Prof. Dr. André Fischer
European Neuroscience Institute
Prof. Dr. Fabian Theis
Institute of Computational Biology
The role of microRNAome signatures during the longitudinal course of schizophrenia: Biomarkers and pathomechanisms
The pathogenesis of complex neuropsychiatric disorders such as schizophrenia is driven by variable combinations of environmental and genetic factors that can in- or decrease disease risk. Epigenetic processes have emerged as key regulators of genome-environment (GxE) interactions and thus gain increasing interest in neurosciences. In addition to histone-modifications and DNA-methylation, microRNAs were shown to mediate epigenetic processes. MicroRNAs have also recently been implicated with the pathogenesis of schizophrenia. Of note, there is first evidence that changes in the microRNA signature might be suitable as a blood biomarker for the prediction of disease pathogenesis and treatment efficacy. Here we provide preliminary data suggesting that the blood microRNAome could indeed be a suitable biomarker for longitudinal analysis. On this basis we will - for the first time - analyze the brain and blood microRNAome in animal models for schizophrenia-like phenotypes in a longitudinal manner with a specific focus on GxE interactions. Most importantly, we will entirely rely on next-generation-sequencing that will allow us to study the microRNAome plus other small non-coding RNAs in an unbiased and quantitative manner.
Furthermore, we will use a systems biology approach to decipher microRNAome changes linked to disease phenotypes and aim to detect novel pathomechanisms. The analysis of mouse models will be complemented by the longitudinal microRNAome analysis of blood samples from schizophrenia patients and healthy controls. Since we put a special emphasis on using comparable approaches in mouse models and in humans we are confident that our project will help identifying not only longitudinal biomarkers for the course of schizophrenia but also point to pathomechanisms which will help us to select target microRNAs for further mechanistic analysis.