Prof. Dr. Gabriele Ende

The neural and neurochemical patterns of acute threat as modulators of aggression in BPD will be investigated in this project. The modulation of aggressive responses under acute threat is induced by the threat-of-shock paradigm. The main translational research question is if and how aggressive responses are modulated by threat, and which neurofunctional and neurochemical patterns underlie these responses during safe and threat conditions. MR spectroscopy will be used in patients to assess glutamate and GABA levels. In a further translational approach, the least and the most aggressive/impulsive recombinant inbred mouse lines identified in C01 in Frankfurt will be tested in Mannheim with animal MR spectroscopy at 9.4T to determine the relationship between glutamate, GABA, impulsivity, and aggression in these mouse lines as well as in comparable brain regions assessing neurofunctional and neurochemical patterns.

Beta-hydroxy-butyrate (BHB), a ketone body, is negatively associated with aggressive behavior. BHB is a metabolite and an active signaling substrate involved in epigenetic regulation of e.g., neurotrophic factor genes in the brain. Of the three main ketone bodies, acetone, acetoacetate and BHB, acetone is a very volatile compound, mainly eliminated through respiration, thus can be measured non-invasively in breath. A reduction of acetone in breath has been found to highly correlate with BHB in blood and be associated with symptom severity in schizophrenia (Jiang et al. 2022). Using MR spectroscopy, A08 aims to (1) identify whether acetone and other volatile organic compounds in breath are associated with aggression and acute threat processing in mental disorders and (2) to examine whether these breath markers are associated with direct metabolic brain correlates (like BHB, glutamate) and with the brain-derived neurotrophic factor (BDNF) levels in plasma. In a translational approach, (3) we will test if supplementation of BHB reduces aggressive behavior in mice.

Data management and training platform. A decentralized data management infrastructure will help focus on developmental and therapeutic longitudinal data, training all participating researchers in the necessary skills for future use. This strategy will lay the foundations for further data-driven computational modelling projects in the next funding period.