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Int J Neuropsychopharmacol. 2014 Oct 31;18(2). pii: pyu019. doi: 10.1093/ijnp/pyu019.

Proteomic enrichment analysis of psychotic and affective disorders reveals common signatures in presynaptic glutamatergic signaling and energy metabolism.

Author information

1
Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK (Drs Gottschalk, Wesseling, and Drs Guest and Bahn); Department of Neuroscience, Erasmus Medical Center, Rotterdam, The Netherlands (Dr Bahn).
2
Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK (Drs Gottschalk, Wesseling, and Drs Guest and Bahn); Department of Neuroscience, Erasmus Medical Center, Rotterdam, The Netherlands (Dr Bahn). sb209@cam.ac.uk.

Abstract

BACKGROUND:

Although genetic studies suggest an overlap in risk alleles across the major psychiatric disorders, disease signatures reflecting overlapping symptoms have not been found. Profiling studies have identified candidate protein markers associated with specific disorders of the psychoaffective spectrum, but this has always been done in a selective fashion without accounting for the entire proteome composition of the system under investigation.

METHODS:

Employing an orthogonal system-based proteomic enrichment approach based on label-free liquid chromatography mass spectrometry, we analyzed anterior prefrontal human post-mortem brain tissue of patients affected by schizophrenia (n = 23), bipolar disorder (n = 23), major depressive disorder with (n = 12) and without psychotic features (n = 11), and healthy controls (n = 23). Labeled selected reaction monitoring (SRM) was used to validate these findings on a pathway level. Independent in silico analyses of biological annotations revealed common pathways across the diseases, associated with presynaptic glutamatergic neurotransmission and energy metabolism. We validated the proteomic findings using SRM and confirmed that there were no effects of post-mortem confounders.

RESULTS:

Schizophrenia and affective psychosis were linked to a hypoglutamatergic state and hypofunction of energy metabolism, while bipolar disorder and major depressive disorder were linked to a hyperglutamatergic state and hyperfunction of energy metabolism.

CONCLUSIONS:

These findings support recent investigations, which have focused on the therapeutic potential of glutamatergic modulation in psychotic and affective disorders. We suggest a disease model in which disturbances of the glutamatergic system and ensuing adaptations of neuronal energy metabolism are linked to distinct psychiatric symptom dimensions, delivering novel evidence for targeted treatment approaches.

KEYWORDS:

glutamate; glycolysis; proteomics; psychosis; systems biology

PMID:
25609598
PMCID:
PMC4368887
DOI:
10.1093/ijnp/pyu019
[Indexed for MEDLINE]
Free PMC Article

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