A snapshot of plasma metabolites in first-episode schizophrenia: a capillary electrophoresis time-of-flight mass spectrometry study

Cerebrospinal fluid metabolomics identifies a key role of isocitrate dehydrogenase in bipolar disorder: evidence in support of mitochondrial dysfunction hypothesis

Although evidence for mitochondrial dysfunction in the pathogenesis of bipolar disorder (BD) has been reported, the precise biological basis remains unknown, hampering the search for novel biomarkers. In this study, we performed metabolomics of cerebrospinal fluid (CSF) from male BD patients (n=54) and age-matched male healthy controls (n=40). Subsequently, post-mortem brain analyses, genetic analyses, metabolomics of CSF samples from rats treated with lithium or valproic acid were also performed. After multivariate logistic regression, isocitric acid (isocitrate) levels were significantly higher in the CSF from BD patients than healthy controls. Furthermore, gene expression of two subtypes (IDH3A and IDH3B) of isocitrate dehydrogenase (IDH) in the dorsolateral prefrontal cortex from BD patients was significantly lower than that of controls, although the expression of other genes including, aconitase (ACO1, ACO2), IDH1, IDH2 and IDH3G, were not altered. Moreover, protein expression of IDH3A in the cerebellum from BD patients was higher than that of controls. Genetic analyses showed that IDH genes (IDH1, IDH2, IDH3A, IDH3B) and ACO genes (ACO1, ACO2) were not associated with BD. Chronic (4 weeks) treatment with lithium or valproic acid in rats did not alter CSF levels of isocitrate, and mRNA levels of Idh3a, Idh3b, Aco1 and Aco2 genes in the rat brain. These findings suggest that abnormality in the metabolism of isocitrate by IDH3A in the mitochondria plays a key role in the pathogenesis of BD, supporting the mitochondrial dysfunction hypothesis of BD. Therefore, IDH3 in the citric acid cycle could potentially be a novel therapeutic target for BD.

Tryptophan Metabolism and White Matter Integrity in Schizophrenia

Schizophrenia is associated with abnormalities in the structure and functioning of white matter, but the underlying neuropathology is unclear. We hypothesized that increased tryptophan degradation in the kynurenine pathway could be associated with white matter microstructure and biochemistry, potentially contributing to white matter abnormalities in schizophrenia. To test this, fasting plasma samples were obtained from 37 schizophrenia patients and 38 healthy controls and levels of total tryptophan and its metabolite kynurenine were assessed. The ratio of kynurenine to tryptophan was used as an index of tryptophan catabolic activity in this pathway. White matter structure and function were assessed by diffusion tensor imaging (DTI) and (1)H magnetic resonance spectroscopy (MRS). Tryptophan levels were significantly lower (p<0.001), and kynurenine/tryptophan ratios were correspondingly higher (p=0.018) in patients compared with controls. In patients, lower plasma tryptophan levels corresponded to lower structural integrity (DTI fractional anisotropy) (r=0.347, p=0.038). In both patients and controls, the kynurenine/tryptophan ratio was inversely correlated with frontal white matter glutamate level (r=-0.391 and -0.350 respectively, p=0.024 and 0.036). These results provide initial evidence implicating abnormal tryptophan/kynurenine pathway activity in changes to white matter integrity and white matter glutamate in schizophrenia.

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

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.

Metabolite signature for diagnosing major depressive disorder in peripheral blood mononuclear cells

BACKGROUND

Major depressive disorder (MDD) is a serious debilitating psychiatric disorder. However, the molecular mechanisms of MDD remain largely unknown, and no objective laboratory-based tests are available to diagnose this disorder.

METHODS

A gas chromatography-mass spectrometry (GC-MS) based metabolomic approach was used to compare peripheral blood mononuclear cells (PBMC) metabolic profiling of 50 first onset drug-naïve MDD subjects and 50 healthy controls (training samples), to identify potential metabolite biomarkers for MDD. An independent sample cohort including 58 MDD patients, 40 schizophrenia (SCZ) patients and 56 healthy controls (test samples) was used to validate diagnostic generalizability and specificity of identified biomarkers.

RESULTS

17 PBMC metabolites responsible for discriminating MDD group from healthy control group were identified. These metabolites were mainly involved in disturbances of energy and neurotransmitter metabolism. This PBMC metabolite signature could effectively discriminate MDD subjects from the healthy controls with an AUC of 0.926 in training samples and 0.870 in test samples. Moreover, this metabolite signature enabled distinguishing MDD subjects from schizophrenia subjects with an AUC of 0.899.

