Metabolomic Profiling of Post-Mortem Brain Reveals Changes in Amino Acid and Glucose Metabolism in Mental Illness Compared with Controls

Rong Zhang, Tong Zhang, Ali Muhsen Ali, Mohammed Al Washih, Benjamin Pickard, David G. Watson

Research output: Contribution to journalArticle

12 Citations (Scopus)
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Abstract

Metabolomic profiling was carried out on 53 post-mortem brain samples from subjects diagnosed with schizophrenia, depression, bipolar disorder (SDB), diabetes, and controls. Chromatography on a ZICpHILIC column was used with detection by Orbitrap mass spectrometry. Data extraction was carried out with m/z Mine 2.14 with metabolite searching against an in-house database. There was no clear discrimination between the controls and the SDB samples on the basis of a principal components analysis (PCA) model of 755 identified or putatively identified metabolites. Orthogonal partial least square discriminant analysis (OPLSDA) produced clear separation between 17 of the controls and 19 of the SDB samples (R2CUM 0.976, Q2 0.671, p-value of the cross-validated ANOVA score 0.0024). The most important metabolites producing discrimination were the lipophilic amino acids leucine/isoleucine, proline, methionine, phenylalanine, and tyrosine; the neurotransmitters GABA and NAAG and sugar metabolites sorbitol, gluconic acid, xylitol, ribitol, arabinotol, and erythritol. Eight samples from diabetic brains were analysed, six of which grouped with the SDB samples without compromising the model (R2 CUM 0.850, Q2 CUM 0.534, p-value for cross-validated ANOVA score 0.00087). There appears on the basis of this small sample set to be some commonality between metabolic perturbations resulting from diabetes and from SDB.

Original languageEnglish
Pages (from-to)106-116
Number of pages11
JournalComputational and Structural Biotechnology Journal
Volume14
Early online date26 Feb 2016
DOIs
Publication statusE-pub ahead of print - 26 Feb 2016

Keywords

  • bipolar disorder
  • brain tissue
  • branched chain amino acids
  • depression
  • diabetes
  • metabolomics
  • schizophrenia
  • sorbitol

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