symAtrial - Systems Medicine of Atrial Fibrillation

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A multidisciplinary, integrative, systems-based approach to investigate the development and progression of atrial fibrillation.

Atrial fibrillation (AF) is the most common arrhythmia in the general population and is associated with an increased risk of stroke and heart failure. Substantial intra-individual differences in disease occurrence, progression and outcomes reflect how complex the disease is. So far, a handful of established classical risk factors including age, sex, hypertension, valvular disease, and heart failure are known. Additionally, the strong impact of a positive family history and recent studies that identified a number of rare and common genetic variants associated with AF suggest a genetic background contributing to AF susceptibility. However, the extent to which those variants influence AF is unclear and explain only a limited percentage of the heritability of AF. Moreover, despite many years of basic and clinical research, it is still only marginally understood how the different affected biological pathways ranging from ion channel modulation, inflammation, and atrial fibrosis converge to a final clinical phenotype of AF and its major complications, heart failure and stroke. Therefore, i) innovative approaches to enhance AF risk assessment are urgently needed and ii) a molecular understanding of the disease biology promises novel ways for risk assessment.

We are a systems medicine research consortium, funded within the framework of e:Med. The consortium comprises the following four partners:

  • Dr. Matthias Heinig, Helmholtz-Zentrum Munich, Institute of Computational Biology
  • Dr. Arne Schillert, Universität zu Lübeck, Institut für Medizinische Biometrie und Statistik
  • Dr. Renate Schnabel, Universitätsklinikum Hamburg-Eppendorf
  • Prof. Dr. Tanja Zeller, (Coordinator), Universitätsklinikum Hamburg-Eppendorf

Within our symAtrial consortium, we take an interdisciplinary systems medicine approach integrating knowledge from AF epidemiology, bioinformatics, statistics and molecular biology:

  • Use of interdisciplinary systems medicine approach to explore the molecular pathophysiology of atrial fibrillation.
  • Identification of new, molecular risk factors of atrial fibrillation.
  • Development and validation of risk (forecasts) algorithms, which integrate epidemiological and molecular information in bioinformatic approaches to identify high-risk individuals.
  • Development of methods and central units of data integration and system medical platforms within the consortium.


Our paper Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data appeared in PLoS ONE