Psychiatry Investig.  2015 Apr;12(2):249-259. 10.4306/pi.2015.12.2.249.

Proteomic Analysis of Serum from Patients with Major Depressive Disorder to Compare Their Depressive and Remission Statuses

Affiliations
  • 1Department of Senior Healthcare, BK21 Plus Program, Graduate School, Eulji University, Daejeon, Republic of Korea. kanghg@eulji.ac.kr
  • 2Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon, Republic of Korea.
  • 3Laboratory of Stem Cell Biology, Division of Biotechnology, College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea.
  • 4College of Pharmacy, Gachon University, Incheon, Republic of Korea. hklee@gachon.ac.kr
  • 5Institute for Senior Industry, Eulji University, Seongnam, Republic of Korea.
  • 6Department of Biomedical Laboratory Science, Graduate School of Health Science, Eulji University, Seongnam, Republic of Korea.

Abstract


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.

Keyword

Biomarker; Inflammation; Major depressive disorder; Neurotransmitter; Proteomics
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