From Molecular phenotyping to personalized pharmacotherapy in cardiology

Aims of the project

Cardiovascular disease (CVD) represents the most important cause of morbidity and mortality in the EU.
Within the MATCH project an interdisciplinary and translational approach integrating knowledge from comprehensive Omics-based molecular phenotype analyses, cardiovascular epidemiology, imaging, bioinformatics, statistics and molecular biology will be taken.

Evidence-based medicine has considerably advanced the treatment of coronary heart disease (CHD), and its implementation was driven by multicenter interventional trials. However, most large‐scale clinical trials and therapies did not relevantly reduce the residual risk. Therefore, innovative approaches to foster individualized pharmacotherapy in CHD are urgently needed. The objective of MATCH is the identification of a biomarker signature, which associates with beneficial outcome on specific lipid therapy.

We will take an interdisciplinary approach integrating knowledge from various disciplines. Bioinformatics analyses will generate a molecular biomarker signature of responders (subjects with no clinical events during follow-up) versus non-responders (subjects with multiple events during follow-up) across cardiovascular lipid trials. This signature will be optimized in human cohorts and atherosclerosis-prone mouse models and validated in a second subset of patients. Finally, the signature shall be translated in an imaging-based OCT- (optical coherence tomography) trial longitudinally assessing the progress of coronary atherosclerosis in subjects with CHD.
For more information, please see the official project-site

Contribution of the Department of Medical Bioinformatics

Our department is involved in the Workpackages 2 and 5:

Work Package WP2: Bioinformatical derivation of molecular biomarker signature
Within MATCH a molecular biomarker signature to discriminate responders to various lipid therapies from non-resonders will be established. Based on the comprehensive set of Omics data established by WP1 (Hamburg), the application of bioinformatical, statistical and systems medicine approaches shall derive the best molecular biomarker signature for discrimination. 
Here in Göttingen, we will perform bioinformatical and statistical analyses to derive and validate biomarker signature.

Work Package WP5: Project coordination, management and ELSA
Efficient and effective project management ensures that the project meets the timeline and delivers the anticipated results.
Due to the clinical dimension of MATCH and the use of patient biomaterial and data within this project, ethical, legal and social aspects (ELSA) will be taken care of.

Project Partners



PD Dr. Mahir Karakas (Univerity Medical Center Hamburg-Eppendorf)
Prof. Tanja Zeller (University Medical Center Hamburg-Eppendorf)


Prof. Tim Beißbarth (University Medical Center Göttingen)
Prof. Dr. Massimiliano Caprio (IRCCS San Raffaele, Italy)
Dr. David-Alexandre Tregouet (Institute for Cardiometabolism and Nutrition Pierre & Marie Curie, Paris, France)

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