Proteomic analysis of serum from patients with major depressive disorder to compare their depressive and remission statuses

Psychiatry Investig. 2015 Apr;12(2):249-59. doi: 10.4306/pi.2015.12.2.249. Epub 2015 Mar 18.


Objective: Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum.

Methods: Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed.

Results: The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together.

Conclusion: This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation.

Keywords: Biomarker; Inflammation; Major depressive disorder; Neurotransmitter; Proteomics.