Neural plasticity in an iPS-cell based model of Alzheimerʼs disease and schizophrenia

Introduction Neurodegenerativ disease or psychiatirc disorders like Alzheimerʼs disease (AD) and schizophrenia (SCZ) are associated with a loss of neurons. Neurodegeneration is regulated by aging or a defect occuring during neural development. A loss of functional neurons affects the neural plasticity – the ability of the brain to adapt on stimuli of our environment. Additionally, from epidemological studies of the last years, we know many common genetic risk factors for both disease, leading to the question, if we can also find in iPS-cell derived neurons of AD and schizophrenia patients a changed neural plasticity compared to healthy controls.

Methods We established an iPS cell-based model, which allows us to analyze neural plasticity in a human in vitro model. We successfully differentiated the iPS cells to neural stem cells, neural progenitor cells, and finally to functional neurons.

Results The neural differentiation was verified by the expression of different markers by FACS, QPCR or immunofluorescence analysis. Gene expression analysis revealed in NSCs of AD patients compared to healthy controls show enhanced or increased expression of aging markers. Very interesting was the significant reduced FGF2 protein amount in AD-specific NSCs. FGF2 is not only described as an aging marker; more important for us FGF2 is a key protein during the neural development. Further, first results of proteome analysis, shows strong differences between the protein expression in neurons of SCZ compared to a healthy control. First pathway analysis demonstrate an association of the identified proteins with neural development.

Conclusion The introduced iPS-cell based model allows us to analyze cellular mechanisms of diseases that affect the neural network in a human in vitro model. With this model, we also get first hints, for changes in neural plasticity shared between AD and SCZ. In the future, we plan electrophysiological analysis and defined analysis of plasticity markers.