Periodic Reporting for period 2 - CARDIATEAM (CARdiomyopathy in type 2 DIAbetes mellitus)
Reporting period: 2020-03-01 to 2021-02-28
Type 2 Diabetes (T2DM) epidemic is associated with serious comorbidities such as heart failure, the second most common cardiovascular disease after ischaemic heart disease in T2DM. CARDIATEAM is aiming to differentiate diabetic cardiomyopathy (DCM) against other forms of heart failure, identify its causal mechanism, and evaluate its impact on mortality. Thus, the identification of a novel phenotypic signature of DCM should allow to:
• predict cardiac function decline in T2DM patients
• allow for early preventive strategies
• facilitate tailored therapies to slow disease progression
• develop disease modeling for translatable preclinical models
Seven dedicated work packages (WP) have been set-up to establish a strong collaborative network of clinical and basic researchers. Enrolling 1,600 patients in a prospective clinical study, CARDIATEAM will provide a unique and highly standardized set of data and allow differentiation of related forms of heart failure. Deep phenotyping and unbiased machine learning will allow in a yet unrivalled precision to identify clusters of connected pathology, identification of affected biochemical pathways and specific biomarkers. A central database integrating historical data and data from clinical and experimental sources will permit novel bioinformatics-assisted visualization and modelling of interactions between phenotype, genetic, immune and metabolic pathways.
Building on these results, CARDIATEAM will enable DCM modelling, identify crucial pathophysiologic mechanisms and ultimately develop tailored treatments and robust preclinical models.
• predict cardiac function decline in T2DM patients
• allow for early preventive strategies
• facilitate tailored therapies to slow disease progression
• develop disease modeling for translatable preclinical models
Seven dedicated work packages (WP) have been set-up to establish a strong collaborative network of clinical and basic researchers. Enrolling 1,600 patients in a prospective clinical study, CARDIATEAM will provide a unique and highly standardized set of data and allow differentiation of related forms of heart failure. Deep phenotyping and unbiased machine learning will allow in a yet unrivalled precision to identify clusters of connected pathology, identification of affected biochemical pathways and specific biomarkers. A central database integrating historical data and data from clinical and experimental sources will permit novel bioinformatics-assisted visualization and modelling of interactions between phenotype, genetic, immune and metabolic pathways.
Building on these results, CARDIATEAM will enable DCM modelling, identify crucial pathophysiologic mechanisms and ultimately develop tailored treatments and robust preclinical models.
The second period was marked with the management of the COVID-19 pandemic and its sanitary measures, leading inevitably to a delay in the start of the clinical study.
The achievements of the organization of the clinical study for the first two periods of the CARDIATEAM projects are:
- Agreement on definitions and criteria for clinical events
- Localization of the protocol of the clinical trial and related documents in all countries
- Validation of study documents and of scientific protocol by regulatory agencies and ethical committees in France, Netherlands, Germany, UK and Spain
Against all adversities related to COVID-19 pandemic , remote solutions have been deployed by the coordination team in tight collaboration with local PI’s team to mitigate the impact of the sanitary crisis. The robust prescreening strategies deployed in each center, have ensured the recruitment of 29 patients in the French centres.
In this difficult period, all partners have undergone preparative and regulatory aspects to initiate enrolment for the clinical trial.
The required infrastructure to collect imaging data in the CARDIATEAM cohort has been installed. The CARDIATEAM web-based database platform is operational and has been successfully tested and validated. Participating centres are trained and certified by transferring collected data to the imaging core labs and uploading the measurements to a central repository. All data is transferred anonymous in a safe and secure manner. All data flows are thus in place and quality assurance measures have been taken and implemented. Hereto, a certification process has been put in place as well as continuous monitoring of the core-lab performance.
Data from recruiting sites are collected, structured and secured in a database developed and hosted at SIB. Clinical data from the recruited patients are collected via an eCRF system, developed by OPALE feeding into the database. A data transfer protocol has been implemented between the main data processing partners to securely push validated records into the central database. We have established pipelines for processing of clinical data into the database and have developed web-based mining tools to query the content of the database to allow live monitoring of collected data.
NL-HI together with other partners (INSERM and SIB) has set-up and tested the required methodology -unsupervised machine learning to analyze the future deep phenotypic data.
LIH-IBBL has elaborated standard operating procedures (SOP) to ensure standardized processes amongst all collection sites involved in the constitution of the prospective CARDIATEAM cohort, for sample collection, processing, storage and transfer to the central biobank. These SOPs provide the collection sites with clear instructions on the conditions under which the blood and urine samples have to be collected from the participants, and further processed to generate plasma, serum, buffy coat and urine derivatives of high and standardized quality. UNITO and Inserm have coordinated and reviewed these SOP.
LIH-IBBL has started with the production and shipment of sample collection kits to registered clinical sites.
Concerning animal model, WP7 partners have now provided an overview of existing preclinical models of metabolic disorders pertinent to the project. Four interesting models have been identified within the consortium and thoroughly discussed in monthly telephone conference between WP7 partners.
The achievements of the organization of the clinical study for the first two periods of the CARDIATEAM projects are:
- Agreement on definitions and criteria for clinical events
- Localization of the protocol of the clinical trial and related documents in all countries
- Validation of study documents and of scientific protocol by regulatory agencies and ethical committees in France, Netherlands, Germany, UK and Spain
Against all adversities related to COVID-19 pandemic , remote solutions have been deployed by the coordination team in tight collaboration with local PI’s team to mitigate the impact of the sanitary crisis. The robust prescreening strategies deployed in each center, have ensured the recruitment of 29 patients in the French centres.
