In recent years there has been major advances in the identification of genes involved in Parkinson's disease (PD). Nevertheless, there are still gaps in our understanding of the disease mechanisms. In this study we have used a comprehensive approach based on a unique collection of families with PD and large numbers of clinically well-defined patients from different populations worldwide for genetic and environmental risk factors. Subsequently, genetic factors have been studied in cell models derived from the patients.
We have used modern gene sequencing techniques to identify the genetic risk factors involved in PD. The studies have used unique databases and collections of biological material from many countries. Analyses of genetic and environmental risk factors have been performed with novel statistical and computational methods. These analyses are still ongoing.
We expect that the combination of state-of-the-art genetic technologies with a detailed ascertainment of environmental modifiers will provide important clues to decipher the complexity of the disease process in PD. Studies of PD in patient-based material allows to discover molecular mechanisms and leading to therapies for this still uncurable disease.
Despite the advances in the identification of genes involved in Parkinson's disease (PD), there are still gaps in our understanding of the mechanisms underlying the neurodegenerative process and its relation to environmental factors. We are proposing a co mprehensive 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 resequenc ing 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 filtere d for pathogenic relevance based on novel prediction algorithms combined with unique expression databases and replicated in large cohorts of PD patients.
Subsequent assessment of disease modifiers includes two complementary approaches: Mendelian randomi zation, and gene-environment interaction studies. In order to validate genetic risk variants, functional studies on patient-based material will be performed. Established readouts allow to study functional effects of identified genetic risk factors and wil l be used to assign novel disease genes and risk variants to defined pathogenic pathways.
We expect that the combination of comprehensive state-of-the-art genetic technologies with a detailed ascertainment of environmental modifiers will provide importa nt clues to decipher the complexity of neurodegeneration in PD. Subsequent modelling of PD in patient-based material allows to discover molecular mechanisms and leading to therapies for this still uncurable disease.