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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06191224
Other study ID # BASEC 2023-00706
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date May 28, 2023
Est. completion date July 5, 2025

Study information

Verified date January 2024
Source Insel Gruppe AG, University Hospital Bern
Contact Sebastian B. U. Jordi
Phone +41 31 664 33 63
Email research.2omrx@passfwd.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Objective: This study is designed to address the complex interplay between the gut microbiome, environmental factors, and inflammatory diseases, with a specific emphasis on serving as a healthy cohort for several related projects. Primary hypotheses: Since data from this study will be used as control data for four studies, four primary hypothesis will be defined. Hypothesis H1: Levels of intestinal inflammation will be substantially higher in Zimbabweans living in rural areas and low-resource settings (i.e. high-density areas) compared to Zimbabwean and Swiss individuals living in high-resource settings. Hypothesis H2: Bottlenecks and blooms of bacterial strains are less frequent in healthy participants than in inflammatory bowel disease (IBD) patients and bacterial strains will have lower mutation rates in healthy patients when compared to strains from IBD subjects (partner study: BASEC 2021-00871). Hypothesis H3: Longitudinal changes of the faecal microbiome of healthy Swiss individuals differ systematically compared to longitudinal changes of the faecal microbiome of Swiss UC patients with active disease (partner study: BASEC 2022-02008). Hypothesis H4: The HRV of healthy Swiss individuals differ systematically from HRV of Swiss IBD patients and can be associated with differentially abundant bacterial taxa (partner study: BASEC 2022-02008).


Description:

Objective: This study investigates the relationship between lifestyle, gut bacteria, and diseases such as colorectal cancer and inflammatory bowel diseases (IBD). The investigators aim to understand how the gut microbiome, influenced by different environments, impacts disease development. Our research focuses on healthy Swiss individuals as a control group for ongoing projects. Primary hypotheses: Since data from this study will be used as control data for four studies, four primary hypothesis will be defined. Hypothesis H1: Levels of intestinal inflammation will be substantially higher in Zimbabweans living in rural areas and low-resource settings (i.e. high-density areas) compared to Zimbabwean and Swiss individuals living in high-resource settings. Hypothesis H2: Bottlenecks and blooms of bacterial strains are less frequent in healthy participants than in IBD patients and bacterial strains will have lower mutation rates in healthy patients when compared to IBD subjects (partner study: BASEC 2021-00871). Hypothesis H3: Longitudinal changes of the faecal microbiome of healthy Swiss individuals differ systematically compared to longitudinal changes of the faecal microbiome of Swiss UC patients with active disease (partner study: BASEC 2022-02008). Hypothesis H4: The heart rate variability (HRV) of healthy Swiss individuals differ systematically from HRV of Swiss IBD patients and can be associated with differentially abundant bacterial taxa (partner study: BASEC 2022-02008). Secondary hypotheses Hypothesis H5: The faecal microbiome composition of healthy Swiss individuals differs systematically from the faecal microbiome composition of healthy Zimbabweans. (O1) Hypothesis H6: The faecal microbiome composition of healthy Swiss individuals differs systematically from the faecal microbiome of Swiss UC patients experiencing a disease flare. Hypothesis H7: The faecal microbiome composition of healthy Swiss individuals differs systematically from the faecal microbiome of Swiss UC patients after achieving disease remission. Hypothesis H8: The faecal microbiome composition of healthy Swiss without symptoms of irritable bowel syndrome (Rome IV criteria) differs systematically from the faecal microbiome of healthy Swiss with symptoms of irritable bowel syndrome. Design: Observational cohort study with 200 healthy Swiss participants. Participants are followed-up during one year. During the study, 12 faecal samples, voluntary blood samples, and comprehensive data are collected from each participant. Assessed data include clinical assessments, detailed socio-economic information and voluntary heart rate variability (HRV) measurements. The study's longitudinal approach comprises 12 defined follow-ups at days 0, 3, 5, and 7; weeks 2, 3, 4, 8, and 12; and months 6, 9, and 12. The faecal samples will be collected by the participants at home with provided vials. In addition, each faecal sample is accompanied by a follow-up questionnaire to filled out by the patient. The questionnaires focus on gastrointestinal symptoms, fatigue, socio-economic variables, emotional well-being, five factor model (personality) assessment and type D personality, and a simple dietary assessment covering a 24-hour period. Participants will mail the stool vials and questionnaires, using a provided envelope, to Inselspital Bern via the Swiss postal service. Blood samples will be acquired only from a subset of the participants primarily at enrolment. Recruitment: Primarily at the Department of Visceral Surgery and Medicine of the University Hospital Bern (Inselspital Bern), and through outreach to the general population.


Recruitment information / eligibility

Status Recruiting
Enrollment 200
Est. completion date July 5, 2025
Est. primary completion date July 5, 2025
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years to 90 Years
Eligibility Inclusion Criteria: - Signed informed consent - Age 18-90 years - General ability to give consent for study inclusion, understand and follow study procedures - No current or past diagnosis of IBD or colorectal carcinoma - No current medical complaints typical for IBD or other severe intestinal diseases (e.g. Diarrhea, severe constipation, abdominal pain, blood in stool, weight loss). Minor symptoms, (not impairing daily activities) are permitted. - No other current relevant gastrointestinal disease or condition plausibly interfering with microbiota assessment according to the discretion of the study physician. Exclusion Criteria: - All patients with recent acute gastrointestinal disease (e.g., confirmed infectious diarrhea) within the last month or relevant intestinal symptoms (impairing daily activities). - Use of antibiotics within the last 3 months. - Current pouch or ileostomy/ colostomy. - Severe medical, surgical, or psychiatric comorbidities interfering with study procedure according to the judgement of the investigator (patients with comorbidities that would not interfere with the primary endpoints I-III but don't allow the assessment of HRV according to the judgement of the investigator (e.g. heart diseases) will be included in the study but the HRV will not be assessed). - Participation in an interfering clinical study.