In this difficult period, all partners have undergone preparative and regulatory aspects to initiate enrolment for the clinical trial.
The required infrastructure to collect imaging data in the CARDIATEAM cohort has been installed. The CARDIATEAM web-based database platform is operational and has been successfully tested and validated. Participating centres are trained and certified by transferring collected data to the imaging core labs and uploading the measurements to a central repository. All data is transferred anonymous in a safe and secure manner. All data flows are thus in place and quality assurance measures have been taken and implemented. Hereto, a certification process has been put in place as well as continuous monitoring of the core-lab performance.
Data from recruiting sites are collected, structured and secured in a database developed and hosted at SIB. Clinical data from the recruited patients are collected via an eCRF system, developed by OPALE feeding into the database. A data transfer protocol has been implemented between the main data processing partners to securely push validated records into the central database. We have established pipelines for processing of clinical data into the database and have developed web-based mining tools to query the content of the database to allow live monitoring of collected data.
NL-HI together with other partners (INSERM and SIB) has set-up and tested the required methodology -unsupervised machine learning to analyze the future deep phenotypic data.
LIH-IBBL has elaborated standard operating procedures (SOP) to ensure standardized processes amongst all collection sites involved in the constitution of the prospective CARDIATEAM cohort, for sample collection, processing, storage and transfer to the central biobank. These SOPs provide the collection sites with clear instructions on the conditions under which the blood and urine samples have to be collected from the participants, and further processed to generate plasma, serum, buffy coat and urine derivatives of high and standardized quality. UNITO and Inserm have coordinated and reviewed these SOP.
LIH-IBBL has started with the production and shipment of sample collection kits to registered clinical sites.
Concerning animal model, WP7 partners have now provided an overview of existing preclinical models of metabolic disorders pertinent to the project. Four interesting models have been identified within the consortium and thoroughly discussed in monthly telephone conference between WP7 partners.
CARDIATEAM will go beyond the state-of-the-art since it will investigate mechanisms underlying DCM and prognosis.
The expected results of CARDIATEAM will be
• establishment of a prospective cohort of 1,600 patients within 2 years and with a follow-up of 3 years, phenotyping the patients with echocardiography, CMR, retinography and -omics
• Application of unsupervised machine learning algorithms to improve cardiac phenotyping & identification of DCM (WP4)
• Provide a sex- and age- based stratification approach of T2DM patients at risk of DCM (WP 2)
• Identification of causal mechanisms and pathways responsible for DCM (WP 2, WP3, WP5 & WP7)
• Identification of new potential therapeutic targets for preventing or alleviating DCM (WP6)
• Application of disease modelling to develop DCM preclinical models (WP7)
• New taxonomy of DCM to be communicated to health agencies, practitioners and patients (WP1)
The results of CARDIATEAM will impact clinical care with the stratification of patients into risk groups of developing DCM, earlier diagnosis of DCM and an improvement of therapy thanks to better assessment of underlying pathophysiology and identification of new biomarkers.
The outcome and results of CARDIATEAM will have significant impact on the efficiency of R&D in the field of Diabetes & Cardiovascular Disease.
The deep molecular and phenotypic characterization of DCM with the discovery and validation of respective biomarkers will allow an improvement in developing therapeutic options by:
- discovery and validation of biomarkers being predictive for risk and progression to DCM as well as to monitor efficacy of treatment options.
- development appropriate (animal) models of relevance for human DCM to profile and develop drug candidates for this medical indication.
- stratification of patients with DCM for clinical drug trials; this would enable smaller and focused clinical studies to evaluate efficacy of drug candidates in this indication earlier, faster and cheaper to progress and introduce them into clinical practice.
SMEs involved in CARDIATEAM will strengthen their visibility in Europe. Finally, DCM cluster analysis will potentially allow the rational repositioning of existing treatments.
The expected results of CARDIATEAM will be
• establishment of a prospective cohort of 1,600 patients within 2 years and with a follow-up of 3 years, phenotyping the patients with echocardiography, CMR, retinography and -omics
• Application of unsupervised machine learning algorithms to improve cardiac phenotyping & identification of DCM (WP4)
• Provide a sex- and age- based stratification approach of T2DM patients at risk of DCM (WP 2)
• Identification of causal mechanisms and pathways responsible for DCM (WP 2, WP3, WP5 & WP7)
• Identification of new potential therapeutic targets for preventing or alleviating DCM (WP6)
• Application of disease modelling to develop DCM preclinical models (WP7)
• New taxonomy of DCM to be communicated to health agencies, practitioners and patients (WP1)
The results of CARDIATEAM will impact clinical care with the stratification of patients into risk groups of developing DCM, earlier diagnosis of DCM and an improvement of therapy thanks to better assessment of underlying pathophysiology and identification of new biomarkers.
The outcome and results of CARDIATEAM will have significant impact on the efficiency of R&D in the field of Diabetes & Cardiovascular Disease.
The deep molecular and phenotypic characterization of DCM with the discovery and validation of respective biomarkers will allow an improvement in developing therapeutic options by:
- discovery and validation of biomarkers being predictive for risk and progression to DCM as well as to monitor efficacy of treatment options.
- development appropriate (animal) models of relevance for human DCM to profile and develop drug candidates for this medical indication.
- stratification of patients with DCM for clinical drug trials; this would enable smaller and focused clinical studies to evaluate efficacy of drug candidates in this indication earlier, faster and cheaper to progress and introduce them into clinical practice.
SMEs involved in CARDIATEAM will strengthen their visibility in Europe. Finally, DCM cluster analysis will potentially allow the rational repositioning of existing treatments.