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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - PRISM (Psychiatric Ratings using Intermediate Stratified Markers - Sofia ref.: 115916)

Teaser

Summary

Most mental health conditions are still classified and diagnosed solely based on the symptoms observed, as there are few objective biomarkers for these conditions as there are for other conditions, such as diabetes. Many different neuropsychiatric diseases share symptoms, which makes it difficult to understand what the underlying biological cause of a specific disease is. For example, we do not really have an idea how, if at all, the biological cause for social withdrawal in Alzheimerâ€™s disease (AD) differs from that in schizophrenia (SZ).
This lack of understanding of the root biological causes is one of the reasons behind the dramatic slowdown in the development of new drugs to treat neuropsychiatric disorders. Historically, many of the major drug classes for psychiatric disorders were discovered as a consequence of chance observations in human studies, an approach that suffers from a high rate of attrition and risk of drug candidate failures during development. Modern drug design aims to reduce this risk of attrition by altering a known biological process and closely monitoring and quantifying the treatment effects of doing this. The emergence of new ways of measuring brain activity (e.g. functional Magnetic Resonance Imaging (fMRI) of the brain, which registers blood flow to functioning areas of the brain) is for the first time opening the door to applying this type of drug discovery to mental health conditions.
Therefore, the overall objective of this project is to develop a quantitative biological approach to the understanding and classification of neuropsychiatric diseases to accelerate the discovery and development of better treatments for patients. The concept of our proposal is to define a set of quantifiable biological parameters for social withdrawal and cognitive deficits to cluster and differentiate SZ, AD, and to a lesser degree, patients with major depressive disorder (MD). In phase I of the project (years 1-3), the following specific objectives will be addressed:
1.) Proof-of-concept (PoC) analyses to cluster and differentiate SZ and AD patients on the basis of quantitative biological parameters.
2.) Explore dimensional relationships between pathology (e.g., cognitive deficits) and social withdrawal.
3.) Develop deeper understanding of the quantitative biology of social withdrawal using clinical data from SZ, AD and MD patients and by establishing a network of pre-clinical research sites able to perform high quality back-translation studies.
4.) Develop a path towards recognition of social withdrawal as a registrable symptom across disorders.

Work performed

For the clinical deep phenotyping study, recruitment and inclusion of patients and age matched healthy controls progressed well in the past 12 months of the project. Based on the initial experiences with the protocol, small adjustments were made to further optimize the study. For each of the tasks and questionnaires, lead data analysts were identified, who will be responsible to deliver high quality endpoint measures to the central database for the primary analysis. With the help of the newly appointed data management coordinator and statistical coordinator, statistical analysis plans and primary endpoint measures for these tasks and questionnaires are being defined for the primary data analysis.

To develop a deeper understanding of the quantitative biology of social withdrawal, genetic analysis of a population cohort contributed to the generation of a preliminary molecular landscape for social withdrawal. The consortium is currently investigating the availability of mouse lines that are mutant for genes within this molecular landscape to initiate a genetic validation study of the social withdrawal phenotype in mice. In addition, all equipment and protocols for preclinical studies on behaviour and EEG are in place, and are currently being implemented to establish a functional network of preclinical research sites to perform high quality back-translation studies. In addition, the multi-center preclinical study on social behaviour using a colony based design with automated behavioural tracking started.

To develop the regulatory path for social withdrawal across disorders, discussions within the consortium were initiated regarding a digital biomarker for social withdrawal. To validate a quantitative and objective biomarker for social withdrawal, social questionnaire data are being assessed in patients and age matched healthy controls and will be compared to smartphone measures.

Final results

PRISM addresses the treatment needs of the three most prevalent brain disorders in Europe. The economic burden of these three disorders is huge and most of the imposed costs are indirect due to lack of productivity. Social withdrawal has been identified as one of the main reasons for mental health related disability benefit claims in the UK (UK Department of Work and Pensions Annual Report, 2012). Moreover, these diseases lie heavily on caregivers and impact significantly on their ability to work (Haro et al., 2014).
PRISM will deliver a sustainable European network of preclinical and clinical centres working cooperatively to develop and deliver state of the art (epi-)genetic, imaging and neuropsychological techniques to specifically assess the efficacy of new interventions in SZ, AD and MD.
The project will bridge the important translation gap between discovery and the validation of biomarkers and their associated technologies to a point where they can be deployed reliably and effectively across the network. The PRISM network will establish that quantitative biological parameters can be used to effectively stratify patients using biomarkers for social withdrawal. In addition, innovative molecular landscaping methods are being applied to provide new insights in signaling pathways underlying these quantitative biological parameters.
With leading pre-clinical academic and EFPIA partners, back-translation of human biological substrates for social withdrawal and cognitive deficits will be performed using core technologies. This will provide a standardized framework for forward translation of novel therapeutics with pre-validated biomarkers and stratification tools for social withdrawal and cognitive deficits in SZ, AD, and MD patient populations. Novel technologies are being implemented to assess social group behaviour and sensory processing deficits in pre-clinical models that eventually may become relevant for studying neurobiological mechanisms underlying symptoms across the neuropsychiatric spectrum.