Multiplatform metabolome and proteome profiling identifies serum metabolite and protein signatures as prospective biomarkers for schizophrenia

J Neural Transm (Vienna). 2015 Aug:122 Suppl 1:S111-22. doi: 10.1007/s00702-014-1224-0. Epub 2014 May 1.


Schizophrenia is a severe mental illness with a biological basis. However, the search for reliable biomarkers suitable for clinical routine has been futile so far. Accordingly, there is a need for innovative approaches such as genomics and proteomics to achieve this goal. In the present study, we compared metabolomic and proteomic data from 26 schizophrenia patients as well as from unaffected controls carefully matched for age and gender in a multi-platform approach. The combined analysis identified many signatures with initially good biomarker characteristics. After statistical analysis and comparison of these identified serum metabolites (analysed by Gas Chromatography Mass Spectrometry) and hydrophobic serum proteins (analysed by matrix-assisted laser desorption ionisation mass spectrometry), several markers (e.g., 2-piperidinec carboxylic acid, 6-deoxy-mannofuranose, galactoseoxime and a serum peptide of m/z 3177) were determined as having the best discriminating value between the groups. Our findings represent a proof of principle indicating that metabolomic and proteomic approaches can be successfully used in psychiatric biomarker research, even though the results should be regarded as preliminary with a need for replication in larger samples.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Blood Proteins / metabolism*
  • Case-Control Studies
  • Cohort Studies
  • Female
  • Humans
  • Lipids / blood
  • Male
  • Metabolome / physiology*
  • Middle Aged
  • Proteome / metabolism*
  • Proteomics / methods
  • ROC Curve
  • Schizophrenia / blood*
  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
  • Young Adult


  • Blood Proteins
  • Lipids
  • Proteome