Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT03018925 |
| Other study ID # |
IISP 53713 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
October 2016 |
| Est. completion date |
October 2020 |
Study information
| Verified date |
June 2021 |
| Source |
Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
This study aims to characterize the changes on intestinal microbiota pattern associated with
the use of golimumab in order to determine if intestinal microbiota markers may correlate
with golimumab therapeutic effect in patients naïve & non-naïve to anti-TNF treatment
Description:
Golimumab effect in the modulation of gut microbiota in Ulcerative Colitis. Pilot Study.
1. BACKGROUND Recently, a consistent body of evidence indicates that the gut microbiota
ability to modulate and direct the host immune response is considered one of the pivotal
factors that modulate the delicate balance between health and disease in digestive
diseases. In the case of inflammatory bowel disease (IBD), the gut microbiota has a
central role in maintaining the microbiological homeostasis of the patient. Recent
studies describe the existence of different patterns of intestinal microbiota from
patients with IBD and healthy individuals . The alteration of the microbiological
pattern not associated with disease is known as dysbiosis and is directly related to the
degree of inflammation of the intestinal mucosa, and, thus, the clinic status: a greater
dysbiosis, greater clinical correlation with disease state, so that the gut microbiota
is a direct marker of the state of colonic inflammation .
The state of dysbiosis is measured through different microbiological indices of the total
population of bacteria in the colon. Changes in rates of these indices are the parameters
that are measured to characterize the gut microbiota of the patients. In the case of
ulcerative colitis (UC) studies have shown that intestinal microbiota is a central factor in
maintaining the balance between deep remission and the presence of a flare-up. Despite
advances, in-depth knowledge of how the gut microbiota interacts with the intestinal mucosa
and alters the intestinal barrier and the molecular/genetic mechanism is still unknown. Some
genes and associated cofactors have been identified but the exact mechanism of interaction
has not yet been described. The data indicate that, presumably, the mechanism of regulation
is a multifactorial process.
In this way, a deep understanding of gut microbiota and its interactions with the host and
the colon will be of great interest, in order to shape the future of IBD treatment,
especially of UC. Thus, IBD patients' intestinal microbiota could be either a therapeutic
target itself (fecal transplantation) or be consider as an adjustable adjuvant with
immunomodulators The group of anti-TNF drugs are the most recently incorporated in the
therapeutic arsenal of UC, in some cases changing the natural curse of the disease. However,
it is still unknown how these drugs modulate the intestinal microbiota and how they interfere
with it, although, probably, they develop a role. Recent results from studies by our group,
indicate that on entering clinical remission, gut microbiota is modified to patterns less
related with dysbiosis. Given the increasing importance of the use of anti-TNF drugs, it is
of great interest to discriminate between the patterns associated with dysbiosis and those
related with healthy mucosa, and how they are modified as a result of the use of anti-TNF
drugs. In this way, previous results of our group analyzing the changes of intestinal
microbiota associated with Adalimumab anti-TNF drug treatment have shown that during the
progression of the patient into remission, the mucosal dysbiosis pattern changes. On the
other hand, our group has also observed that after drug treatment failure, the gut microbiota
returns to a pattern closer to dysbiosis. For that reason, gut microbiota could be considered
as an excellent indicator of the real drug effectiveness in the patient.
Regarding Golimumab, a recently introduced anti-TNF drug therapy in UC, it is still unknown
how it is able to modulate the intestinal microbiota to remission-related patterns, since to
date there are not available studies about the relationship between Golimumab and this
phenomenon.
The use of prebiotics and probiotics has shown some effectiveness as adjuvants in the
treatment of UC . For that reason, further characterization of the gut microbiota patterns is
very important to develop new strategies for adjuvant ability to modulate it, especially in
patients receiving anti-TNF drugs and do not achieve complete remission. Similarly to recent
studies, we suggest that the modulation of gut microbiota could optimize the response
outcomes in patients treated with Golimumab.
In conclusion, based on current trends in the literature, we suggest that modulation of the
intestinal microbiota and the characterization of remission-related patterns, will have a
huge impact on the management of patients with UC. Moreover, the modulation of gut microbiota
together with the anti-TNF drug effectiveness could be the most promising field in the
management of inflammatory bowel disease.
2. HYPOTHESIS AND OBJECTIVES 2.1 Hypothesis
1. Intestinal microbiota profile change according to UC activity.
2. The Intestinal microbiota profile correlated to clinical remission is represented by
stable intestinal microbiota biodiversity.
3. Assess if Intestinal Microbiota is a useful tool to measure Golimumab effectiveness in
patients naïve to anti-TNF treatment and patients recurrent to anti-TNF treatment.
2.2 Objectives
1. To correlate clinical remission under Golimumab treatment with normal intestinal
microbiota profile biodiversity
2. To characterize the pattern of intestinal microbiota associated with the use of
Golimumab and temporal dynamics of microbial change.
3. Assess the effect of golimumab on the degree of colic dysbiosis in the treatment of
Ulcerative Colitis naive to Golimumab.
3. MATERIAL AND METHODS 3.1 Type of study/design Multicenter transversal pilot Study 3.2
Study population The proposed study will include 15 UC anti-TNF naïve patients from Hospital
Universitari Dr. Josep Trueta. Investigators will consider remission when patients have an
endoscopic Mayo score ≤1, and activity index score, Mayo= 0 points.
