A quantitative approach to neuropsychiatry: The why and the how. (February 2019)

• Record Type: Journal Article
• Authors: Kas, Martien J.; Penninx, Brenda; Sommer, Bernd; Serretti, Alessandro; Arango, Celso; Marston, Hugh
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 97(2019)
• Page Start: 3
• Page End: 9
• Publication Date: 2019-02
• Subjects: Schizophrenia -- Alzheimer's Disease -- Major Depression -- Behaviour -- EEG -- Neuro-imaging -- Genetics -- Smartphone technology -- Mouse -- Human -- Cross-disorder -- Transdiagnostic -- Drug discovery -- Translational research -- Sensory processing -- Social withdrawal -- Attention -- Working memory -- Quantitative biology; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2017.12.008
• Languages: English
• ISSNs: 0149-7634

Abstract

Highlights: The PRISM project will provide a quantitative biological approach across neuropsychiatric diseases. Quantifiable biological parameters for social withdrawal and cognitive deficits will be assessed. Homologous preclinical and clinical paradigms will be implemented to deliver predictive animal models. A molecular landscape with functional signalling pathways for social withdrawal will be built. The PRISM project aims to provide solutions to the growing public health challenges of psychiatry and neurology. Abstract: The current nosology of neuropsychiatric disorders allows for a pragmatic approach to treatment choice, regulation and clinical research. However, without a biological rationale for these disorders, drug development has stagnated. The recently EU-funded PRISM project aims to develop a quantitative biological approach to the understanding and classification of neuropsychiatric diseases to accelerate the discovery and development of better treatments. By combining clinical data sets from major worldwide disease cohorts and by applying innovative technologies to deeply phenotype stratified patient groups, we will define a set of quantifiable biological parameters for social withdrawal and cognitive deficits common to Schizophrenia (SZ), Major Depression (MD), and Alzheimer's Disease (AD). These studies aim to provide new classification and assessment tools for social and cognitive performance across neuropsychiatric disorders, clinically relevant substrates for treatment development, and predictive, preclinical animal systems. With patients and regulatory agencies, we seek to provide clear routes for the future translation and regulatory approval for new treatments and provide solutions to the growing public health challenges of psychiatry and neurology.