Multi-omics Dissection of Gut Microbiome Engraftment During FMT

The gut microbiota plays a key role in immunity and metabolism and contributes to diseases such as recurrent C. difficile infection (rCDI), ulcerative colitis (UC), and metabolic syndrome (MetS). Microbiota therapeutics, particularly fecal microbiota transplantation (FMT), show promise-achieving \~90% cure rates in rCDI-but demonstrate variable efficacy in chronic conditions. Microbiome engraftment appears critical for FMT success, yet consistent predictors remain lacking. A meta-analysis of 20 FMT studies by our group and the Segata Lab linked engraftment to clinical response across diseases, with taxon-specific patterns and ML-based predictability. While viral, fungal, host immune, genetic, and metabolic factors may affect engraftment, their roles are not well-defined. Key unresolved questions include the interplay among host factors, microbial strains, and metabolites, their influence on engraftment, and impact on clinical outcomes. This study aims to unravel microbiome engraftment dynamics and link them to therapeutic response.

Gut microbiota regulates key functions in humans, i.e. immunity and metabolism, and is a pathogenic pathway of many disorders, including recurrent C. difficile infection (rCDI), ulcerative colitis (UC), and metabolic syndrome (MetS). Microbiota therapeutics (MT) have raised high expectations without comparable results. Among MT, fecal microbiota transplantation (FMT), the transfer of healthy donor feces to a recipient with a microbiome-associated disease, has achieved high (nearly 90%) cure rates of rCDI but lower and less consistent results in chronic disorders, i.e. UC or MetS. Clinical and microbial features seem to be related with FMT outcomes, but consistent predictors are not available. Donor-recipient microbiome engraftment may be critical for the clinical success of FMT. In a pooled meta-analysis of 20 FMT studies in different diseases by our group and the Segata Lab , donor recipient microbiome engraftment was associated with clinical response regardless of disease, differed among bacterial taxa, and was predicted by machine learning (ML). Other factors could influence engraftment, but evidence is unclear. Virome and fungome, have been linked to FMT success, but their engraftment kinetics is unknown. Host factors, i.e. genetics, gut immunity and microbial metabolites are supposed to play a role in engraftment, but supporting data are still absent. Crucial issues of the engraftment dynamics remain still unsolved, including 1) which are the interactions among host factors, microbial strains, and products during FMT; 2)whether and how they influence engraftment and 3) clinical outcomes.Our aim is to disentangle the dynamics of microbiome engraftment and correlate them to clinical outcomes. OBJECTIVES Primary objectives - To assess the longitudinal multidomain interactions of host and microbiome variables and their influence on microbial engraftment Secondary Objectives \- To assess the longitudinal multidomain interactions of host and microbiome variables and their influence on clinical outcomes Endpoints Primary - The longitudinal evaluation of multidomain interactions of host and microbiome variables throughout a multi-omics approach at 90 days after the last FMT Secondary \- The longitudinal evaluation of multidomain interactions of host and microbiome variables throughout a multi-omics approach at 7,30,180,360 days after the last FMT Procedures: Baseline assessment At baseline enrolled patients will be evaluated by the gastroenterology staff and endocrine and metabolic Unit staff of the Fondazione Policlinico Universitario A. Gemelli IRCCS and their demographic, clinical characteristics and laboratory data will be recorded, specifically: * Disease clinical and endoscopic activity for UC patients, expressed using Mayo score * Insulin sensitivity, assessed by Matsuda index and OGIS index after an oral glucose tolerance test (OGTT), for MetS patients. * Clinical characteristic, the occurrence of diarrhea and fecal C. difficil trial.show_full_description

Inclusion Criteria: Coorte: Patients affected by Ulcerative Colitis * Age ≥18 years. * UC with mild-to-moderate activity (total Mayo score 3-10 + endoscopic subscore≥1) (23) * UC during stable maintenance therapy (\> 8 weeks with salicylates, immunosuppressants); * Ability to give informed consent. Coorte: Patients affected by metabolic syndrome * Age ≥18 years. * Patients with MetS (high glycaemia levels (\> 100 mg/dL), hypertension (\> 130/85 mmHg), raised triglyceride levels (\> 150 mg/dL), low high-density lipoprotein cholesterol levels (\< 40 mg/dL in men; \<50 mg/dL in women), and abdominal obesity (waist circumference of \> 102 cm in men; \>88 cm in women) * Stable treatment (\> 8 weeks) of one of these disorders, included in MetS definition. * Ability to give informed consent Coorte: Patients affected by rCDI * Age ≥18 years * Mild recurrent Clostridioides difficile infection (26) * Ability to give informed consent. Exclusion criteria * Pregnancy, breastfeeding, and the refusal to follow an effective contraception method for all the study duration (for women). * Known active gastrointestinal disorders (e.g. infectious gastroenteritis except CDI, coeliac disease, irritable bowel syndrome, chronic pancreatitis, biliary salt diarrhoea) apart from UC, with clinical characteristics reports in inclusion criteria. * Antimicrobial treatment up to 4 weeks prior to screening visit (apart for patients with rCDI) * Previous colorectal surgery or cutaneous stoma * Critical and severe comorbidities * Inability to give informed consent.