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PRECISE-PD: From pathophysiology to precision medicine for Parkinson’s disease

JC. Corvol, S. Durrleman, S. Lehericy, D. Devos, W. Meissner, E. Bezard, D. Grosset, H. Morris, O. Monchy, EA. Fon, F. Durif, F. Tubach, Y. de Rycke, O. Rascol (Paris, France)

Meeting: 2019 International Congress

Abstract Number: 422

Keywords: Parkinsonism

Session Information

Date: Monday, September 23, 2019

Session Title: Genetics

Session Time: 1:45pm-3:15pm

Location: Les Muses Terrace, Level 3

Objective: To propose a mechanism-based progression model of Parkinson’s disease (PD) by combining genetic, imaging, and longitudinal clinical data from a large cohort of patients.

Background: PD is a complex neurodegenerative disease characterized by the progression of motor and non-motor symptoms. The relationships between progression profiles and their underlying molecular mechanisms remain to be identified.

Method: Since 2016, the French clinical research network for Parkinson’s disease and movement disorders (NS-PARK/FCRIN) has implemented a web-based solution to prospectively collect clinical information from all consecutive PD patients followed in the 25 expert centers for PD in France, updated by the neurologist at each visit of the patient. Thanks to the French patient organization France Parkinson, we recently got funding from the French patient organization France Parkinson to implement a biobank and a multicenter brain imaging pipeline, and to develop computerized approaches to model disease progression by integrating clinical, genomic, and brain imaging data.

Results: The NS-PARK database currently includes clinical data from around 20,000 patients. A centralized biobank will provide standardized samples of DNA, plasma, and serum from at least 5,000 patients. Genotyping will be performed by using the last generation of genome wide genotyping arrays, and data will be imputed to extend genomic data for these patients. We will used the national Center for Image Acquisition and Processing (Centre d’Acquisition et de Traitement de Images – CATI) to monitor and centralized standardized brain imaging data (MRI) obtained from patients. We will combine different computational and statistical approaches including latent class models, Bayesian non-linear models, and non-negative matrix factorization allowing to model and predict individual trajectories by integrating clinical, biological, and brain imaging data. Replication is planned to be performed in independent cohorts.

Conclusion: PRECISE-PD is an unpreceded opportunity to open the path to the new era of precision and personalized medicine for PD.

To cite this abstract in AMA style:

JC. Corvol, S. Durrleman, S. Lehericy, D. Devos, W. Meissner, E. Bezard, D. Grosset, H. Morris, O. Monchy, EA. Fon, F. Durif, F. Tubach, Y. de Rycke, O. Rascol. PRECISE-PD: From pathophysiology to precision medicine for Parkinson’s disease [abstract]. Mov Disord. 2019; 34 (suppl 2). https://www.mdsabstracts.org/abstract/precise-pd-from-pathophysiology-to-precision-medicine-for-parkinsons-disease/. Accessed June 14, 2025.
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