Metabolic Profiling of Human Blood Serum from Treated Patients with Bipolar Disorder Employing <sup>1</sup>H NMR Spectroscopy and Chemometrics

Sussulini, Alessandra; Prando, Alessandra; Maretto, Danilo Althmann; Poppi, Ronei J.; Tasić, Ljubica; Banzato, Cláudio E. M.; Arruda, Marco Aurélio Zezzi

doi:10.1021/ac901502j

Cited by 63 publications

(55 citation statements)

References 36 publications

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“…With regards to BD, previous metabonomic studies have used a NMR metabonomic platform to identify differential metabolites in post-mortem brain tissue and plasma1718. Meanwhile, in our group, Zheng et al .…”

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confidence: 99%

Combined Application of NMR- and GC-MS-Based Metabonomics Yields a Superior Urinary Biomarker Panel for Bipolar Disorder

Chen

Liu

Fan

et al. 2014

Sci Rep

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Bipolar disorder (BD) is a debilitating mental disorder that cannot be diagnosed by objective laboratory-based modalities. Our previous studies have independently used nuclear magnetic resonance (NMR)-based and gas chromatography-mass spectrometry (GC-MS)-based metabonomic methods to characterize the urinary metabolic profiles of BD subjects and healthy controls (HC). However, the combined application of NMR spectroscopy and GC-MS may identify a more comprehensive metabolite panel than any single metabonomic platform alone. Therefore, here we applied a dual platform (NMR spectroscopy and GC-MS) that generated a panel of five metabolite biomarkers for BD-four GC-MS-derived metabolites and one NMR-derived metabolite. This composite biomarker panel could effectively discriminate BD subjects from HC, achieving an area under receiver operating characteristic curve (AUC) values of 0.974 in a training set and 0.964 in a test set. Moreover, the diagnostic performance of this panel was significantly superior to the previous single platform-derived metabolite panels. Thus, the urinary biomarker panel identified here shows promise as an effective diagnostic tool for BD. These findings also demonstrate the complementary nature of NMR spectroscopy and GC-MS for metabonomic analysis, suggesting that the combination of NMR spectroscopy and GC-MS can identify a more comprehensive metabolite panel than applying each platform in isolation.

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confidence: 99%

Combined Application of NMR- and GC-MS-Based Metabonomics Yields a Superior Urinary Biomarker Panel for Bipolar Disorder

Chen

Liu

Fan

et al. 2014

Sci Rep

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“…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)(12)(13).…”

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confidence: 99%

Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder

Zheng

Wang

Chen

et al. 2013

Molecular & Cellular Proteomics

184

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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...

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“…Studies applying metabolomic profiling of patient serum are also starting to be used to explore the biology of psychiatric disorders [41,42,43,44,45,46]. Such studies have suggested the possibility of identifying biomarkers for schizophrenia [47,48,49,50,51,52], major depressive disorder [53,54] and posttraumatic stress disorder [55], and have also been used to study medication-induced metabolic changes [56,57]. In bipolar disorder, metabolomic studies have been undertaken in urine samples to identify potential biomarkers [58,59,60,61].…”

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confidence: 99%

Perturbational Profiling of Metabolites in Patient Fibroblasts Implicates α-Aminoadipate as a Potential Biomarker for Bipolar Disorder

et al. 2016

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Many studies suggest the presence of aberrations in cellular metabolism in bipolar disorder. We studied the metabolome in bipolar disorder to gain insight into cellular pathways that may be dysregulated in bipolar disorder and to discover evidence of novel biomarkers. We measured polar and nonpolar metabolites in fibroblasts from subjects with bipolar I disorder and matched healthy control subjects, under normal conditions and with two physiologic perturbations: low-glucose media and exposure to the stress-mediating hormone dexamethasone. Metabolites that were significantly different between bipolar and control subjects showed distinct separation by principal components analysis methods. The most statistically significant findings were observed in the perturbation experiments. The metabolite with the lowest p value in both the low-glucose and dexamethasone experiments was α-aminoadipate, whose intracellular level was consistently lower in bipolar subjects. Our study implicates α-aminoadipate as a possible biomarker in bipolar disorder that manifests under cellular stress. This is an intriguing finding given the known role of α-aminoadipate in the modulation of kynurenic acid in the brain, especially as abnormal kynurenic acid levels have been implicated in bipolar disorder.

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Metabolic Profiling of Human Blood Serum from Treated Patients with Bipolar Disorder Employing ¹H NMR Spectroscopy and Chemometrics

Cited by 63 publications

References 36 publications

Combined Application of NMR- and GC-MS-Based Metabonomics Yields a Superior Urinary Biomarker Panel for Bipolar Disorder

Combined Application of NMR- and GC-MS-Based Metabonomics Yields a Superior Urinary Biomarker Panel for Bipolar Disorder

Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder

Perturbational Profiling of Metabolites in Patient Fibroblasts Implicates α-Aminoadipate as a Potential Biomarker for Bipolar Disorder

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Metabolic Profiling of Human Blood Serum from Treated Patients with Bipolar Disorder Employing 1H NMR Spectroscopy and Chemometrics

Cited by 63 publications

References 36 publications

Combined Application of NMR- and GC-MS-Based Metabonomics Yields a Superior Urinary Biomarker Panel for Bipolar Disorder

Combined Application of NMR- and GC-MS-Based Metabonomics Yields a Superior Urinary Biomarker Panel for Bipolar Disorder

Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder

Perturbational Profiling of Metabolites in Patient Fibroblasts Implicates α-Aminoadipate as a Potential Biomarker for Bipolar Disorder

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Metabolic Profiling of Human Blood Serum from Treated Patients with Bipolar Disorder Employing ¹H NMR Spectroscopy and Chemometrics