Over the first 3 years of the project, researchers involved in WP1 used existing cohorts to analyze associations between dietary patterns and changes in various aspects of whole body metabolism and low grade inflammation. Association studies were performed between metabolic phenotypes, gut microbial signatures, and networks of specific bacterial groups, as well as metabolomic features. This work has led to several original publications. The integration of metabolomic profiling with gut metagenomic data has identified metabolomic-metagenomic networks associating with cardiometabolic risks. These new findings have generated hypotheses that will be tested in the new Metacardis cohort (WP3). Continuing analyses on data from legacy cohorts will be the subject of systems biology work in WP5.

WP2 provides consortium partners with a portfolio of experimental systems to generate material and information relevant to gut microbiota functions and molecular mediators. Until now, results from WP2 have demonstrated the pathophysiological consequences of human gut microbiota and gut microbial metabolites, which were identified from research activities in WP1. This work has mainly focused on in vivo rodent models (rat and mouse) using an experimental pipeline designed to assess a broad range of cardiometabolic phenotypes. Additionally, successful purification of active fractions of metagenomic clones are being tested in cellular systems, the relevance of which will be examined using translational in vivo rodent models. Finally, molecular mechanisms mediating the biological roles of gut microbial metabolites have been identified and provide information of gene and gene pathways linking gut microbiota with cardiometabolic phenotypes.

Since the beginning of the project, we have officially finished recruitment of the main cohort (WP3), with ongoing recruitment of a sub-group (obese patients undergoing bariatric surgery). As such, the main cohort consists of 8 groups: 1) Metabolic Syndrome, 2a) Obese, 2b) Obese with bariatric surgery, 3) T2DM, 4) Acute Coronary Artery Disease (CAD) (no Congestive Heart Failure (CHF)), 5) Chronic CAD (no CHF), 6) Chronic CAD with CHF, 7) Chronic CHF no CAD, 8) Healthy (control) patients. Currently, the collective cohort is over 2000 patients for which we have detailed clinical data. We have also obtained social (lifestyle, dietary habits, etc) and biological data (circulating hormones and inflammatory markers) along with clinical measurements, which will allow us to characterize our patient cohort. Through stringent database cleaning and management, we have identified potential confounders, regrouped patients into the proper groups based on clinical status, and excluded certain patients from cohort analysis. Collectively, this WP has been fundamental in ensuring high quality database delivery into upstream analysis of the cohort in WP5, which will answer the key questions of MetaCardis. The curation of the data were performed in order to obtain a “core cohort” which combines metagenomics ad metabolomic and clinical full data as a data set to address these prioritized questions.

In WP4, stool samples from the patients were received and stored at INRA. Total DNA was extracted from all samples and sequenced using an emerging technology, Ion Proton, which was benchmarked and found to be quicker, more robust, and reliable than Solid Wildfire.  Profiles of genes, metagenomic species, units, and mOTUs were generated for all samples and transferred to the data hub at EMBL. For metabolome analysis, 2162 urine and 2251 serum samples were profiled by 1H NMR spectroscopy. All data were pre-processed followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) analysis based on available clinical data (Age, Country, Gender, Pathology group). This data was collectively transferred to WP5 for systems biology analysis.

WP5 addresses the effort to go from massive parallel, high-dimensional -omics data to clinically applicable tools and findings, as well as to enable personalized medicine with regards to cardiovascular and metabolic conditions. Work so far has centered on preparing reception and processing WP1, 3, and 4 data. This includes storing and harmonizing data files so that the consortium can leverage partners’ expertise.. Likewise, the previous work in metabolic modelling, gut-specific annotations, dietary and other metadata representations, and machine learning techniques will allow MetaCardis to provide a unified understanding of microbiota’s implication in health and cardiometabolic disease progression. These data infrastructure and representation efforts have now been linked together with a repertoire of analysis techniques and algorithms for data integration, exploration, evaluation and visualization. These techniques have been evaluated, benchmarked and documented, and are accessible to consortium partners. Collectively, the synthesis of work across partners in the project will allow the proceeding to computational analysis on the novel datasets generated within the project.

Within WP6, we organized several fellowships for young investigators (doctoral and post-doctoral researchers) as an exchange between partners’ laboratories and to strengthen consortium collaboration and to increase knowledge sharing. In this light, we also organized several workshops on MetaCardis-related data and analysis. An internal exploitation panel is also established to monitor and gauge results of the project.

The project website is regularly updated and displays the publications and press articles on the project.

In WP8, the consortium organized the first exchange with an ethical expert on questions relating to data exploitation. Specifically, these questions were addressed in context of the researcher and clinician and how this can be disseminated to patients as well as patients’ expectations for the project. Additionally, as the consortium has generated large datasets, we have discussed the ethical obligations and implications in handling these datasets.

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