Building a Unique Patient Cohort and Data Infrastructure
Since its launch, CARDIATEAM has built a large, deeply characterized group of volunteers from across Europe. By the end of the most recent period (February 2025), 1,219 patients have been recruited, including people with and without type 2 diabetes and with different heart conditions. Recruitment was expanded and adapted to overcome challenges, such as those posed by the COVID-19 pandemic, with additional French centers and increased targets at some hospitals.. The infrastructure for collecting patient data-including advanced heart imaging (echocardiography, cardiac MRI), eye scans, and blood samples- is now fully operational, supported by a secure web-based database. This database integrates clinical, imaging, and molecular data, ensuring high-quality, standardized information for analysis.
Data Quality, Monitoring, and Analysis
All 17 participating centers are actively uploading data, with over 2,500 imaging studies and 290,000 data entries reviewed to date. Automated tools and dedicated data scientists have been deployed to monitor data quality, identify inconsistencies, and ensure the integrity of the information collected. Regular meetings and training sessions keep all partners aligned and maintain high standards across the network. Tests show that the quality of the imaging data is excellent and matches international standards.
Innovative Machine Learning and Pheno-Mapping Approaches
CARDIATEAM stands out for its use of advanced computational methods, including unsupervised machine learning and clustering, to analyze the large and complex dataset. These techniques help identify subgroups of patients with similar disease patterns and uncover hidden links between risk factors and heart dysfunction. Early analyses have highlighted the importance of metabolic and immune pathways in the development of DCM, pointing to potential new avenues for diagnosis and treatment.
Biomarker Discovery and Molecular Research
A key part of the project is the analysis of multiple layers of biological data-genes, proteins, and metabolites-from patient samples. This “omics” approach is revealing molecular signatures that may predict who is most at risk for DCM or who may benefit from specific treatments. Collaboration with our industry partners has enabled the measurement of additional biomarkers, enriching the dataset and increasing the potential for discovery.
Preclinical Models and Experimental Research
To complement patient studies, CARDIATEAM is developing and refining animal models that mimic DCM. These models help researchers explore how factors like diet, aging, and genetics contribute to heart disease in diabetes. Recent experiments have focused on mice exposed to metabolic stress, offering insights into the progression from metabolic disorders to heart failure. Tissue samples from these studies are being analyzed to identify early changes and potential therapeutic targets.
Knowledge Sharing and Scientific Impact
The consortium regularly meets to discuss progress, share results, and plan next steps. CARDIATEAM has published review articles on experimental models and the role of epigenetics in DCM, contributing to the global understanding of this condition. The project is active in scientific conferences and public events, promoting collaboration and raising awareness about the importance of personalized medicine in diabetes and heart disease.
Our next steps will focus on finding clear links between specific biological markers and clinical outcomes. By combining advanced data analysis with laboratory research, we hope to uncover the mechanisms behind diabetic cardiomyopathy.
