Systems Medicine of Heart Failure (SMART)

Executive Summary

e:Med Flyer 2016The cooperation project Systems Medicine of Heart Failure (SMART) focuses on researching risk factors of heart failures. The onset and course of heart failure (HF) is triggered by a complex regulatory network that includes stressors (pressure overload by individual anatomic hemodynamic settings), intrinsic (genes), environmental (regulating epigenetics), and modifying factors (such as hormones and the immune system). SMART aims to establish individualized strategies for the prevention and management of HF by early detection of the physiological, genomic, proteomic and hemodynamic mechanisms that lead from one common cause of ventricular dysfunction (pressure overload) to maladaptive remodeling and irreversible HF. To cope with the complexity of HF, SMART will interrelate models describing the interplay between genome, proteome and cell function, regulating hormones, tissue composition and hemodynamic whole organ function up to a whole body description of a patient and patient cohorts. The ultimate goal is to demonstrate proof-of-concept tools for predicting disease evolution and efficacy of treatment in a given patient. To achieve this task SMART will apply
– A modelling framework that couples multi-scale mechanistic models with in-depth genome/proteome, cell physiology and whole organ (biomechanical and fluid dynamic) models
– Subsequently, investigate methods validity and relevance for “quantitative prediction” of treatment outcome in a clinical proof-of-concept trial (demonstrator) of patients with aortic valve diseases.

 

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  • Nordmeyer, S., Kraus, M., Ziehm, M., Kirchner, M., Schafstedde, M., Kelm, M., Niquet, S., Stephen, M., Baczko, I., Knosalla, C., Schapranow, M.-P., Dittmar, G., Gotthardt, M., Falcke, M., Regitz-Zagrosek, V., Kuehne, T., Mertins, P.: Disease- and sex-specific differences in patients with heart valve disease: A proteome study. Life Sci Alliance. 6, e202201411 (2023).
  • Kraus, M., Mathew Stephen, M., Schapranow, M.-P.: Eatomics: Shiny exploration of quantitative proteomics data. Journal of Proteome Research. (2020).
  • Slosarek, T., Kraus, M., Schapranow, M.-P., Bottinger, E.: Qualitative Comparison of Selected Indel Detection Methods for RNA-Seq Data. International Work-Conference on Bioinformatics and Biomedical Engineering. bll. 166–177. Springer (2019).
  • Kraus, M., Hesse, G., Slosarek, T., Danner, M., Kesar, A., Bhushan, A., Schapranow, M.-P.: DEAME-Differential Expression Analysis Made Easy. Heterogeneous Data Management, Polystores, and Analytics for Healthcare. bll. 162–174. Springer (2018).
  • Kraus, M., Schapranow, M.-P.: An In-Memory Database Platform for Systems Medicine. Proceedings of the International Conference on Bioinformatics and Computational Biology. bll. 93–100. The International Society for Computers and Their Applications (ISCA) (2017).
  • Kraus, M., Niedermeier, J., Jankrift, M., Tietboehl, S., Stachewicz, T., Folkerts, H., Uflacker, M., Neves, M.: Olelo: a web application for intuitive exploration of biomedical literature. Nucleic acids research. (2017).
  • Schapranow, M.-P., Kraus, M., Danner, M., Plattner, H.: IMDBfs: Bridging the Gap between In-Memory Database Technology and File-Based Tools for Life Sciences. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine. bll. 1133–1139. IEEE (2016).

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