Major depressive disorder is associated with changes in a cluster of serum and urine biomarkers

2019 ◽  
Vol 125 ◽  
pp. 109796 ◽  
Author(s):  
Erin M. van Buel ◽  
Marcus J.M. Meddens ◽  
Eduard A. Arnoldussen ◽  
Edwin R. van den Heuvel ◽  
Willem C. Bohlmeijer ◽  
...  
2021 ◽  
Vol 12 ◽  
Author(s):  
Yuhang Huan ◽  
Jing Wei ◽  
Jingjing Zhou ◽  
Min Liu ◽  
Jian Yang ◽  
...  

Major depressive disorder (MDD) is a common mental disorder that can cause substantial impairments in quality of life. Clinical treatment is usually built on a trial-and-error method, which lasts ~12 weeks to evaluate whether the treatment is efficient, thereby leading to some inefficient treatment measures. Therefore, we intended to identify early candidate urine biomarkers to predict efficient treatment response in MDD patients. In this study, urine samples were collected twice from 19 respondent and 10 non-respondent MDD patients receiving 0-, 2-, and 12-week treatments with escitalopram. Differential urinary proteins were subsequently analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Our two pilot tests suggested that the urine proteome reflects changes associated with major depressive disorder at the early stage of treatment measures. On week 2, 20 differential proteins were identified in the response group compared with week 0, with 14 of these proteins being associated with the mechanisms of MDD. In the non-response group, 60 differential proteins were identified at week 2, with 28 of these proteins being associated with the mechanisms of MDD. In addition, differential urinary proteins at week 2 between the response and non-response groups can be clearly distinguished by using orthogonal projection on latent structure-discriminant analysis (OPLS-DA). Our small pilot tests indicated that the urine proteome can reflect early effects of escitalopram therapy between the response and non-response groups since at week 2, which may provide potential early candidate urine biomarkers to predict efficient treatment measures in MDD patients.


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