Cardiovascular Disease remains the leading cause of death in Germany, and is responsible for a major proportion of chronic diseases in the population as well as hospital admissions. An important research area is therefore the development of better preventive strategies to reduce the risk of complications such as heart attacks and strokes. The better early detection of an increased cardiovascular risk is therefore very important.
In the present project supported by the Einstein Foundation in a close international collaboration between Charité Universitätsmedizin Berlin and Professor Deanfield from the University College London (UK) together with the Berlin Institute of Health novel ways of early risk prediction for cardiovascular diseases, such as heart attack and stroke, could be developed and evaluated.
In the first project the impact of genetics (polygenic risk score) on early cardiovascular risk prediction was evaluated in a large population of > 350,000 people without known cardiovascular disease. The results of this collaborative project demonstrated that particularly in younger people (< 50 years) without know high cardiovascular risk, the prediction of the risk of heart attack and stroke was improved by including genetics to known cardiovascular risk factors. The findings of this project could be published in Lancet Digital Health are publicly available (Lancet Digit Health 2022: e84-e94).
In a further collaborative project the impact of the metabolic profile (from peripheral blood) for risk prediction of disease development was explored. Here the nuclear magnetic resonance (NMR)-spectroscopy based metabolmic profile was asessed for prediction of common diseases, such as diabetes, heart failure, coronary disease, arial fibrillation and others. The results of a 168 metabolite measurement in plasma in >100,000 people was used in a neural-network analysis for risk prediction. The metabolomic state added predictive information over comprehensive clinical variables for common diseases, including type 2 diabetes, and heart failure. Taken together, this study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of common diseases simultaneously. This international collaborative project is published in the journal Nature Medicine (Nat Med 2022 Nov; 28(11):2309-2320)) und publicly availabl.
In summary, the support of the Einstein Foundation enabled an international collaboration to study novel ways for early cardiovascular risk prediction, using advanced technologies such as polygenetic score analysis, metabolomics together with neural network-based analyses. The eraly risk detection is paticularly important for cardiovascular disease, since there are opportunities for disease prevention such as a more intense control of cardiovascular risk factors. We thank the Einstein Foundation for making this interesting and important work possible.