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
Switzerland Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland Bern

Sponsors (1)

Lead Sponsor Collaborator
Benjamin Misselwitz

Country where clinical trial is conducted

Switzerland, 

Outcome

Type Measure Description Time frame Safety issue
Other Difference in microbiome composition - Healthy Swiss circadian cycle Dissimilarity changes (weighted Unifrac index) between the microbiomes of samples from healthy Swiss individuals in dependence on the circadian cycle (indicated by sampling time).
The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method.
All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Difference in microbiome composition - Healthy Swiss menstrual cycle Dissimilarity changes (weighted Unifrac index) between the microbiomes of samples from healthy Swiss females in dependence on the menstrual cycle.
The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method.
All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Difference in microbiome composition - Healthy Swiss fatigue symptoms Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals with and without symptoms of fatigue assessed by the VAS-F fatigue severity scale.
The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method.
All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Difference in microbiome composition - Healthy Swiss depressive symptoms Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals with and without symptoms of depression assessed by a two questions screening test.
The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method.
All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Difference in microbiome composition - Healthy Swiss personality (NEO-FFI) Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals in dependence on scores in personality domains assessed by the NEO-FFI questionnaire.
The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method.
All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Difference in microbiome composition - Healthy Swiss personality (DS14) Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals with and without type D personality assessed by the DS14 questionnaire.
The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method.
All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Difference in microbiome composition - Healthy Swiss nutrition Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals in dependence on their recent nutrition (simple self-reported dietary assessment covering a 24-hour period).
The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method.
All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Healthy Swiss core microbiome (strict) - Composition Characterisation of a constant healthy Swiss core microbiome comprising bacterial taxa that are present in all available samples of healthy Swiss individuals. All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Healthy Swiss core microbiome (light) - Composition Characterisation of a healthy Swiss core microbiome comprising bacterial taxa that are present in 80% of available samples of healthy Swiss individuals. All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Other Healthy Swiss core microbiome (strict) - Bacterial metabolic pathways Characterisation of core bacterial metabolic pathways present (independent of expression) in all available samples of healthy Swiss individuals. The presence of a bacterial metabolic pathway will either be inferred by PICRUSt (or comparable tools) and/or assessed by shotgun metagenomic sequencing and/or full genome sequencing of isolated bacterial strains from participant samples. All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Primary Intestinal inflammation - healthy Swiss vs. healthy Zimbabweans Difference in calprotectin levels of healthy Swiss individuals and healthy Zimbabweans in high-resource settings compared to calprotectin levels in Zimbabweans in low-resource settings. All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Primary Evolutionary dynamics of bacterial strains - Swiss healthy vs. Swiss IBD The evolutionary dynamics of the most frequent and the most abundant bacteria in healthy Swiss individuals compared to Swiss IBD patients by assessing mutation rate per genome per generation.
Comment: calculation of mutation rates is only feasible for abundant bacteria which can be found in a high fraction of participants over more than one timepoint. The investigators will thus determine the most suitable bacterial species and focus the analysis on this bacterial species.
All timepoints with samples in both groups will be analysed.
Primary Intra-individual microbiome composition changes - Swiss healthy vs. Swiss UC with initial active disease Difference in absolute dissimilarity (weighted Unifrac index) changes within individuals over time between the faecal microbiomes of healthy Swiss individuals and the faecal microbiomes of Swiss UC patients initially experiencing a disease flare. Samples from enrolment and after 12 months will be analysed. Alternatively, samples from enrolment and a second timepoint (> 1 week later) with the most available samples and relevant metadata will be prioritised.
Primary Heart rate variability - Swiss healthy vs. Swiss IBD Heart rate variability (the root mean square of successive differences) measurements compared between healthy Swiss individuals and Swiss IBD patients. Measurments from the first timepoint with heart rate variability assessment will be analysed.
Secondary Difference in healthy microbiome composition - Swiss vs. Zimbabweans Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals and the microbiomes of healthy Zimbabweans. (H5) The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method. All sampling timepoints will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Secondary Difference in microbiome composition - Swiss healthy vs. Swiss UC active Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals and the microbiomes of Swiss UC patients with active disease (i.e., in a disease flare). (H6) The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method. All sampling timepoints of defined subgroups will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Secondary Difference in microbiome composition - Swiss healthy vs. Swiss UC remission Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss individuals and the microbiomes of Swiss UC patients with inactive disease (i.e., remission). (H7) The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method. All sampling timepoints of defined subgroups will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Secondary Difference in microbiome composition - Swiss healthy no IBS vs. Swiss healthy IBS Dissimilarity (weighted Unifrac index) between the microbiomes of healthy Swiss with and without symptoms of irritable bowel syndrome (Rome IV criteria). (H8) The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method. All sampling timepoints of defined subgroups will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
Secondary Difference in microbiome composition - Swiss low HRV vs. Swiss high HRV Dissimilarity (weighted Unifrac index) between the microbiomes of individuals with a low heart rate variability compared to individuals with a high HRV. (H8) The endpoint will be tested by performing a permutational multivariate analysis of variance of the index with the adonis function of the vegan R package or another appropriate method. All sampling timepoints of defined subgroups will be analysed, accounting for dependence between samples from the same individual. Alternatively, the timepoint with the most available samples and relevant metadata will be prioritised.
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