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Research Paper|Volume 11, Issue 17|pp 6626—6637

Age-specific urinary metabolite signatures and functions in patients with major depressive disorder

Jian-Jun Chen1, Jing Xie2, Wen-Wen Li3, Shun-Jie Bai4, Wei Wang5, Peng Zheng5, Peng Xie5,6,7
  • 1Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
  • 2Department of Endocrinology and Nephrology, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing 400014, China
  • 3Department of Pathology, Faculty of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
  • 4Department of Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
  • 5NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, Chongqing Medical University, Chongqing 400016, China
  • 6Department of Neurology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
  • 7Department of Neurology, Yongchuan Hospital of Chongqing Medical University, Chongqing 400016, China
Received: May 20, 2019Accepted: July 26, 2019Published: September 6, 2019

Copyright © 2019 Chen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Major depressive disorder (MDD) patients in different age ranges might have different urinary metabolic phenotypes, because age could significantly affect the physiological and psychological status of person. Therefore, it was very important to take age into consideration when studying MDD. Here, a dual platform metabolomic approach was performed to profile urine samples from young and middle-aged MDD patients. In total, 18 and 15 differential metabolites that separately discriminated young and middle-aged MDD patients, respectively, from their respective HC were identified. Only ten metabolites were significantly disturbed in both young and middle-aged MDD patients. Meanwhile, two different biomarker panels for diagnosing young and middle-aged MDD patients, respectively, were identified. Additionally, the TCA cycle was significantly affected in both young and middle-aged MDD patients, but the Glyoxylate and dicarboxylate metabolism and phenylalanine metabolism were only significantly affected in young and middle-aged MDD patients, respectively. Our results would be helpful for developing age-specific diagnostic method for MDD and further investigating the pathogenesis of this disease.