Clinical trial NCT06191224: SwissGut - The Healthy Swiss Microbiome
Official title: SwissGut - A Longitudinal Cohort Study of the Healthy Human Faecal Microbiome in Switzerland
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Healthy
Keywords: microbiota
microbiome
health
hygiene
lifestyle
mental health
personality
inflammatory bowel disease
irritable bowel disease
nutrition
Lead sponsor: Insel Gruppe AG, University Hospital Bern
Sponsor class: OTHER
First posted: 2024-01-05
Enrollment: 200
Sex: ALL
Minimum age (years): 18
Maximum age (years): 90
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population will be recruited through convenience sampling at our institution in Bern and via outreach to the general population Switzerland-wide with a bias favouring the German speaking parts because documents are in German only. No members of the study team will be participants.

Brief 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).

Detailed 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.

Eligibility criteria: 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.

Primary outcomes:
measure: Intestinal inflammation - healthy Swiss vs. healthy Zimbabweans
timeFrame: 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.
measure: Evolutionary dynamics of bacterial strains - Swiss healthy vs. Swiss IBD
timeFrame: All timepoints with samples in both groups will be analysed.
measure: Intra-individual microbiome composition changes - Swiss healthy vs. Swiss UC with initial active disease
timeFrame: 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.
measure: Heart rate variability - Swiss healthy vs. Swiss IBD
timeFrame: Measurments from the first timepoint with heart rate variability assessment will be analysed.
Secondary outcomes:
measure: Difference in healthy microbiome composition - Swiss vs. Zimbabweans
timeFrame: 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.
measure: Difference in microbiome composition - Swiss healthy vs. Swiss UC active
timeFrame: 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.
measure: Difference in microbiome composition - Swiss healthy vs. Swiss UC remission
timeFrame: 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.
measure: Difference in microbiome composition - Swiss healthy no IBS vs. Swiss healthy IBS
timeFrame: 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.
measure: Difference in microbiome composition - Swiss low HRV vs. Swiss high HRV
timeFrame: 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.
Other outcomes:
measure: Difference in microbiome composition - Healthy Swiss circadian cycle
timeFrame: 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.
measure: Difference in microbiome composition - Healthy Swiss menstrual cycle
timeFrame: 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.
measure: Difference in microbiome composition - Healthy Swiss fatigue symptoms
timeFrame: 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.
measure: Difference in microbiome composition - Healthy Swiss depressive symptoms
timeFrame: 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.
measure: Difference in microbiome composition - Healthy Swiss personality (NEO-FFI)
timeFrame: 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.
measure: Difference in microbiome composition - Healthy Swiss personality (DS14)
timeFrame: 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.
measure: Difference in microbiome composition - Healthy Swiss nutrition
timeFrame: 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.
measure: Healthy Swiss core microbiome (strict) - Composition
timeFrame: 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.
measure: Healthy Swiss core microbiome (light) - Composition
timeFrame: 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.
measure: Healthy Swiss core microbiome (strict) - Bacterial metabolic pathways
timeFrame: 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.
Locations:
city: Bern
country: Switzerland
facility: Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland
Study officials:
affiliation: Inselspital, Bern University Hospital
name: Benjamin Misselwitz, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: University of Bern
name: Sebastian B. U. Jordi
role: STUDY_DIRECTOR
References: