4.7 Article

Identification and validation of argininosuccinate synthase as a candidate urinary biomarker for major depressive disorder

期刊

CLINICA CHIMICA ACTA
卷 451, 期 -, 页码 142-148

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.cca.2015.09.018

关键词

Argininosuccinate synthase; Diagnostic; Biomarker; Major depressive disorder; Proteomics; Urine; Urinary

资金

  1. National Basic Research Program of China (973 Program) [2009CB918300]
  2. National Key Scientific Program of China [2012CB910602]
  3. National Key Scientific Instrument and Equipment Development Project [2012YQ120044]

向作者/读者索取更多资源

Background: Major depressive disorder (MDD) is a debilitating psychiatric mood disorder. However, no objective laboratory-based test is yet available to aid in the diagnosis of this disorder. Methods: In order to identify urinary protein biomarker candidates for MDD, the differential proteomic analysis of urine samples from first-episode drug-naive MDD subjects and healthy controls (HC) was carried out by using two-dimensional gel electrophoresis separation followed by MALDI-TOF/TOF-MS/MS identification. Then, the differential expression levels of some candidate proteins were further validated by immunoblot analysis. Results: Through mass spectrometry and database searching, a total of 27 differential proteins were identified, primarily including enzymes, plasma proteins, serpins, and adhesion molecules. Five proteins were selected for subsequent validation by Western blotting. One arginine recycling enzyme - argininosuccinate synthase (ASS1) - was further confirmed to be significantly downregulated in the urine of 30 depressed subjects while remaining unchanged in the plasma. Importantly, receiver-operator curve analyses revealed that ASS1 displayed strong efficacy in distinguishing MDD subjects from HC Conclusion: The present study provides a range of urinary protein biomarker candidates for MDD, and further demonstrates that ASS1 has a potential for clinical diagnosis of this disorder. (C) 2015 Elsevier B.V. All rights reserved.

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