and brands of packaged products.
- -
- Record of adherence to the Mediterranean diet. Together with the dietary record, the patients will also complete a validated survey of adherence to the Mediterranean diet [25] classifying this adherence as low (0–6 points), moderate (7–10 points) or high (11–14 points).
2.6. Study Design
2.7. Inclusion Criteria
2.8. Exclusion Criteria
2.9. Sample Size Considerations
2.10. Planning of the Sample Collection
2.11. Sequencing and Bioinformatics
2.12. Identification and Evaluation of Potential Biomarkers
2.13. Anti-TNF Dosage and Safety Evaluation
2.14. Statistical Analysis
3. Discussion
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
CD | Crohn’s disease |
CI | confidence interval |
CRP | C-reactive protein |
ET | enterotype |
FC | fecal calprotectin |
HBI | Harvey-Bradshaw Index |
IBD | inflammatory bowel disease |
RNA | ribonucleic acid |
SCFA | short chain fatty acids |
STAMP | Statistical Analysis of Metagenomic Profiles |
TNF | Tumor necrosis factor |
References
- Amon, P.; Sanderson, I. What is the microbiome? Arch. Dis. Child. Educ. Pract. Ed. 2017, 102, 258–261. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Young, V.B. The role of the microbiome in human health and disease: An introduction for clinicians. BMJ 2017, 356, j831. [Google Scholar] [CrossRef] [PubMed]
- Qin, J.; Li, R.; Raes, J.; Arumugam, M.; Burgdorf, K.S.; Manichanh, C.; Nielsen, T.; Pons, N.; Levenez, F.; Yamada, T.; et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 2010, 464, 59–65. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Methé, B.A.; Nelson, K.E.; Pop, M.; Creasy, H.H.; Giglio, M.G.; Huttenhower, C.; Gevers, D.; Petrosino, J.F.; Abubucker, S.; Badger, J.H.; et al. A framework for human microbiome research. Nature 2012, 486, 215–221. [Google Scholar] [CrossRef] [Green Version]
- Arumugam, M.; Raes, J.; Pelletier, E.; Le Paslier, D.; Yamada, T.; Mende, D.R.; Fernandes, G.R.; Tap, J.; Bruls, T.; Batto, J.M.; et al. Enterotypes of the human gut microbiome. Nature 2011, 473, 174–180. [Google Scholar] [CrossRef]
- Zuo, T.; Ng, S.C. The Gut Microbiota in the Pathogenesis and Therapeutics of Inflammatory Bowel Disease. Front. Microbiol. 2018, 9, 2247. [Google Scholar] [CrossRef]
- Collins, S.M. A role for the gut microbiota in IBS. Nat. Rev. Gastroenterol. Hepatol. 2014, 11, 497–505. [Google Scholar] [CrossRef]
- Klindworth, A.; Pruesse, E.; Schweer, T.; Peplies, J.; Quast, C.; Horn, M.; Glöckner, F.O. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2013, 41, 1–11. [Google Scholar] [CrossRef]
- Kaur, N.; Chen, C.C.; Luther, J.; Kao, J.Y. Intestinal dysbiosis in inflammatory bowel disease. Gut Microbes 2011, 2, 211–216. [Google Scholar] [CrossRef] [Green Version]
- Erickson, A.R.; Cantarel, B.L.; Lamendella, R.; Darzi, Y. Integrated metagenomics/metaproteomics reveals human host-microbiota signatures of Crohn’s disease. PLoS ONE 2012, 7, e49138. [Google Scholar] [CrossRef] [Green Version]
- Manichanch, C.; Borruel, N.; Casellas, F.; Guarner, F. The gut microbiota in IBD. Nat. Rev. Gastroenterol. Hepatol. 2012, 9, 599–608. [Google Scholar] [CrossRef] [PubMed]
