On 25 May at 12:00 Taavi Vanaveski will defend his doctoral thesis “Modeling the quantitative nature of neuropsychiatric disorders in animal models: metabolic, behavioral and genetic profiles” for obtaining the degree of Doctor of Philosophy (in Neuroscience).
Supervisors:
Associate Professor Mari-Anne Philips, University of Tartu
Professor Eero Vasar, University of Tartu
Associate Professor Kersti Lilleväli, Centre of Estonian Rural Research and Knowledge
Opponent:
Professor Emeritus Heikki Rauvala, University of Helsinki (Finland)
Summary
Mental disorders are heterogeneous conditions arising from a variety of genetic and environmental insults. The gradual manifestation of mental disorder is often overshadowed by natural development, accompanied by an unpredictable course, unknown side effects, and significant disturbances of higher cognition. The polygenic nature makes it difficult to distinguish between disorders, and difficult to detect and treat on time. Therefore, early detection is key in preventing further progressive deterioration. Scientific research prioritises finding early biological markers that reflect the course of these disorders. These markers should be searched for on a molecular, synaptic, cellular, tissue, network and higher-order systems level. Different simplified models, including genetically modified or pharmacologically manipulated rodent models, make this task feasible. The following dissertation examines three different simplified models: the role of mitochondrial energy metabolism in inhibitory neurotransmission, metabolic predisposition in psychosis, and the expression pattern of IglON neural cell adhesion molecules. Understanding these models takes us closer to understanding mental disorders and discovering therapeutic opportunities. The findings of these three models can be summarised as follows. PPARGC1α (PGC1α) overexpression mutant displays labile mood phenotype that allows for mood disorder modelling. The 129sv mouse strain simplifies the modelling of psychosis in the predisposed population. The expression pattern of IgLONs refers to their potential to reflect irregularities in brain development and maintenance.