WP 3 : In vivo assessment of disease processes & therapeutic efficacy

WP coordinator(s): E. Brouillet (Node 1); P. Remy (Node 3)
WPs collaborators: P. Hantraye (Node 1) ; P. Aubourg (Node 4-NBPS); AC Bachoud-Levi (Node 3); (Node 2)

Objectives and perimeter:

 WP3 intends to focus on three key methodological aspects at both preclinical and clinic stages leading to the development and validation of

  1. 1) relevant rodent and primate models to accelerate the translation of new imaging and behavioural methods to the clinic
  2. 2) brain imaging biomarkers specific of disease processes
  3. 3) tests assessing disease-specific behavioural deficits.


The predictability of the therapeutic efficacy in existing animal models of neurodegenerative diseases is limited by the use of genetic mouse models. More specifically, there is an incompatibility between brain size and spatial resolution/sensitivity of available state-of-the-art imaging equipment; a limited behavioural repertoire and a reduced availability of biological fluids compared to higher animal species.
In parallel, existing animal models are insufficiently characterized as their pertinence in mimicking the disease process and their predictability once transposed to the clinic still needs to be validated. The complexity of the physiopathological mechanisms underlying brain disorders is only partially addressed by currently available imaging methods (e.g., PET, MRI and NMR spectroscopy) that only investigate a limited number of biological processes.

Therefore existing methods need to be refined to assess in both animal models and patients specific landmarks of brain dysfunction and cell death like:

  1. 1) defects in metabolism,
  2. 2) potential neuroinflammatory/immunological processes associated with neurodegeneration and
  3. 3) protein aggregation. 

It is also important to improve methods to follow-up, quantify and characterize functional/structural changes in vivo. The pertinence and predictability of new imaging biomarkers of disease process and/or therapeutic efficacy need also to be formerly established. Recent developments indicate that 3-dimension multimodal co-registration of MRI and histological data from animal models and even post-mortem patient’s brains can address these issues.
Preclinical and clinical assessment of the effect of new therapies have so far neglected potential side-effects of putative treatments and concentrated on major symptoms leaving a large spectrum of motor and cognitive deficits largely unexplored. Identifying or refining key preclinical/clinical behavioural features is therefore mandatory and should benefit from cross-validation with other techniques such as imaging, electrophysiology or biology.

State of the art:

Genetic animal models, phylogenetically far from human’s disease, exist for preclinical research. More recently, the proof-of-concept that genetic models could be obtained through somatic gene transfer in various animal species including NHP (1) has suggested new possibilities to better mimic brain pathologies associated to specific gene mutations.  Existing MRI (including fMRI, diffusion tensor imaging) and NMR spectroscopy (MRS) applications provide information regarding atrophy in the CNS, degeneration of fibre tracts and biochemical defects. However, precise investigation of disease processes like protein aggregation, axonal pathologies and demyelinisation requires further methodological developments. As far as PET is concerned, newly developed radiotracers such as 11C-PIB or 18F-DPA714 are used to detect senile plaques and neuroinflammation, although their relative specificity is currently being challenged (2). Despite the fact that clinical improvement is the ultimate goal of therapeutic development, key clinical markers vary in a single disease depending on the stage or on confounding factors (e.g. symptomatic drugs, placebo effects). Disease-specific scales are available but do not reliably fulfil the gaps between the mechanism of action of a new treatment and the identification of a real impact on the disease processes.



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