LIMITATIONS

This study was limited by potential confounding effects of different drug treatments in some MDD and schizophrenia subjects, and lack of animal studies to further validate the identified metabolite pathways in MDD.

CONCLUSION

These findings suggest that early disturbances of PBMC energy and neurotransmitter metabolism may be associated with the onset of MDD. This PBMC metabolite signature may facilitate development of a laboratory-based diagnostic test for MDD.

Blood metabolomics analysis identifies abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism in bipolar disorder

Background

Bipolar disorder (BD) is a severe and debilitating psychiatric disorder. However, the precise biological basis remains unknown, hampering the search for novel biomarkers. We performed a metabolomics analysis to discover novel peripheral biomarkers for BD.

Methods

We quantified serum levels of 116 metabolites in mood-stabilized male BD patients (n = 54) and age-matched male healthy controls (n = 39).

Results

After multivariate logistic regression, serum levels of pyruvate, N-acetylglutamic acid, α-ketoglutarate, and arginine were significantly higher in BD patients than in healthy controls. Conversely, serum levels of β-alanine, and serine were significantly lower in BD patients than in healthy controls. Chronic (4-weeks) administration of lithium or valproic acid to adult male rats did not alter serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, or arginine, but lithium administration significantly increased serum levels of α-ketoglutarate.

Conclusions

The metabolomics analysis demonstrated altered serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, and arginine in BD patients.

General significance

The present findings suggest that abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism play a role in the pathogenesis of BD.

•

Metabolomics analysis of serum sample from bipolar disorder (BD) was performed.

•

Pyruvate, N-acetylglutamic acid, α-ketoglutarate, and arginine were higher in BD.

•

β-alanine, and serine were lower in BD patients.

•

Abnormalities in citric acid cycle, urea cycle, and amino acid metabolism in BD.

Metabolomic Profiling of Post-Mortem Brain Reveals Changes in Amino Acid and Glucose Metabolism in Mental Illness Compared with Controls

Metabolomic profiling was carried out on 53 post-mortem brain samples from subjects diagnosed with schizophrenia, depression, bipolar disorder (SDB), diabetes, and controls. Chromatography on a ZICpHILIC column was used with detection by Orbitrap mass spectrometry. Data extraction was carried out with m/z Mine 2.14 with metabolite searching against an in-house database. There was no clear discrimination between the controls and the SDB samples on the basis of a principal components analysis (PCA) model of 755 identified or putatively identified metabolites. Orthogonal partial least square discriminant analysis (OPLSDA) produced clear separation between 17 of the controls and 19 of the SDB samples (R2CUM 0.976, Q2 0.671, p-value of the cross-validated ANOVA score 0.0024). The most important metabolites producing discrimination were the lipophilic amino acids leucine/isoleucine, proline, methionine, phenylalanine, and tyrosine; the neurotransmitters GABA and NAAG and sugar metabolites sorbitol, gluconic acid, xylitol, ribitol, arabinotol, and erythritol. Eight samples from diabetic brains were analysed, six of which grouped with the SDB samples without compromising the model (R2 CUM 0.850, Q2 CUM 0.534, p-value for cross-validated ANOVA score 0.00087). There appears on the basis of this small sample set to be some commonality between metabolic perturbations resulting from diabetes and from SDB.

Capillary Electrophoresis-Mass Spectrometry for Clinical Metabolomics

In clinical metabolomics, capillary electrophoresis-mass spectrometry (CE-MS) has become a very useful technique for the analysis of highly polar and charged metabolites in complex biologic samples. A comprehensive overview of recent developments in CE-MS for metabolic profiling studies is presented. This review covers theory, CE separation modes, capillary coatings, and practical aspects of CE-MS coupling. Attention is also given to sample pretreatment and data analysis strategies used for metabolomics. The applicability of CE-MS for clinical metabolomics is illustrated using samples ranging from plasma and urine to cells and tissues. CE-MS application to large-scale and quantitative clinical metabolomics is addressed. Conclusions and perspectives on this unique analytic strategy are presented.

