MultiModal Mental Models: converging approaches from genomes to mental illness and interplay with psychosocial stressors (4MENT)
The convergence environment wants to better understand the etiology and disease mechanisms of severe mental disorders, focusing on schizophrenia, bipolar disorder and related mental phenotypes.
Project leader: Ole Andreassen, Professor in psychiatry, Inst. of Clinical Medicine, Faculty of Medicine (MED), UiO
- Lars T. Westlye, Associate Professor in brain imaging, Dept. of Psychology, Faculty of Social Sciences, UiO
- Gaute T. Einevoll, Professor in computational neuroscience, Dept. of Physics, Faculty of Mathematics and Natural Sciences, UiO
- Marianne Fyhn, Associate Professor in biology, Dept. of Biosciences, Faculty of Mathematics and Natural Science, UiO
- Jens Saugstad, Professor of philosophy, Dept. of Philosophy, Classics, History of Art, Faculty of Humanities, UiO
Co-Leader: Assoc. Prof. Yunpeng Wang
Mental disorders are recognized as leading causes of morbidity globally, and are among the costliest disorders to affect humans. Identifying the underlying pathophysiology is imperative and can lead to major health benefits, through better treatment and prevention strategies. Mental disorders are complex, with biological and psychosocial mechanisms. Thus, a multidisciplinary approach is necessary to generate new knowledge.
4MENT provides the synergy and critical mass needed to gain breakthroughs in understanding causes of mental diseases. We will apply a series of novel technology and large human samples with psychosocial and psychiatric characterization, in combination with physics and mathematics, which is needed to leverage i) large population-based Nordic samples with genetic and environmental information, ii) cross-diagnosis phenotyping applying frontline MRI imaging technology, iii) novel computational method for increased gene discovery and disease prediction, iv) stem cells from a well-characterized clinical sample together with the genome editing technology (CRISPR), v) cultural and anthropological aspects of evolution, and made possible by strong interdisciplinary translation from expertise in epistemology and the philosophy of mind.
These innovative approaches will be used to identify more of the genetic architecture of mental phenotypes, determine the functional implications of these gene variants, and develop prediction tools for treatment stratification in a personalized medicine framework, and delineate environmental and psychosocial factors. The project depends on novel team efforts, only possible through excellent multidisciplinary expertise, and strong international collaborations.
To establish a convergence environment with a research team across several disciplines, from molecular and statistical genetics, large-scale data mining/machine learning, mathematical modeling and brain imaging integrated with psychiatry, psychology and philosophy.
- Determine if the genetic risk variants of severe mental disorders affect certain brain functions;
- Apply mathematical models to link risk variants to gene expression, protein levels and electrophysiological functions of neurons;
- Validate the identified molecular genetic mechanisms from analytical approaches in stem cells experiments;
- Identify psychosocial factors that interplay with genes in the risk of mental illness, focusing on electrophysiological phenotypes (EEG);
- Develop integrative risk prediction models for severe mental illness.
Prof. Ole A. Andreassen, Faculty of Medicine (MED); Assoc. Prof. Yunpeng Wang, Faculty of Social Science (SOCSCI); Assoc. Prof. Lars T. Westlye, SOCSCI; Prof. Gaute T. Einevoll, Faculty of Mathematics and Natural Science (MATNAT); Prof. Jens Saugstad, Faculty of Humanities (HUM); Prof. Srdjan Djurovic, Oslo University Hospital (OUS); Assoc. prof. Marianne Fyhn, MATNAT; Assoc. Prof. Unn K. Haukvik, MED; Post doc, Torbjørn Elvsåshagen, OUS and MED; Post doc, Tuomo Mäki-Marttunen, Simula Research Labs and MATNAT