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Aging (Albany NY). 2019 Sep 6;11. doi: 10.18632/aging.102133. [Epub ahead of print]

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

Author information

1
Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China.
2
Department of Endocrinology and Nephrology, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing 400014, China.
3
Department of Pathology, Faculty of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
4
Department of Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
5
NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, Chongqing Medical University, Chongqing 400016, China.
6
Department of Neurology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
7
Department of Neurology, Yongchuan Hospital of Chongqing Medical University, Chongqing 400016, China.

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.

KEYWORDS:

biomarker; major depressive disorder; metabolite; metabolomics

PMID:
31493765
DOI:
10.18632/aging.102133
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