The scientific rationale for joint research is represented by the fact that MASLD is generally silent, i.e. has few or no symptoms and is often diagnosed when dangerous comorbidities have already developed. Thus, the prevention of MASLD is of critical importance, especially in the high-risk patients (obese, T2D, hypertriglyceridemic). 

The main challenge is to uncover mechanisms that distinguish high-risk patients who develop steatosis from those who do not, which is a possible avenue for the discovery of novel therapeutics strategies against MASLD. Gut dysbiosis and disruption of the gut-liver axis have been linked with the pathogenesis of MASLD, so dietary modifications, probiotics, prebiotics, and fecal microbiota transplantation have all been proposed as its potential microbiota-based therapeutic strategies. However, very few studies so far have focused on the use of bacterial metabolites or their synthetic derivatives, some of which have exhibited encouraging results in improving MASLD in clinical trials. 

Work package 2 will include two research tasks:

1. μMark. Within this task the  analysis of gut microbiota diversity and function in stool samples from high-risk patients without confirmed steatosis, and matched MASLD patients will be performed, followed by bioinformatics data interpretation and pathway analysis. This will provide a metagenomic signature and highlight the MASLD-specific metabolic pathways.

2. LipoMark. The analysis of the lipid profile and bacterial metabolites in the plasma samples from the same groups of patients, by using untargeted lipidomics and targeted metabolomics will be performed, followed by bioinformatic and multivariate statistical analysis. The expected outcome is the specific lipidomic signature for MASLD patients, as the fingerprint of hepatic metabolic dysfunction, together with the identification of potentially beneficial bacterial metabolites. The data integration in the systems biology approach will be used to identify specific pathways and molecules associated with the disease and potentially guide the discovery of disease biomarkers and potential therapeutic targets.