Gene expression-based biological test for major depressive disorder: an advanced study
Received 18 August 2016
Accepted for publication 11 November 2016
Published 21 February 2017 Volume 2017:13 Pages 535—541
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 3
Editor who approved publication: Dr Taro Kishi
Shin-ya Watanabe,1 Shusuke Numata,1 Jun-ichi Iga,2 Makoto Kinoshita,1 Hidehiro Umehara,1 Kazuo Ishii,3 Tetsuro Ohmori1
1Department of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, 2Department of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Ehime, 3Department of Applied Biological Science, Faculty of Agriculture, Tokyo University of Agriculture and Technology, Tokyo, Japan
Purpose: Recently, we could distinguished patients with major depressive disorder (MDD) from nonpsychiatric controls with high accuracy using a panel of five gene expression markers (ARHGAP24, HDAC5, PDGFC, PRNP, and SLC6A4) in leukocyte. In the present study, we examined whether this biological test is able to discriminate patients with MDD from those without MDD, including those with schizophrenia and bipolar disorder.
Patients and methods: We measured messenger ribonucleic acid expression levels of the aforementioned five genes in peripheral leukocytes in 17 patients with schizophrenia and 36 patients with bipolar disorder using quantitative real-time polymerase chain reaction (PCR), and we combined these expression data with our previous expression data of 25 patients with MDD and 25 controls. Subsequently, a linear discriminant function was developed for use in discriminating between patients with MDD and without MDD.
Results: This expression panel was able to segregate patients with MDD from those without MDD with a sensitivity and specificity of 64% and 67.9%, respectively.
Conclusion: Further research to identify MDD-specific markers is needed to improve the performance of this biological test.
Keywords: depressive disorder, biomarker, gene expression, schizophrenia, bipolar disorder
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