TRANSCRIPTOME-INFORMED COMPUTATIONAL MODELING IDENTIFIES BRAIN REGION-SPECIFIC METABOLITE ALTERATIONS IN SCHIZOPHRENIA

Schizophrenia is a highly heritable psychiatric disorder that is associated with disturbances in multiple neurobiological pathways including brain energy metabolism. Metabolic disturbances in schizophrenia include decreased glucose metabolism in the frontal cortex, increased lactate brain lactate levels, and a reduced NAD⁺/NADH ratio. However, the cause of these disturbances remains unclear. Here, we combined differential expression (DE) analysis with computational modeling to investigate how the expression of cytosolic energy metabolism-associated genes influences the concentrations of key energy metabolites. The DE analysis used human post-mortem RNA sequencing data from the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC) from the CommonMind Consortium (Hoffman et al. 2019, https://doi.org/10.1038/s41597-019-0183-6). Metabolic simulations were carried out using a biophysical model of brain energy metabolism (Winter et al. 2018, https://doi.org/10.1177/0271678X17693024). The DE analysis identified nine genes in the ACC and 24 in the DLPFC. Approximately two thirds of the DE genes were downregulated in both brain areas in schizophrenia. Decreased expression of neuronal LDHB in the ACC caused a decrease of pyruvate and an increase of NAD⁺/NADH ratio. Furthermore, decreased expression of neuronal PFKM in the DLPFC caused an increase of glucose and NAD⁺/NADH ratio and a decrease of pyruvate, lactate, and ATP. Our findings thus suggest that the hypometabolism of glucose, which is often associated with schizophrenia, may be explained by differential expression of LDHB and PFKM, while the observations of increased lactate levels and decreased NAD⁺/NADH ratio in schizophrenia are caused by other mechanisms.