Model Systems infrastructure of the German Center for Mental Health (DZPG): toward an integrated, mechanism-based framework for mental health research

Abstract Mental health is fragile and disorders are highly prevalent arising from complex interactions between genetic, developmental, psychological, social and environmental factors. The key mechanisms underlying resilience, vulnerability factors, brain repair systems, and recovery remain poorly understood, hindering the development of effective prevention and personalized treatment. The German Center for Mental Health (Deutsches Zentrum für Psychische Gesundheit, DZPG) addresses these challenges through a nationwide, interdisciplinary research network that integrates basic science with translational approaches across multiple sites. Its embedded “Model Systems” infrastructure provides a state-of-the-art platform to investigate brain–behavior mechanisms. Animal models are available to explore the links between genes, neural circuits, and behavior. Additionally, humanized model systems are established based on transgenesis and induced pluripotent stem cell (iPSC)-based models. Brain organoids further support research into neurodevelopment and multicellular interactions. Critically, when combined with high-content/high-throughput screening, iPSC-derived models link disease mechanisms to therapeutic targets. Advanced techniques, such as machine learning-based behavior quantification, single-cell and spatial multi-omics analyses, and genome editing enable in-depth analysis of disease/patient-specific cellular phenotypes and networks. Patient and public involvement embedded within the Model Systems infrastructure secures the scientific and translational relevance of the activities and helps to link experimental findings in our model systems to clinical symptoms and behavioral dimensions. By integrating animal, cellular, and human data on a multi-systems level with clinically relevant symptoms, the DZPG leverages model systems to accelerate mechanistic discovery and translation in mental health research.