Healthy
Conditions
Keywords
microbiota, microbiome, health, hygiene, lifestyle, mental health, personality, inflammatory bowel disease, irritable bowel disease, nutrition
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.
Interventions
None listed
Sponsors
Benjamin Misselwitz
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 90 Years
Healthy volunteers
Yes
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Intestinal inflammation - healthy Swiss vs. healthy Zimbabweans | 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. | 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. |
| Evolutionary dynamics of bacterial strains - Swiss healthy vs. Swiss IBD | All timepoints with samples in both groups will be analysed. | 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. |
| Intra-individual microbiome composition changes - Swiss healthy vs. Swiss UC with initial active disease | 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. | 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. |
| Heart rate variability - Swiss healthy vs. Swiss IBD | Measurments from the first timepoint with heart rate variability assessment will be analysed. | Heart rate variability (the root mean square of successive differences) measurements compared between healthy Swiss individuals and Swiss IBD patients. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Difference in healthy microbiome composition - Swiss vs. Zimbabweans | 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. | 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. |
| Difference in microbiome composition - Swiss low HRV vs. Swiss high HRV | 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. | 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. |
| Difference in microbiome composition - Swiss healthy vs. Swiss UC active | 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. | 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. |
| Difference in microbiome composition - Swiss healthy vs. Swiss UC remission | 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. | 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. |
| Difference in microbiome composition - Swiss healthy no IBS vs. Swiss healthy IBS | 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. | 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. |
Other
| Measure | Time frame | Description |
|---|---|---|
| Difference in microbiome composition - Healthy Swiss circadian cycle | 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. | 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. |
| Healthy Swiss core microbiome (strict) - Bacterial metabolic pathways | 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. | 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. |
| Difference in microbiome composition - Healthy Swiss menstrual cycle | 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. | 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. |
| Difference in microbiome composition - Healthy Swiss fatigue symptoms | 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. | 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. |
| Difference in microbiome composition - Healthy Swiss depressive symptoms | 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. | 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. |
| Difference in microbiome composition - Healthy Swiss personality (NEO-FFI) | 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. | 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. |
| Difference in microbiome composition - Healthy Swiss personality (DS14) | 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. | 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. |
| Difference in microbiome composition - Healthy Swiss nutrition | 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. | 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. |
| Healthy Swiss core microbiome (strict) - Composition | 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. | Characterisation of a constant healthy Swiss core microbiome comprising bacterial taxa that are present in all available samples of healthy Swiss individuals. |
| Healthy Swiss core microbiome (light) - Composition | 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. | Characterisation of a healthy Swiss core microbiome comprising bacterial taxa that are present in 80% of available samples of healthy Swiss individuals. |
Countries
Switzerland
Contacts
Primary ContactSebastian B. U. Jordi
Backup ContactBenjamin Misselwitz, MD
Outcome results
None listed