- Da Silva, A.C.; Gomes, F.; Sassaki, Y.; Rodrigues, J. Escherichia coli from Crohn’s disease patient displays virulence features of enteroinvasive (EIEC), enterohemorragic (EHEC), and enteroaggregative (EAEC) pathotypes. Gut Pathog. 2015, 7, 2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Borruel, N.; Carol, M.; Casellas, F.; Antolín, M.; De Lara, F.; Espín, E.; Naval, J.; Guarner, F.; Malagelada, J.R. Increased mucosal tumour necrosis factor alpha production in Crohn’s disease can be downregulated ex vivo by probiotic bacteria. Gut 2002, 51, 659–664. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rajca, S.; Grondin, V.; Louis, E.; Vernier-Massouille, G.; Grimaud, J.-C.; Bouhnik, Y.; Laharie, D.; Dupas, J.-L.; Pillant, H.; Picon, L.; et al. Alterations in the intestinal microbiome (dysbiosis) as a predictor of relapse after infliximab withdrawal in Crohn’s disease. Inflamm. Bowel Dis. 2014, 20, 978–986. [Google Scholar] [CrossRef] [PubMed]
- Peyrin-Biroulet, L.; Reinisch, W.; Colombel, J.F.; Mantzaris, G.J.; Kornbluth, A.; Diamond, R.; Rutgeerts, P.; Tang, L.K.; Cornillie, F.J.; Sandborn, W.J. Clinical disease activity, C-reactive protein normalisation and mucosal healing in Crohn’s disease in the SONIC trial. Gut 2014, 63, 88–95. [Google Scholar] [CrossRef] [PubMed]
- Harvey, R.; Bradshaw, J. A simple index of Crohn’s disease activity. Lancet 1980, 1, 514. [Google Scholar] [CrossRef]
- Rogler, G.; Vavricka, S.; Schoepfer, A.; Lakatos, P.L. Mucosal healing and deep remission: What does it mean? World J. Gastroenterol. 2013, 19, 7552–7560. [Google Scholar] [CrossRef]
- Roseth, A.G.; Aadland, E.; Grzyb, K. Normalization of faecal calprotectin: A predictor of mucosal healing in patients with inflammatory bowel disease. Scand. J. Gastroenterol. 2004, 39, 1017–1020. [Google Scholar] [CrossRef]
- Sipponen, T.; Savilahti, E.; Kolho, K.L.; Nuutinen, H.; Turunen, U.; Färkkilä, M. Crohn’s disease activity assessed by fecal calprotectin and lactoferrin: Correlation with Crohn’s disease activity index and endoscopic findings. Inflamm. Bowel Dis. 2008, 14, 40–46. [Google Scholar] [CrossRef]
- Lopez-Siles, M.; Martinez-Medina, M.; Busquets, D.; Sabat-Mir, M.; Duncan, S.H.; Flint, H.J.; Aldeguer, X.; Garcia-Gil, L.J. Mucosa-associated Faecalibacterium prausnitzii and Escherichia coli co-abundance can distinguish Irritable Bowel Syndrome and Inflammatory Bowel Disease phenotypes. Appl. Environ. Microbiol. 2015, 81, 7582–7592. [Google Scholar] [CrossRef] [Green Version]
- Zhou, Y.; Xu, Z.Z.; He, Y.; Yang, Y.; Liu, L.; Lin, Q.; Nie, Y.; Li, M.; Zhi, F.; Liu, S.; et al. Gut Microbiota Offers Universal Biomarkers across Ethnicity in Inflammatory Bowel Disease Diagnosis and Infliximab Response Prediction. mSystems 2018, 3, 1–14. [Google Scholar] [CrossRef] [Green Version]
- Magnusson, M.K.; Strid, H.; Sapnara, M.; Lasson, A.; Bajor, A.; Ung, K.-A.; Öhman, L. Anti-TNF therapy response in patients with ulcerative colitis is associated with colonic antimicrobial peptide expression and microbiota composition. J. Crohns Colitis 2016, 10, 943–952. [Google Scholar] [CrossRef]
- Wang, Y.; Gao, X.; Ghozlane, A.; Hu, H.; Li, X.; Xiao, Y.; Li, D.; Yu, G.; Zhang, T. Characteristics of faecal microbiota in paediatric Crohn’s disease and their dynamic changes during infliximab therapy. J. Crohns Colitis 2017, 1, 1–10. [Google Scholar] [CrossRef] [PubMed]
- Puig, L.; Ruiz de Morales, J.G.; Dauden, E.; Andreu, J.L.; Cervera, R.; Adán, A.; Marsal, S.; Escobar, C.; Hinojosa, J.; Palau, J.; et al. La prevalencia de diez enfermedades inflamatorias inmunomediadas (IMID) en España. Rev. Esp. Salud Pública 2019, 93, 25. [Google Scholar]
- Martínez-González, M.A.; Salas-Salvadó, J.; Estruch, R.; Corella, D.; Fitó, M.; Ros, E. Predimed Investigators. Benefits of the Mediterranean Diet: Insights from the PREDIMED Study. Prog. Cardiovasc. Dis. 2015, 58, 50–60. [Google Scholar] [CrossRef] [Green Version]
