symAtrial

Systems Medicine of Atrial Fibrillation

Atrial fibrillation is the most common arrhythmia with a high mortality rate. The overall objective of our interdisciplinary symAtrial consortium is to gain a better understanding of the development of atrial fibrillation and the underlying disease mechanisms by the use of systems medicine approaches.

The main focus of our investigation is the identification of disease-relevant genes and signaling pathways by molecular and animal model-based approaches, as well as the prospective investigation of these candidate genes in clinical and population-based cohorts. This understanding will help to improve current risk prediction tool to identify patients at "high-risk" for atrial fibrillation and - ultimately - precision therapy and prevention strategies for clinical use.
The partner within the symAtrial consortium combine different disciplines from Cardiology (Schnabel), epidemiology (Schnabel / Zeller), molecular biology (Zeller), bioinformatics (Heinig / Schillert) and data management (Schillert / Heinig) in a systems medicine approach. The consortium builds on existing clinical and population-based cohorts with detailed clinical data and biomaterials, large omics datasets and established molecular models.
Sub project 1 of symAtrial is dedicated to the establishment of the IT infrastructure and the harmonization of existing data sets. The remaining four sub projects will identify candidate genes of atrial fibrillation by analyzing various omics data sets (sub project 2), by using bioinformatics and systems biology approaches (sub project 3), by molecular characterization of the candidate genes (sub project 4), and by clinical-epidemiological risk prediction models (sub project 5).

Subprojects in symAtrial:

SP 1   Infrastructure of data management and data exchange

SP 2   Omics analyses and longitudinal gene expression analysis

SP 3   Regulatory networks and computational systems biology

SP 4   Molecular characterization of AF candidate genes and pathways and translation

SP 5   Genomic Epidemiology of Atrial Fibrillation

Keywords: atrial fibrillation, systems medicine, systems biology, UHZ