Deciphering the Impact of Exposures From the Gut Microbiome-derived Molecular Complex in Human Health and Disease

The ExpoBiome project will analyze the impact of fasting on patients with Parkinsons's Disease (PD) or rheumatoid arthritis (RA) on a clinical level as well as the effect of fasting on their immune system and gut microbiota. ExpoBiome will combine metagenomics and other "omics" \[meta-transcriptomics, meta-proteomics and (meta-)metabolomics\], bioinformatic analyses and biostatistics under a systems biology framework to gain new mechanistic insights into microbiome-immune system interactions in the context of chronic diseases with inflammatory signatures.

Besides a one time crossectional study of healthy participants, patients with RA and PD a longitudinal fasting study with two arms (RA and PD) is planned.

The human gut microbiome is a complex ecosystem, which contributes essential functions to human physiology. Changes to the microbiome are associated with several chronic diseases characterised by inflammation, including neurodegenerative and autoimmune diseases. Microbiome-derived effector molecules comprising nucleic acids, (poly)peptides and metabolites are present at high levels in the gut but have so far eluded systematic study. This gap in knowledge is limiting mechanistic understanding of the microbiome's functional impact on chronic diseases such as Parkinson's Disease (PD) and rheumatoid arthritis (RA). Here, for the first time a combination of advanced high-resolution methodologies will be integrated to comprehensively identify the constituents of this molecular complex and their impact on the human immune system. First, a quantitative, integrated multi-omic analysis on microbiome samples collected from healthy individuals and patients with newly diagnosed PD or RA will be performes.

Using contextualised prior knowledge (ExpoBiome Map) and machine learning methods, we will identify microbial molecules associated with condition-specific immunophenotypes. Second, the biomarker signature during a model clinical intervention (therapeutic fasting) will be validated and tracked to predict treatment outcomes. Third, microbes and molecules will be screened in personalised HuMiX gut-on-chip models to identify novel anti-inflammatory compounds. By providing mechanistic insights into the molecular basis of human-microbiome interactions, the project will generate essential new knowledge about causal relationships between the gut microbiome and the immune system in health and disease. By facilitating the elucidation of currently unknown microbiome-derived molecules, it will identify new genes, proteins,metabolites and host pathways for the development of future diagnostic and therapeutic applications.

Eligibility Criteria:
Inclusion Criteria:

* One of the following diagnoses: rheumatoid arthritis (first diagnosis \>6 weeks ago and \<8 years), parkinson's disease OR healthy volunteer
* Control ("healthy") individuals must be without any evidence of active, known or treated RA, without any evidence of active, known or treated central nervous system disease, and without a known family history of idiopathic PD
* Arthritis in at least one joint
* Control individuals should match the RA or PD individuals as closely as possible, especially their age, sex, and education
* Present written declaration of consent
* Consent to specimen collection and specimen use
* Ability to understand the patient information and willingness to sign the consent form

Exclusion Criteria:

* gout or proven bacterial arthritis
* Psychiatric illness that limits understanding of the examination protocol (unable to consent)
* BMI \< 18.5
* Pre-existing/current eating disorders (bulimia nervosa, anorexia nervosa) within the past 5 years.
* Severe internal diseases (e.g. renal insufficiency with creatinine \> 2mg/dl)
* Participation in another study
* Existing vegan diet or fasting within the past 6 months
* Pregnancy or breastfeeding
* Chronic inflammatory bowel disease
* Use of antibiotics within the past 12 months
* Presence of anemia