- Lewis, J.D.; Chen, E.Z.; Baldassano, R.N.; Otley, A.R.; Griffiths, A.M.; Lee, D.; Bittinger, K.; Bailey, A.; Friedman, E.S.; Hoffmann, C.; et al. Inflammation, Antibiotics, and Diet as Environmental Stressors of the Gut Microbiome in Pediatric Crohn’s Disease. Cell Host Microbe 2015, 18, 489–500. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Scaldaferri, F.; Gerardi, V.; Pecere, S.; Petito, V.; Lopetuso, L.R.; Zambrano, D.; Schiavoni, E.; D’Ambrosio, D.; di Agostini, A.; Laterza, L.; et al. Anti-TNF-α induction regimen modulates gut microbiota molecular composition while inducing clinical response in Crohn’s Disease patients: Toward a personalized Medicine. Gastroenterology 2015, 148, S-852. [Google Scholar] [CrossRef]
- Kolho, K.L.; Korpela, K.; Jaakkola, T.; Pichai, M.V.; Zoetendal, E.G.; Salonen, A.; De Vos, W.M. Fecal microbiota in pediatric inflammatory bowel disease and its relation to inflammation. Am. J. Gastroenterol. 2015, 110, 921–930. [Google Scholar] [CrossRef]
- Busquets, D.; Mas-de-Xaxars, T.; Lpez-Siles, M.; Martínez-Medina, M.; Bahí, A.; Sàbat, M.; Louvriex, R.; Miquel-Cusachs, J.O.; Garcia-Gil, J.L.; Aldeguer, X. Anti-tumour necrosis factor treatment with adalimumab induces changes in the microbiota of Crohn’s Disease. J. Crohns Colitis 2015, 9, 899–906. [Google Scholar] [CrossRef] [Green Version]
- Ribaldone, D.G.; Caviglia, G.P.; Abdulle, A.; Pellicano, R.; Ditto, M.C.; Morino, M.; Fusaro, E.; Saracco, G.M.; Bugianesi, E.; Astegiano, M. Adalimumab Therapy Improves Intestinal Dysbiosis in Crohn’s Disease. J. Clin. Med. 2019, 8, 1646. [Google Scholar] [CrossRef] [Green Version]
- Bolyen, E.; Rideout, J.R.; Dillon, M.R.; Bokulich, N.A.; Abnet, C.C.; Al-Ghalith, G.A.; Alexander, H.; Alm, E.J.; Arumugam, M.; Asnicar, F.; et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 2019, 37, 852–857. [Google Scholar] [CrossRef] [PubMed]
- Segata, N.; Izard, J.; Waldron, L.; Gevers, D.; Miropolsky, L.; Garrett, W.S.; Huttenhower, C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011, 12, R60. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dobnik, D.; Štebih, D.; Blejec, A.; Morisset, D.; Žel, J. Multiplex quantification of four DNA targets in one reaction with Bio-Rad droplet digital PCR system for GMO detection. Sci. Rep. 2016, 6, 1–9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Postel, M.; Roosen, A.; Laurent-Puig, P.; Taly, V.; Wang-Renault, S.F. Droplet-based digital PCR and next generation sequencing for monitoring circulating tumor DNA: A cancer diagnostic perspective. Expert Rev. Mol. Diagn. 2018, 18, 7–17. [Google Scholar] [CrossRef] [PubMed]
- Huijsdens, X.W.; Linskens, R.K.; Mak, M.; Meuwissen, S.G.; Vandenbroucke-Grauls, C.M.; Savelkoul, P.H. Quantification of Bacteria Adherent to Gastrointestinal Mucosa by Real-Time PCR. J. Clin. Microbiol. 2002, 40, 4423–4427. [Google Scholar] [CrossRef] [Green Version]
- Furet, J.P.; Firmesse, O.; Gourmelon, M.; Bridonneau, C.; Tap, J.; Mondot, S.; Dore, J.; Corthier, G. Comparative assessment of human and farm animal faecal microbiota using real-time quantitative PCR. FEMS Microbiol. Ecol. 2009, 68, 351–362. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Naranjo, C.A.; Busto, U.; Sellers, E.M.; Sandor, P.; Ruiz, I.; Roberts, E.A.; Janecek, E.; Domecq, C.; Greenblatt, D.J. A method for estimating the probability of adverse drug reactions. Clin. Pharmacol. Ther. 1981, 30, 239–245. [Google Scholar] [CrossRef]
- Parks, D.H.; Tyson, G.W.; Hugenholtz, P.; Beiko, R.G. STAMP: Statistical analysis of taxonomic and functional profiles. Bioinformatics 2014, 30, 3123–3124. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Monif, G.R. Understanding Therapeutic Concepts in Crohn’s Disease. Clin. Med. Insights Gastroenterol. 2018, 11, 1–3. [Google Scholar] [CrossRef] [Green Version]