3.3 Interventions NOTE: "The assignment of a patient to a particular therapeutic strategy is
not predetermined in advance by the study protocol, instead clinical practice. Plus, the
decision to prescribe a particular drug is clearly unlinked from the decision to include the
patient in the study. Patients will not undergo any intervention, whether diagnostic or
monitoring, other than the usual clinical practice, and epidemiological methods shall be used
for the analysis of the data collected"
3.3.1 Treatments GOLIMUMAB induction with 200mg at week 0, and 100mg at week 2. Under 80kg,
the follow up treatment will be 50mg/month, and 100mg/month in patients over 80kg, as
clinical practice.
3.4 Variables 3.4.1 Demographic variables
- Age expressed in years (y)
- Sex Male (M)/ Female (F)
- Body Mass Index
- Ethnic: Caucasian/ African/ Asiatic/ American
- Tobacco: YES / NO / EX-Smoker
- Age of UC diagnosis expressed in years (y)
- Familiar Antecedents (YES/NO) which kind of disease?
- Localization Left (L)/ Righ (R) / extended (E) 3.4.2 Clinical variables
- Mayo clinic score (Clinical colitis activity index) (Schroeder KW et al. NEngl J Med
1987; 317: 1625-9). Score range: 0-9 points
- CRP (C-reactive protein): blood C-reactive protein concentration (mg/L)
- Faecal calprotectin: stool sample expressed in concentration of calprotectin in ug for g
of feces (ug/g)
- Standard Analysis:
Hemoglobin: blood hemoglobin concentration (g / dl) Platelets: blood platelets concentration
(x103/ ul) Leucocytes: blood leucocytes concentration (x103/ ul) Albumin: blood albumin
concentration (g / dl) Creatinine levels: blood creatinine concentration (mg/ dl) 3.4.3
Endoscopic variables • Mayo (Endoscopic score of Ulcerative Colitis) (Schroeder KW et al.
1987). Mayo Endoscopic Score is based only on Endoscopic Findings. Mayo Score range from 0 to
3.
o Note: Investigators will send the image to a centralized digital platform, where Mayo score
will be assessed by 2 independent professionals in order to minimize inter-observer bias.
3.4.4 Microbiological variables
- Operational Taxonomic Units (OTUs)
- Abundance and bacterial load. 3.5 Methods The proposed study will include 15 UC patients
over 18 years with informed consent signed, under treatment with anti-TNF according to
clinical practice. All of them will have been screened for opportunistic infections.
Patients will be anti-TNF naïve patients.
Stool samples will be collected before starting Anti-TNF treatment (A), and at weeks 4 (B), 9
(C), 13 (D), 26 (E), 39 (F), and 52 (G) to complete the study. The monitoring period will be
one year. Investigators will collect demographic variables (age, sex, tobacco, age of
diagnosis, localization,…), clinical data (partial Mayo clinical score, CRP, albumin,
hemoglobin, creatinine, leucocytes, platelets…), and microbiological variables at A, B, C, D,
E, F and G. Also, 7 calprotectin sampling (at weeks 4 (B), 9 (C), 13 (D), 26 (E), 39 (F), and
52 (G) as a clinical practice) and Mayo endoscopic index (at baseline and at the end of the
monitoring period as a clinical practice). Follow-up visits will also take place within
routine clinical practice. For better follow-up the evolution of the patient, investigators
will perform additional tests included in routine clinical practice as a rectosigmoidoscopy
at week 12 after starting Anti-TNF treatment.
Investigators will consider remission when patients have an endoscopic Mayo score ≤1, and
activity index score, Mayo clinical score =0 points.
Moreover, depending on the evolution of the patient, additional tests will also be performed
as routine clinical protocol during the monitoring period.
NOTE: Any test performed during the study and / or additional testing is routine clinical
practice according to clinical judgment and criteria of the physician.
3.5.1 Sample processing
DNA Extraction:
Before microbiological analyses, genomic DNA of 16s RNA gene will be extracted using
NucleoSpin® Soil Kit (Machery-Nagel GmbH & Co., Germany). DNA concentration will be
determined with Qubit® BR (Invitrogen) Kit.
Bacterial 16S rRNA Gene Amplification by Pyrosequencing For pyrosequencing purposes, the 16S
rRNA gene was partially amplified from extracted genomic DNA using the universal bacterial
primers GC-357F 5'- CGCCCG CCGCGCCCCGCGCCCGGCCCGCCGCCCCCGCCC- CCT ACG GGA GGC AGC AG-3'
(341Y357) and 907R 5'-CCG TCA ATT CCT TTG AGT TT-3' (907Y926). PCR was performed with a
GeneAmp PCR System ® 2700 (AppliedBiosystems)). Then we purify the PCR product with kit
Ampure (Agencourt AMPure, Beckman Coulter Inc), and quantify the PCR products with Qubit® BR
(Invitrogen) Kit. The pyrosequencing will be performed with a 454 Life Genome Sciences
Sequencer FLX.
Sequence Editing and Analysis High-quality consensus sequences will be obtained and manually
refined with the Bioedit software package. Alignments were carried out with ClustalW24
software. Consensus sequences were compared with those in GenBank and the Ribosomal Database
Project by using BLASTN 2.2.10. Sequences will be grouped by number of operational taxonomic
units or phylotypes with the DOTUR program26 using the farthest neighbor method at a
precision level of 0.01, i.e., 99% minimum similarity for any pair of sequences to belong to
the same phylotype, on a distance matrix with the Jukes-Cantor correction calculated with the
DNADIST program of the Phylip software package.
3.6 Statistical analysis Statistical analysis will be performed with the SPSSx version 11.0.
Significance of distances between groups was checked using an analysis of variance. Pearson_s
x2 test was used to compare the prevalence of genus and species.
Clinical and laboratory data will be correlated with the values of quantitative microbial
indices using Receiver Operating Characteristic (ROC) curves.
