Periodic Reporting for period 1 - TO_AITION (A high-dimensional approach for unwinding immune-metabolic causes of cardiovascular disease-depression multimorbidities)
Periodo di rendicontazione: 2020-01-01 al 2021-06-30
Depression is a common and serious comorbidity of cardiovascular disease (CVD) affecting one in three patients, among which women earlier and more frequently. Depression increases the risk for CVD development, acute events and mortality by >2 fold, independently of traditional risk factors, and constitutes an enormous socioeconomic burden in terms of morbidity, mortality and healthcare costs. Still, the patients at risk, disease trajectories and causative mechanisms involved remain unknown.
TO_AITION addresses the hypothesis that immune-metabolic dysregulation, occurring as a result of genetic, lifestyle and environmental risk factors ‘training’ innate immunity, drives low grade systemic inflammation leading to the development of CVD-depression comorbidity.
It integrates basic (cell models, immune-metabolic mechanisms, myeloid cell reprogramming), preclinical (animal models, CRISPR genome editing) and clinical (longitudinal cohorts with comprehensive existing data) research, in order to characterise immune-metabolic mechanisms driving CVD-depression comorbidity, identify new biomarkers and develop novel tools for the diagnosis, prognosis and monitoring of patients.
Effective patient-oriented awareness actions, dissemination, exploitation and management activities are also provisioned. TO_AITION will therefore rationally change our current understanding of the causative mechanisms driving CVDdepression comorbidity, unravelling patients’ complexity and improving their diagnosis, monitoring and management.
TO_AITION addresses the hypothesis that immune-metabolic dysregulation, occurring as a result of genetic, lifestyle and environmental risk factors ‘training’ innate immunity, drives low grade systemic inflammation leading to the development of CVD-depression comorbidity.
It integrates basic (cell models, immune-metabolic mechanisms, myeloid cell reprogramming), preclinical (animal models, CRISPR genome editing) and clinical (longitudinal cohorts with comprehensive existing data) research, in order to characterise immune-metabolic mechanisms driving CVD-depression comorbidity, identify new biomarkers and develop novel tools for the diagnosis, prognosis and monitoring of patients.
Effective patient-oriented awareness actions, dissemination, exploitation and management activities are also provisioned. TO_AITION will therefore rationally change our current understanding of the causative mechanisms driving CVDdepression comorbidity, unravelling patients’ complexity and improving their diagnosis, monitoring and management.
During this period, significant progress has still been realized in several areas as highlighted below.
First, the TO_AITION cloud platform has been implemented, enabling data storage and processing of the many datasets of the project. Harmonization activities of the various cohorts’ datasets have also taken place, preparing the ground for subsequent analyses. The enrichment of TO_AITION key datasets has started.
For the analysis of the various cohorts, various methodologies are evaluated, and new analytical and computational models, and pipelines, are under development. The construction of multiplex disease networks, the identification of shared risk markers common to both CVD outcomes and depression, and the uncovering of synergistic associations within disease networks and markers linked to multimorbidity has started. Initial exploratory analyses have been performed using datasets from the DETECT, NESDA, LURIC, YFS and OPUS studies.
Work to implement and evaluate a range of causal inference methods deployed in the networks generated has started. These tools are addressed in order of increasing biological insight and interpretability, from identification of likely driver nodes, to rule-based network causal inference, to finally Mendelian randomization coupled with machine learning.
The development of purpose-built human cell-based and animal models for the evaluation of causality of novel factors and pathways identified has also been initiated.
For the Identification of novel biomarkers for the diagnosis, prognosis and monitoring of CVD-depression co/multimorbidities, a novel and computationally efficient methodology capable of predicting the significant coronary stenosis has been developed and is used to analyze medical data from the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort.
Regulatory and ethical aspects of the project, including Ethics approval forms, establishment of an Ethics Advisory Board, access rights, compliance with the GDPR etc, have also been effectively dealt with during this period. Dissemination, exploitation and awareness activities have started and include a project website videos and interviews of TO_AITION researchers, an electronic newsletter, social media accounts, printed material, awareness-raising activities from the European Society of Cardiology etc.
Finally, an efficient management structure dealing with contractual, financial and legal administration, as well as day to day management has been implemented.
First, the TO_AITION cloud platform has been implemented, enabling data storage and processing of the many datasets of the project. Harmonization activities of the various cohorts’ datasets have also taken place, preparing the ground for subsequent analyses. The enrichment of TO_AITION key datasets has started.
