Project description
Molecular biomarkers for mental disorders
Mental disorders, such as depression, schizophrenia, and bipolar disorder, are complex and multifactorial, involving both genetic and environmental factors that impact brain function and behaviour. However, the lack of mechanistic insight and molecular biomarkers hampers the design of effective therapies. The ERC-funded Deep-CSF-inPsych project aims to transform the field by conducting deep cerebrospinal fluid (CSF) phenotyping on samples from individuals with first-episode psychotic disorders, depression, and healthy controls. Using cutting-edge omics technologies, the study will focus on disease-relevant metabolites and proteins in CSF. Through a systems biology approach, the research team will explore biological pathways and molecular mechanisms across psychiatric disorders, potentially identifying novel therapeutic targets and advancing treatment strategies for mental health.
Objective
Psychiatry is lacking truly objective markers and the limited molecular understanding of disease mechanism underlying mental disorders inhibits us to design new therapies, for which identification of novel treatment targets are urgently needed. No study has yet conducted deep phenotyping of the cerebrospinal fluid (CSF), which is the biological material closest to the brain that is assessable for direct investigations in intra vitam, and no large longitudinal CSF studies on mental disorders currently exists.
I aim at a paradigm change by advancing the current state-of-the-art through novel deep CSF phenotyping on unique CSF samples from individuals with first episode psychotic disorders, depression and healthy controls, to be followed-up longitudinally clinically, and in nationwide registers. Pushing the frontiers of knowledge within psychiatry, I will use novel technologies and for the first-time for these disorders use cutting edge single cell sequencing of cell compartments in the CSF potentially involved in or affected by disease, with a particular focus on T cell alterations. For the first time, longitudinal omics analyses will be conducted with targeted and untargeted metabolomics and proteomics to identify disease relevant metabolites and proteins in the CSF, increasing the understanding of molecular mechanisms of psychiatric symptoms and diagnosis. Systems biology and deep learning approaches will provide crucial insights into biological pathways and the interplay between brain pathophysiological mechanisms in a cross-diagnostic manner, potentially identifying biologically distinct clusters, disentangling the involved molecular mechanisms.
This approach is unprecedented. Identification of novel therapeutic targets, increasing the understanding of mental disorders and insights to molecular mechanisms through deep CSF phenotyping has a ground-breaking potential for psychiatry and neuroscience - paving the way for more effective and mechanism-based treatment.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsproteomics
- medical and health sciencesclinical medicinepsychiatry
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
3400 Hillerod
Denmark