- Na, S.Y.; Moon, W. Perspectives on Current and Novel Treatments for Inflammatory Bowel Disease. Gut Liver 2019, 13, 604–616. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wu, G.D.; Chen, J.; Hoffmann, C.; Bittinger, K.; Chen, Y.-Y.; Keilbaugh, S.A.; Bewtra, M.; Knights, D.; Walters, W.A.; Knight, R.; et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 2011, 334, 105–108. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kovatcheva-Datchary, P.; Nilsson, A.; Akrami, R.; Lee, Y.S.; de Vadder, F.; Arora, T.; Hallen, A.; Martens, E.; Björck, I.; Bäckhed, F. Dietary Fiber-Induced Improvement in Glucose Metabolism Is Associated with Increased Abundance of Prevotella. Cell Metab. 2015, 22, 971–982. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ley, R.E.; Turnbaugh, P.J.; Klein, S.; Gordon, J.I. Human gut microbes associated with obesity. Nature 2006, 444, 1022–1023. [Google Scholar] [CrossRef] [PubMed]
General Well-Being (Previous Day) | 0 (Very Well) | 1 (Slightly Below Par) | 2 (Poor) | 3 (Very Poor) | 4 (Terrible) |
Abdominal pain | 0 (none) | 1 (mild) | 2 (moderate) | 3 (severe) | |
Number of liquid or soft stools per day (previous day) | |||||
Complications (score 1 per item) | Arthritis/ arthralgia | Iritis/ uveitis | Erythema nodosum/ aphthous ulcers/Pyoderma gangrenosum | Anal fissure new fistula/ abscess | |
Abdominal mass | 0 (none) | 1 (dubious) | 2 (definite) | 3 (definite + tender) |
Study Variables |
---|
Primary: Normalization of gut microbiota (after anti-TNF treatment) (yes/no) |
Secondary variables: A. Gut microbiota
|
Target | Primers and Probe | Sequences 5′-3′ | Reference |
---|---|---|---|
F. prausnitzii | Fpra_428_F | TGTAAACTCCTGTTGTTGAGGAAGATAA | [20] |
Fpra_583_R | GCGCTCCCTTTACACCCA | ||
Fpra_493_PR | FAM/CAAGGAAGTGACGGCTAACTACGTGCCAG/IABkFQ | ||
E. coli | Ecoli_395_F | CATGCCGCGTGTATGAAGAA | [35] |
Ecoli_490_R | CGGGTAACGTCAATGAGCAAA | ||
Ecoli_437_PR | FAM/TATTAACTTTACTCCCTTCCTCCCCGCTGAA/IABkFQ | ||
C. coccoides | F_Ccoc_07 | GACGCCGCGTGAAGGA | [36] |
R_Ccoc_14 | AGCCCCAGCCTTTCACAT | ||
P_Erec_482 | VIC/CGGTACCTGACTAAGAAG/IABkFQ | ||
Bacteria | F_Bact_1369 | CGGTGAATACGTTCCCGG | [36] |
R_Prok_1492 | TACGGCTACCTTGTTACGACTT | ||
P_TM_1389F | FAM/CTTGTACACACCGCCCGTC/IABkFQ |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sanchis-Artero, L.; Martínez-Blanch, J.F.; Manresa-Vera, S.; Cortés-Castell, E.; Rodriguez-Morales, J.; Cortés-Rizo, X. Evaluation of Changes in Gut Microbiota in Patients with Crohn’s Disease after Anti-Tnfα Treatment: Prospective Multicenter Observational Study. Int. J. Environ. Res. Public Health 2020, 17, 5120. https://doi.org/10.3390/ijerph17145120
Sanchis-Artero L, Martínez-Blanch JF, Manresa-Vera S, Cortés-Castell E, Rodriguez-Morales J, Cortés-Rizo X. Evaluation of Changes in Gut Microbiota in Patients with Crohn’s Disease after Anti-Tnfα Treatment: Prospective Multicenter Observational Study. International Journal of Environmental Research and Public Health. 2020; 17(14):5120. https://doi.org/10.3390/ijerph17145120
Chicago/Turabian StyleSanchis-Artero, Laura, Juan Francisco Martínez-Blanch, Sergio Manresa-Vera, Ernesto Cortés-Castell, Josefa Rodriguez-Morales, and Xavier Cortés-Rizo. 2020. "Evaluation of Changes in Gut Microbiota in Patients with Crohn’s Disease after Anti-Tnfα Treatment: Prospective Multicenter Observational Study" International Journal of Environmental Research and Public Health 17, no. 14: 5120. https://doi.org/10.3390/ijerph17145120