For the analysis of the various cohorts, various methodologies are evaluated, and new analytical and computational models, and pipelines, are under development. The construction of multiplex disease networks, the identification of shared risk markers common to both CVD outcomes and depression, and the uncovering of synergistic associations within disease networks and markers linked to multimorbidity has started. Initial exploratory analyses have been performed using datasets from the DETECT, NESDA, LURIC, YFS and OPUS studies.
Work to implement and evaluate a range of causal inference methods deployed in the networks generated has started. These tools are addressed in order of increasing biological insight and interpretability, from identification of likely driver nodes, to rule-based network causal inference, to finally Mendelian randomization coupled with machine learning.
The development of purpose-built human cell-based and animal models for the evaluation of causality of novel factors and pathways identified has also been initiated.
For the Identification of novel biomarkers for the diagnosis, prognosis and monitoring of CVD-depression co/multimorbidities, a novel and computationally efficient methodology capable of predicting the significant coronary stenosis has been developed and is used to analyze medical data from the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort.
Regulatory and ethical aspects of the project, including Ethics approval forms, establishment of an Ethics Advisory Board, access rights, compliance with the GDPR etc, have also been effectively dealt with during this period. Dissemination, exploitation and awareness activities have started and include a project website videos and interviews of TO_AITION researchers, an electronic newsletter, social media accounts, printed material, awareness-raising activities from the European Society of Cardiology etc.
Finally, an efficient management structure dealing with contractual, financial and legal administration, as well as day to day management has been implemented.
TO_AITION aims to rationally change our current understanding of the causative mechanisms driving CVD-depression co/multimorbidities, unravelling patients’ complexity, improving the diagnosis, monitoring and management of these diseases, and opening up new avenues of research and new opportunities for potential prophylactic and therapeutic intervention.
To achieve its ambitious yet realistic targets, TO_AITION takes several bold steps beyond the state-of-the-art in all of its objectives, and will lead to multiple advances in the field, many of groundbreaking nature, including:
-The epidemiology of CVD-depression co/multimorbidity: risk, susceptibility factors and disease trajectories
-The current knowledge on the heterogeneity of depression and its relationship to the development of CVD comorbidity and outcomes
The characterization of novel CVD-depression multimorbidity phenotypes and pathobiological states
-The unwinding of novel causative mechanisms driving CVD-depression co/multimorbidity
-The identification of novel biomarkers for CVD-depression multimorbidity and development of a new biomarker test
-The development of innovative predictive multi-scale models of disease risk for improved patient stratification and management
By exploring unique longitudinal cohorts, biobanks and registries of individuals with co/multimorbidities, and existing multi-omics data, and defining disease phenotypes and pathobiological states, the project
This will bring about a step-change in the way patients are stratified, proposing patient stratification on the basis of the underlying pathobiology and presence or risk of co/multimorbidity. It will also characterize causative mechanisms of co/multimorbidity, supporting the development of disease mechanism-based targeted interventions for CVD-depression co/multimorbidities of improved efficacy, predictable drug-drug interactions and reduced side effects.
This will thus lead to earlier diagnosis and better treatment of CVD-depression co/multimorbidities, and improved healthcare of patients, while promoting research and innovation, and supporting the development and growth of relevant biotechnology and pharmaceutical industries, particularly small or medium-sized enterprises (SMEs).
To achieve its ambitious yet realistic targets, TO_AITION takes several bold steps beyond the state-of-the-art in all of its objectives, and will lead to multiple advances in the field, many of groundbreaking nature, including:
-The epidemiology of CVD-depression co/multimorbidity: risk, susceptibility factors and disease trajectories
-The current knowledge on the heterogeneity of depression and its relationship to the development of CVD comorbidity and outcomes
The characterization of novel CVD-depression multimorbidity phenotypes and pathobiological states
-The unwinding of novel causative mechanisms driving CVD-depression co/multimorbidity
-The identification of novel biomarkers for CVD-depression multimorbidity and development of a new biomarker test
-The development of innovative predictive multi-scale models of disease risk for improved patient stratification and management
By exploring unique longitudinal cohorts, biobanks and registries of individuals with co/multimorbidities, and existing multi-omics data, and defining disease phenotypes and pathobiological states, the project
This will bring about a step-change in the way patients are stratified, proposing patient stratification on the basis of the underlying pathobiology and presence or risk of co/multimorbidity. It will also characterize causative mechanisms of co/multimorbidity, supporting the development of disease mechanism-based targeted interventions for CVD-depression co/multimorbidities of improved efficacy, predictable drug-drug interactions and reduced side effects.
This will thus lead to earlier diagnosis and better treatment of CVD-depression co/multimorbidities, and improved healthcare of patients, while promoting research and innovation, and supporting the development and growth of relevant biotechnology and pharmaceutical industries, particularly small or medium-sized enterprises (SMEs).