Abstract
Major depressive disorder (MDD) is a widespread and debilitating mental disorder. However, there are no biomarkers available to aid in the diagnosis of this disorder. In this study, a nuclear magnetic resonance spectroscopy-based metabonomic approach was employed to profile urine samples from 82 first-episode drug-naïve depressed subjects and 82 healthy controls (the training set) in order to identify urinary metabolite biomarkers for MDD. Then, 44 unselected depressed subjects and 52 healthy controls (the test set) were used to independently validate the diagnostic generalizability of these biomarkers. A panel of five urinary metabolite biomarkers-malonate, formate, N-methylnicotinamide, m-hydroxyphenylacetate, and alanine-was identified. This panel was capable of distinguishing depressed subjects from healthy controls with an area under the receiver operating characteristic curve (AUC) of 0.81 in the training set. Moreover, this panel could classify blinded samples from the test set with an AUC of 0.89. These findings demonstrate that this urinary metabolite biomarker panel can aid in the future development of a urine-based diagnostic test for MDD.
Highlights
Major depressive disorder (MDD)1 is a debilitating mental disorder affecting up to 15% of the general population and accounting for 12.3% of the global burden of disease [1, 2]
Metabonomic Analysis of Urine Obtained from MDD Subjects and healthy controls (HCs)—In the training set, orthogonal partial least-squares discriminant analysis (OPLS-DA) analysis was carried out to explore the metabolic differences between MDD subjects and HCs
Representative 600 1H Nuclear magnetic resonance (NMR) spectra of urine obtained from an MDD subject and an HC are shown in supplemental Fig. S1
Summary
Major depressive disorder (MDD) is a debilitating mental disorder affecting up to 15% of the general population and accounting for 12.3% of the global burden of disease [1, 2]. An approach that can be used to circumvent these limitations is to identify disease biomarkers to support objective diagnostic laboratory tests for MDD. With regard to MDD, several animal studies have already characterized the metabolic changes in the blood and urine (14 –19). Using an NMR-based metabonomic approach, this research group identified a unique plasma metabolic signature that enables the discrimination of MDD from healthy controls with both high sensitivity and specificity [20]. These findings motivated further study on urinary diagnostic metabolite biomarkers for MDD, which would be more valuable from a clinical applicability standpoint, as urine can be more non-invasively collected. As systemic metabolic disturbances have been observed in the urine of a depressed animal model, it is likely that diagnostic metabolite markers for MDD can be detected in human urine
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