Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder

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, mhydroxyphenylacetate, and alanine-was identified. This panel was capable of distinguishing depressed subjects from healthy controls with an area under the receiver operating characteristic curve ( 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). Currently, the diagnosis of MDD still relies on the subjective identification of symptom clusters rather than empirical laboratory tests. The current diagnostic modality results in a considerable error rate (3), as the clinical presentation of MDD is highly heterogeneous and the current symptombased method is not capable of adequately characterizing this heterogeneity (4). An approach that can be used to circumvent these limitations is to identify disease biomarkers to support objective diagnostic laboratory tests for MDD.Metabonomics, which can measure the small molecules in given biosamples such as plasma and urine without bias (5), has been extensively used to characterize the metabolic changes of diseases and thus facilitate the identification of novel disease-specific signatures as putative biomarkers (6 -10). Nuclear magnetic resonance (NMR) spectroscopy-based metabonomic approaches characterized by sensitive, highthroughput molecular screening have been employed previously in identifying novel biomarkers for a variety of neuropsychiatric disorders, including stroke, bipolar disorder, and schizophrenia (11-13).Specifically with regard to MDD, several animal studies have already characterized the metabolic changes in the blood and urine (14 -19). These studies provide valuable clues as to the pathophysiological mechanism of MDD. However, no study has been designed with the aim of diagnosing this disease. Recently, 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. Moreover, previous studies have also demonstrated the feasibility of identifying diagnostic metabolite biomarkers of psyc...

Plasma-metabolite-biomarkers for the therapeutic response in depressed patients by the traditional Chinese medicine formula Xiaoyaosan: A 1H NMR-based metabolomics approach

“…Several previous clinical studies have indicated that depressed patients display a disturbance of gut microbiota, including concentration changes in metabolites, such as trimethylamine N-oxide, dimethylamine and dimethylglycine (Ladep et al, 2006;Gros et al, 2009;Zheng et al, 2013.). These findings emphasize the potential intervention of gut microbiota in the development of depression.…”

Advances in Biomarkers of Major Depressive Disorder

“…Urine samples of 82 first-episode drug-naive patients with MDD and 82 healthy controls were analyzed using a NMR spectroscopy-based metabonomics [161]. Five metabolites, malonate, formate, N-methylnicotinamide, m-hydroxyphenylacetate, and alanine, distinguished MDD from controls.…”

Dynamic analysis of the endogenous metabolites in depressed patients treated with TCM formula Xiaoyaosan using urinary 1H NMR-based metabolomics

“…1. Resonance assignments were performed according to the literature Tian et al (2013), Zheng et al (2013), and Dawiskiba et al (2014) and the Chenomx NMR suite (Chenomx Inc., Edmonton, AB, Canada) as well as public NMR databases (HMDB, http://www.hmdb.ca/) and 2D NMR experiments. Urine spectra were dominated by amines and various organic acids, including citrate, succinate and lactate, as well as a range of gut microbial-host cometabolites.…”