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One step closer to a diagnostic test for schizophrenia

31.03.2011


Scientists in Finland have revealed metabolic abnormalities that are associated with schizophrenia. This may be an important step towards development of a clinical test of the disease.

Schizophrenia is a chronic and severe psychotic disorder that affects around 1% of the population. Currently, there is no clinical test for diagnosing schizophrenia, and therefore the condition is usually recognized and treated on the basis of patient symptoms.

A new study performed by Matej Orešič and colleagues from VTT Technical Research Centre of Finland in collaboration with Jaana Suvisaari from the Finnish National Institute for Health and Welfare reveals metabolic abnormalities that are associated specifically with schizophrenia, as opposed to other psychotic disorders. These findings, which were published in Genome Medicine in March 2011, 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 indicates 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.

Reference

M. Orešič, J. Tang, T. Seppänen-Laakso, I. Mattila, S. E. Saarni, S. I. Saarni, J. Lönnqvist, M. Sysi-Aho, T. Hyötyläinen, J. Perälä, J. Suvisaari, Metabolome in schizophrenia and other psychotic disorders: a general population-based study, Genome Medicine (2011). doi: 10.1186/gm233.

http://sysbio.vtt.fi/


Additional information

Matej Orešič
Research Professor
+358 20 722 4491

 

 

Additional information

Matej Orešič
Research Professor
+358 20 722 4491