Schizophrenia is a chronic and severe psychotic disorder that affects around 1% of the population. There is currently no physical or clinical test that can diagnose schizophrenia, and the condition is usually recognized and treated on the basis of patient symptoms. A new study performed by Matej Orešič and colleagues from the VTT Technical Research Centre of Finland reveals metabolic abnormalities that are associated specifically with schizophrenia, compared with other psychotic disorders. These findings, which were published in Genome Medicine this week, might be an important step towards the development of a clinical diagnostic test for schizophrenia.
The team used metabolomics, a high-throughput method for detecting small metabolites, to produce profiles of the serum metabolites associated with schizophrenia, other nonaffective psychosis (ONAP) or affective psychosis. Their analysis suggests that schizophrenia is associated with elevated serum levels of specific triglycerides, indicative of hyperinsulinemia, and also upregulation of the serum amino acid proline. Orešič et al. then combined these metabolic profiles to create a diagnostic model with the potential to discriminate schizophrenia from other psychoses.
This exciting study demonstrates how metabolomics can be a powerful tool for dissecting disease-related metabolic pathways and for identifying candidate diagnostic and prognostic markers in psychiatric research.