Neurodegenerative diseases such as Alzheimer's Disease, Parkinson's Disease or Glaucoma are not only socially devastating, but their increasing incidence also poses an economic threat up to a level where an estimated 1% of the global gross domestic product is spent on caregiving efforts. Since many of these diseases are increasingly common with age, this is especially the case for the EU, where life expectancy is on a constant rise.
In the last 20 years, many risk factors have been identified that link genetic variants to disease susceptibility. While more than a few hundred of these commonly called “risk genes” are known, efforts to translate these insights into improved diagnostics or therapy have lead virtually nowhere. One of the reasons is that the vast majority of genetic variants linked to complex neurodegenerative disorders are surprisingly often found in non-coding regions of the genome and hence do not overlap with protein-coding genes. It is hypothesized that these non-coding variants are linked to a dysregulated gene expression landscape, which are inherently cell type-specific. However, it is currently unknown for many of these variants which cell type they exert their effect in and how strong this effect is. Without this knowledge, efforts to develop targeted therapies are tainted by increased an increased risk of off-target effects. Since cell types always work in networks, a much better understanding of the molecular cascades and their interplay that ultimately lead to the neurodegenerative phenotype is needed in order for the scientific community to develop better diagnostic and therapeutic approaches.
The overarching goal of this project is to develop a method suitable to monitor and functionally interrogate these regions in a cell type-specific way. This is done in vivo with the help of mouse models.
This project officially ended in May 2020. Preliminary results suggest that our approach is expedient, feasible and translatable to disciplines outside of the neurodegeneration research field. Currently, we are collecting more data, after which the results will be disseminated to the scientific community.
