Feature Articles

LiSyM Researches How Genes Impact NAFLD

Genes have an effect on many diseases. According to Professor Dr. med. Frank Lammert, “The genetic profile plays an important role in NAFLD (nonalcoholic fatty liver disease).”
Lammert, who is a member of the LiSyM research network, studies the gene variants that influence how susceptible people are to NAFLD. Other gene variants accelerate the course of the disease, or they increase the risk of complications. “How well therapies work also depends on genes,” Lammert explains, adding: “We need more large-scale clinical studies that combine patients’ clinical and molecular profiles with genetic data!” He believes this is the only way patients can benefit from the latest findings in genetic research.
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The Metabolic Liver Disease NAFLD: A Growing Health Problem

The World Gastroenterology Organization WGO and other health care associations identify the metabolic liver disease, NAFLD (nonalcoholic fatty liver disease), as a “growing public health problem.” As many as one in four people worldwide has a nonalcoholic fatty liver today. The number is even as high as 40% in the US and Europe, according to estimates from the European Association for the Study of the Liver (EASL). The organization believes that 12 million are affected in Germany.
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The Holy Grail of Systems Biology

LiSyM director Professor Dr. med. Peter Jansen believes that mathematical models are indispensable for the research of biological systems.

Human bodies are complex biological systems, with countless reactions taking place in every cell. These reactions are sometimes interconnected or have an impact on further processes. Furthermore, cells, tissue, and organs are closely connected. Professor Dr. med. Peter Jansen, director of the LiSyM research network, believes that the research of systems like these, which consist of multilayered processes, interactions, and dependencies, needs mathematical models. Only models that simulate biological systems on computers make it possible to assemble the existing mass of heterogeneous data into dynamic reproductions in a meaningful way. Mathematical models enable systems researchers to deliver results more quickly and successfully. The idea that digital computers can play an essential role in this research is older than the machines themselves.
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