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Despite the advances in the identification of genes involved in Parkinson’s disease (PD), there are still

appreciable gaps in our understanding of the mechanisms underlying the neurodegenerative process

and its relation to environmental factors in PD. Therefore we are proposing a comprehensive

approach based on (i) a unique collection of families with autosomal dominant and autosomal

recessive PD and (ii) large cohorts of clinically well-defined sporadic PD patients from different

populations worldwide for (iii) genetic studies and (iv) assessment of environmental modifiers that will

translate into (v) functional validation studies in patient-derived cellular models. Using next

generation sequencing strategies including exome sequencing in multiplex families and

targeted resequencing in sporadic PD patients, we will disentangle the complex genetic architecture

of PD in different populations and attempt to better define the underlying functional variants in

disease-associated GWAS loci. Newly identified genetic variants are filtered for pathogenic relevance

based on novel prediction algorithms combined with unique expression databases and

replicated in large cohorts of PD patients . Here the Genetic Epidemiology of Parkinson’s disease

Consortium (GEO-PD) provides a unique resource with a large number of DNA samples and

environmental exposure data of PD patients and controls from different populations worldwide.

Subsequent assessment of disease modifiers includes two complementary approaches: Mendelian

randomization , and gene-environment interaction studies . In order to validate genetic risk

variants, functional studies on patient-based material will be performed. Here the applicants

provide unique expertise for fibroblasts- and induced-pluripotent-stem-cells-(iPSC)-derived

cellular models of PD and a large repository of biomaterials from carriers of PD-associated

mutations. Established readouts allow to study functional effects of identified genetic risk factors and

will be used to assign novel disease genes and risk variants to defined pathogenic pathways.

Moreover patient-based cellular models will be challenged with environmental risk factors identified

as modulators of disease . We expect that the combination of comprehensive state-of-the-art genetic

technologies with a detailed ascertainment of environmental modifiers will provide important clues to

decipher the complexity of neurodegeneration in PD. Subsequent modelling of PD in patient-based

material allows to discover molecular mechanisms and pathways involved and leading to therapies

for this still incurable disease.


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