Schizophrenia is a complex disorder. Although a genetic component has long been recognized, how the genes generate the symptoms remains largely unknown. In the EnerSchiz project, we will use computational modelling and genetic data to investigate how risk genes of schizophrenia that are related to energy metabolism and neuronal excitability affect the disorder at the cellular level. In particular, we will use post-mortem gene expression data from individuals with and without a history of the disease and develop computational models of neurons to predict the effects of the observed gene-expression differences on nerve cell activity. The strength of our approach is that we can assess the combined effects of different genes across multiple aspects of neuron and brain function. Improved understanding of how neurons work in schizophrenia patients compared to healthy controls will pave the way for novel treatments of the disorder. The research will be conducted at Tampere University.

2025

2029