Metabolomics And Genomics Investigations of Psychosis and Cardiometabolic Comorbidity

People with psychotic disorders, such as schizophrenia, often suffer from serious issues like heart disease and diabetes, which is why they live shorter lives than others. These conditions do not coexist by chance; they influence each other in ways scientists are only beginning to understand. A revolutionary approach called metabolomics, which analyzes proteins, cholesterol, and other molecules in your blood, is helping us solve the puzzle of the relation between these conditions. Thanks to large biobanks and national health records, we can now map biological connections between our bodies and brains. MAGIC is a groundbreaking effort combining genetics, high-tech blood analysis, brain imaging, and health records. This initiative aims to uncover hidden relationships between metabolic health and psychotic disorders by: 1. Study links between metabolic markers (like proteins or fat molecules) and psychotic experiences (e.g., hallucinations), as well as common cardiometabolic diseases. We will also couple this to changes in brain structure and body composition. 2. Analyze genetic data to determine which genes contribute to these intertwined issues, using this to explore potential cause-and-effect relationships. 3. Investigate which genetic factors are shared or unique to psychosis and cardiometabolic diseases, revealing the underlying molecular pathways and deepen our understanding of both conditions. 4. Use powerful machine learning techniques to create 'digital twins'—virtual patient models that can predict how these conditions will progress in individuals. This may allow us to tailor intervention strategies to each person's unique genetic and metabolic profile. MAGIC promises to uncover the biological secrets linking metabolism and mental health. By transforming our understanding of these complex relationships, it aims to improve prevention strategies and outcomes. This could be a game-changer in health care, offering hope for better, more personalized care.

People with psychotic disorders often suffer from cardiometabolic diseases, which are major determinants of clinical outcome. It is therefore imperative that we better understand the pathogenesis of metabolic dysfunction and its contribution to the development of psychosis. Markers of metabolic processes can be reliably measured in blood samples using new high-throughput metabolomics, i.e., the measurement of proteins, amino acids, and other small molecules. Such data is now available through large biobanks coupled to national health records. This provides unprecedented opportunities to uncover the genetic architecture of metabolism and its impact on body and brain measures. The MAGIC project will enhance our understanding of the role that metabolic dysfunction plays in psychosis, using a unique set of genomics, metabolomics, imaging, and registry data. We will leverage a transcontinental network of deep-phenotyped, population-based prospective cohorts to (1) establish the relationship between metabolic markers and psychotic experiences, as well as comorbid cardiometabolic conditions, and estimate to what extent associations are mediated by brain morphology and body composition; (2) calculate the amount of genetic overlap between the markers, psychotic disorders and cardiometabolic diseases, and leverage genetic variation to determine causal relationships; (3) identify shared and specific genetic determinants of psychotic disorders and cardiometabolic diseases with enhanced statistical power, thereby uncovering the molecular pathways involved; and (4) predict individual clinical trajectories through a ‘digital twin’ approach, using powerful machine learning techniques. This project has transformative potential by generating an unprecedented overview of the biological underpinnings of metabolic dysfunction in psychosis, promoting tailored prevention strategies and improved individual outcome prediction.