Comprehensive Unbiased Risk factor Assessment for Genetics and Environment in Parkinson's Disease

Lead Research Organisation: University College London
Department Name: Institute of Neurology

Abstract

Despite the advances in the identification of genes involved in Parkinson's disease (PD), there are still appreciable gaps in our understanding of PD. Therefore we propose a comprehensive approach based on (i) a unique collection of families and (ii) large cohorts of sporadic PD patients for (iii) genetic studies and (iv) assessment of environmental modifiers that will translate into (v) functional validation studies.
Using NGS strategies, we will disentangle the complex genetic architecture of PD and better define the underlying functional variants in disease-associated GWAS loci. Newly identified genetic variants are filtered for pathogenic relevance and replicated in large cohorts of PD patients also using the unique resources of the GEO-PD Consortium. Subsequent assessment of disease modifiers includes two complementary approaches: Mendelian randomization, and gene-environment interaction studies. To validate genetic risk variants, functional studies on patient biomaterial will be performed based on (i) the unique expertise for fibroblasts- and iPSC-derived cellular models of PD and (ii) 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.

Publications

10 25 50
 
Title Research data capture 
Description Database framework for recruitment and for entering study data via electronic forms, including directly from participants, 
Type Of Material Database/Collection of data 
Year Produced 2012 
Provided To Others? Yes  
Impact Consolidation of research studies, common data model deployed across internal and external groups, improved data capture and study management, use UCLH hospital setting.