– CLEVER

The lifetime prevalence (~20%) and economic burden ($350 billion annually) associated with major depressive disorders (MDD) make them one of the most common and debilitating psychiatric illnesses.
Currently, the diagnosis of MDD and suicidal behaviors are subjective and quantitative biomarkers for early detection and long-term assessment are lacking. Without such objective biomarkers, diagnosis, monitoring and treatment adjustments rely exclusively on suboptimal clinical examination.
The challenge hasn’t been met yet because the exact cellular and molecular mechanisms underlying MDD pathophysiology have not been identified.
We hypothesize that regional changes of brain activity linked to MDD reflect the utilization of distinct fuel sources for its metabolism. Specifically, we propose that MDD patients rely more on lipids than carbohydrates to meet energy demands, whereas successful treatment would reduce lipolysis and promote glycolysis.
The primary objective of the project is to discover genes and pathways with high relevance for individuals that are more vulnerable to MDD and insufficient treatment response. The secondary objective is to exploit the candidate genes and pathways as proof-of-concept to restore fuel utilization towards more carbohydrates and less lipids in the brain of preclinical animal models of MDD.
We propose applying an innovative approach linking the epigenetic makeup to the metabolism that will lead to better stratification of MDD diagnosis, monitoring, and treatment. Biomarkers for chronic disease trajectories to MDD will be found in the epigenome and reflect the immediate metabolic state of the patients.
A cross-species approach will distinguish conserved mechanisms from evolutionary selected mechanisms linking brain/body metabolism to disease trajectories. A multivariate statistical analysis will identify the most prevalent risk factors for intervention in different preclinical models based on stress exposure.
The project is designed as a reverse translation from patients to animal models and back with a proof-of- concept for intervention. The project will provide conceptual advance in normal and dysfunctional brain/body metabolism, paving the way for predictive metabolic representations of trajectories to successful treatment and prevention. It will also provide novel targets for therapeutic intervention that could significanlty improve the quality of life of the affected individuals and their families