The visualization of complex data using network technologies often makes visible what otherwise remains hidden - and this is also the case in medicine. For several years, researchers at CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences (ÖAW), St. Anna Children's Cancer Research, the University of Vienna and Max Perutz Labs have been working on using network technology to gain a better systemic, molecular understanding of rare diseases and immune and inflammatory diseases. In their most recent studies, the scientists used network-based analyses to identify new molecular mechanistic similarities between rare diseases of the immune system. This allowed them to reclassify them. By comparing the data with clinical data, the scientists were able to show that patients with diseases within a classification group also responded to the same drugs, as they have now described in the journal "Science Advances".
New classification enables more targeted therapies
For their study, the researchers examined around 200 rare immune disorders with inflammatory phenotypes. The network-based analysis of protein-protein interactions revealed similarities in the molecular mechanisms behind these diseases. Through these analyses, the diseases were reclassified, and the researchers subsequently calculated which therapies could yield the best results for each respective group. “Compared to existing clinical data, the new disease classification allows for a much better prediction of promising therapies compared to the previous approach. Network biology allows us to gain deeper insights into the intricate interplay between the immune system and diseases. This, in turn, enables us to develop more targeted and personalized approaches for diagnosis and treatment” explained Kaan Boztug, researcher at the OeAW and Director of St. Anna Children's Cancer Research.
Similar patterns in autoimmune and autoinflammatory diseases
The results also indicate that numerous autoimmune and autoinflammatory diseases such as chronic inflammatory disorders, multiple sclerosis, systemic lupus erythematosus, and type 1 diabetes are closely linked. The study’s first author Julia Guthrie from Max Perutz Labs explained: “We were able to identify a group of key genes and their interaction partners that are central to homeostasis. We refer to this network of key genes as ‘AutoCore’. In autoimmune and autoinflammatory diseases, the 'AutoCore' resides right at the center of the associated genes. Additionally, we identified 19 other subgroups that are intended to provide us with better insights into homeostasis and immune system deregulation.”
Taking a broader perspective
While conventional approaches often categorize immune system disorders according to specific body regions and thus view them in isolation, a systemic approach aims to offer a more detailed picture of underlying mechanisms. Jörg Menche, researcher at the University of Vienna and Max Perutz Labs, explained: “We increasingly recognized the conceptual and practical limitations of the traditional paradigm of ‘one gene, one disease’ in the research of rare diseases. This hinders our understanding of the complex molecular network through which the components of the immune system are orchestrated. Therefore, we developed a visualization in the form of a multidimensional network that depicts all currently known monogenic immune defects underlying autoimmunity and autoinflammation, as well as their molecular interactions. As a result, we can see how closely genes are interconnected in rare diseases.”
The acquired data also provide a crucial foundation for identifying better treatment options for specific groups of disorders.
