Eurach Research

PARNANT

Pathogenetic pathways in age-related neurodegenerations as novel therapeutic targets for Parkinson’s disease

    PARNANT
    • Project duration: -
    • Project status: finished
    • Funding:
      Excellence Science (Horizon 2020 /EU funding /Project)
    • Total project budget: €214,223.00
    • Institute: Institute for Biomedicine

    Parkinson’s disease (PD) is the second most common neurodegenerative disorder (after Alzheimer's) associated with oxidative stress and aging, and affects an estimated 1% of people worldwide over 60 years of age. The pathogenetic triggers of neurodegenerations are largely unknown. Current therapeutic interventions only partially alleviate symptoms and do not restore normal neuronal function or prevent progressive neurodegenerations. Identifying novel molecular targets and searching for therapeutic agents that block neurodegeneration and promote neuronal restoration is a key challenge in the field. Screening candidate genes from human PD GWAS through a human-synuclein Drosophila model, we have identified genes that rescue movement and lifespan phenotypes due to overexpression of synuclein. These candidate genes are thus evolutionarily conserved in both vertebrate and invertebrate animals. We have obtained previously isolated loss-of-function alleles of these genes and generated a transgenic C. elegans strain eraIs1 carrying a GFP-based reporter of alpha-synuclein overexpressed in DA neurons. This new reporter strain allows us to identify alleles that can positively or negatively alter neurodegeneration. We performed a reverse genetic screen of PD GWAS-based susceptibility genes for their ability to modulate toxicity of an alpha-Synuclein reporter in dopaminergic neurons of Caenorhabditis elegans. Obtained data revealed 28 PD risk genes and their associated pathways that can modulate neuronal formation of aSyn inclusions accompanied with neurodegeneration, and which provide new potential therapeutic targets for synucleinopathies.

    This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 845774

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