Manual therapy ameliorates delayed-onset muscle soreness and alters muscle metabolites in rats

Delayed-onset muscle soreness (DOMS) can be induced by lengthening contraction (LC); it can be characterized by tenderness and movement-related pain in the exercised muscle. Manual therapy (MT), including compression of exercised muscles, is widely used as physical rehabilitation to reduce pain and promote functional recovery. Although MT is beneficial for reducing musculoskeletal pain (i.e. DOMS), the physiological mechanisms of MT remain unclear. In the present study, we first developed an animal model of MT in DOMS; LC was applied to the rat gastrocnemius muscle under anesthesia, which induced mechanical hyperalgesia 2–4 days after LC. MT (manual compression) ameliorated mechanical hyperalgesia. Then, we used capillary electrophoresis time-of-flight mass spectroscopy (CE-TOFMS) to investigate early effects of MT on the metabolite profiles of the muscle experiencing DOMS. The rats were divided into the following three groups; (1) normal controls, (2) rats with LC application (LC group), and (3) rats undergoing MT after LC (LC + MT group). According to the CE-TOFMS analysis, a total of 171 metabolites were detected among the three groups, and 19 of these metabolites were significant among the groups. Furthermore, the concentrations of eight metabolites, including branched-chain amino acids, carnitine, and malic acid, were significantly different between the LC + MT and LC groups. The results suggest that MT significantly altered metabolite profiles in DOMS. According to our findings and previous data regarding metabolites in mitochondrial metabolism, the ameliorative effects of MT might be mediated partly through alterations in metabolites associated with mitochondrial respiration.

Metabolite profiling in posttraumatic stress disorder

BACKGROUND

Traumatic stress does not only increase the risk for posttraumatic stress disorder (PTSD), but is also associated with adverse secondary physical health outcomes. Despite increasing efforts, we only begin to understand the underlying biomolecular processes. The hypothesis-free assessment of a wide range of metabolites (termed metabolite profiling) might contribute to the discovery of biological pathways underlying PTSD.

METHODS

Here, we present the results of the first metabolite profiling study in PTSD, which investigated peripheral blood serum samples of 20 PTSD patients and 18 controls. We performed liquid chromatography (LC) coupled to Quadrupole/Time-Of-Flight (QTOF) mass spectrometry. Two complementary statistical approaches were used to identify metabolites associated with PTSD status including univariate analyses and Partial Least Squares Discriminant Analysis (PLS-DA).

RESULTS

Thirteen metabolites displayed significant changes in PTSD, including four glycerophospholipids, and one metabolite involved in endocannabinoid signaling. A biomarker panel of 19 metabolites classifies PTSD with 85% accuracy, while classification accuracy from the glycerophospholipid with the highest differentiating ability already reached 82%.

CONCLUSIONS

This study illustrates the feasibility and utility of metabolite profiling for PTSD and suggests lipid-derived and endocannabinoid signaling as potential biological pathways involved in trauma-associated pathophysiology.

Metabolomics for laboratory diagnostics

Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice.

Carbonyl stress and schizophrenia

Appropriate biological treatment and psychosocial support are essential to achieve and maintain recovery for patients with schizophrenia. Despite extensive efforts to clarify the underlying disease mechanisms, the main cause and pathophysiology of schizophrenia remain unclear. This is due in large part to disease heterogeneity, which results in biochemical differences within a single disease entity. Other factors include variability across clinical symptoms and disease course, along with varied risk factors and treatment responses. Although schizophrenia's positive symptoms are largely managed through treatment with atypical antipsychotics, new classes of drugs are needed to address the unmet medical need for improving cognitive dysfunction and promoting recovery of negative symptoms in these patients. Accumulation of toxic reactive dicarbonyls, such as methylglyoxal, are typical indicators of carbonyl stress, and result in the modification of proteins and the formation of advanced glycation end products, such as pentosidine. In June 2010, we reported on idiopathic carbonyl stress in a subpopulation of schizophrenia patients, leading to a failure of metabolic systems with plasma pentosidine accumulation and serum pyridoxal depletion. Our findings suggest two markers, pentosidine and pyridoxal, as beneficial for distinguishing a specific subgroup of schizophrenics. We believe that this information, derived from in vitro and in vivo studies, is beneficial in the search for personalized and hopefully more effective treatment regimens in schizophrenia. Here, we define a subtype of schizophrenia based on carbonyl stress and the potential for using carbonyl stress as a biomarker in the challenge of overcoming heterogeneity in schizophrenia treatment.