DS0404 -

Methods and Models for Deep Screening of subphenotypes in Parkinson’s Disease – MeMoDeeP

Submission summary

Unraveling the genotype-phenotype relationship in a heterogeneous disorder, like Parkinson’s disease, is one of the most important challenges towards the dissection of its complex etiology. Further, improving patient characterization for genomic is clearly an important step towards enhancing usefulness of genomic medicine and accuracy of disease risk/progression. PD is an age-related neurodegenerative disorder which affects 1% of population over the age of 60 years and 4% over age 80. More than 100,000 patients suffer from this disease in France and the number of cases is expected to increase dramatically with the increase in life expectancy. So far treatments are only substitutive and do not prevent the massive neurodegeneration that results in progressive loss of autonomy and finally death. It is well known that PD can present with different clinical subtypes and severity. Objective biomarkers are lacking and access to DNA/RNA profiles from damaged CNS-specific tissues in a large number of patients is, up to now, relatively limited. Yet, moving beyond empirical stratification of patients raises considerable challenges as the high-dimensionality and the mixture of data types increases. We propose a comprehensive exploration study of different mathematical and statistical models based on one of the largest longitudinal studies of PD and with genomic data. We aim to evaluate the performances of these methods in deciphering subsets of patients in which etiology might be more homogeneous and for which genomic prediction might be more valuable and accurate. The proposed methods will be tested by cross-validation and simulations. In the course of this project, we also aim to gain insights into what improvements could be made further and deliver the corresponding and efficient computational algorithms. We have planned to replicate the findings in a similar and independent cohort of PD (PPMI) and other PD cohorts likely to be built (i.e., FOA call, NINDS). The present project allies researchers from medical, neurological, quantitative genetics and mathematics communities sharing the same goal. In the long run, we expect that it will provide information about pathophysiology and (ultimately) new approaches to treatment. For instance, demonstrating that particular subgroups of PD involve multiple different etiological or pathological processes could, therefore, imply that therapeutic approaches in these sub-groups may also require different targeted drugs and strategies.

Project coordination

maria martinez (INSERM)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


CNRS Laboratoire de Mathématiques et Modélisation d'Evry
INSERM UMR_S1127 Institut National de la Santé et de la Recherche Médicale
CNRS Laboratoire de Mathématiques et Modélisation d'Evry

Help of the ANR 232,956 euros
Beginning and duration of the scientific project: October 2016 - 36 Months

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