Using data from large-scale population-based epidemiological studies, in-house data, as well as publicly available omics datasets, we have established pipelines for computational analyses with the goals of (i) developing of personalized diagnostic and risk prediction tools for patients with cardiovascular diseases and (ii) detecting promising drug targets with causal effects in the pathophysiology of vascular pathologies. We analyze human genomic, transcriptomic, proteomic, and metabolomic data.
Specifically, we are working on the following domains:
We have established and operate the AtherOMICS Biobank, a biobank of human atherosclerotic plaque samples. The biobank includes plaque and peripheral blood samples from patients undergoing carotid and femoral endarterectomy in collaboration with the Vascular Surgery department of the LMU University Hospital (Prof. Dr. Tsilimparis & Dr. Rantner), as well as intracranial vessel samples from patients donating their brain post mortem in collaboration with the Neurobiobank Munich (NBM, Center for Neuropathology and Prion Research). The sample collection is coupled with a comprehensive patient data collection including demographics, clinical information, laboratory results, and imaging studies. The goals of the biobank include: (i) the deep phenotyping of human atherosclerosis, (ii) the development of novel in vivo diagnostics for atheroprogression, and (iii) the discovery and validation of novel therapeutic targets for atherosclerosis.
The biobank includes the following investigations:
Ethics: The study has received ethical approval from the Ethical Committee of the Medical Faculty of the LMU University Hospital in Munich.
Acknowledgements: We would like to cordially thank all the patients taking part in the process whose consent is very important in providing a meaningful contribution to biomedical science.
We develop tools for improved diagnosis and more efficient risk stratification of patients at risk of cardiovascular disease. We analyse omics, physiological data, and medical images with advanced machine learning methods with the following goals:
We are interested in translating our developed tools, biomarkers, and promising drug targets to diagnostics and therapeutics that will benefit patients’ lives. For this reason, we are involved in clinical research including both observational studies and interventional trials in patients with cerebrovascular disease.
