Non-targeted Metabolomics Profiling of Plasma Samples From Patients With Major Depressive Disorder

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Oral D-ribose causes depressive-like behavior by altering glycerophospholipid metabolism via the gut-brain axis

Our previous work has shown that D-ribose (RIB)-induced depressive-like behaviors in mice. However, the relationship between variations in RIB levels and depression as well as potential RIB participation in depressive disorder is yet unknown. Here, a reanalysis of metabonomics data from depressed patients and depression model rats is performed to clarify whether the increased RIB level is positively correlated with the severity of depression. Moreover, we characterize intestinal epithelial barrier damage, gut microbial composition and function, and microbiota-gut-brain metabolic signatures in RIB-fed mice using colonic histomorphology, 16 S rRNA gene sequencing, and untargeted metabolomics analysis. The results show that RIB caused intestinal epithelial barrier impairment and microbiota-gut-brain axis dysbiosis. These microbial and metabolic modules are consistently enriched in peripheral (fecal, colon wall, and serum) and central (hippocampus) glycerophospholipid metabolism. In addition, three differential genera (Lachnospiraceae_UCG-006, Turicibacter, and Akkermansia) and two types of glycerophospholipids (phosphatidylcholine and phosphatidylethanolamine) have greater contributions to the overall correlations between differential genera and glycerophospholipids. These findings suggest that the disturbances of gut microbiota by RIB may contribute to the onset of depressive-like behaviors via regulating glycerophospholipid metabolism, and providing new insight for understanding the function of microbiota-gut-brain axis in depression.

The neuropsychopharmacology of acetyl-L-carnitine (LAC): basic, translational and therapeutic implications

Mitochondrial metabolism can contribute to nuclear histone acetylation among other epigenetic mechanisms. A central aspect of this signaling pathway is acetyl-L-carnitine (LAC), a pivotal mitochondrial metabolite best known for its role in fatty acid oxidation. Work from our and other groups suggested LAC as a novel epigenetic modulator of brain plasticity and a therapeutic target for clinical phenotypes of depression linked to childhood trauma. Aberrant mitochondrial metabolism of LAC has also been implicated in the pathophysiology of Alzheimer's disease. Furthermore, mitochondrial dysfunction is linked to other processes implicated in the pathophysiology of both major depressive disorders and Alzheimer's disease, such as oxidative stress, inflammation, and insulin resistance. In addition to the rapid epigenetic modulation of glutamatergic function, preclinical studies showed that boosting mitochondrial metabolism of LAC protects against oxidative stress, rapidly ameliorates insulin resistance, and reduces neuroinflammation by decreasing proinflammatory pathways such as NFkB in hippocampal and cortical neurons. These basic and translational neuroscience findings point to this mitochondrial signaling pathway as a potential target to identify novel mechanisms of brain plasticity and potential unique targets for therapeutic intervention targeted to specific clinical phenotypes.

Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Associations between prefrontal PI (16:0/20:4) lipid, TNC mRNA, and APOA1 protein in schizophrenia: A trans-omics analysis in post-mortem brain

Background

Though various mechanisms have been proposed for the pathophysiology of schizophrenia, the full extent of these mechanisms remains unclear, and little is known about the relationships among them. We carried out trans-omics analyses by comparing the results of the previously reported lipidomics, transcriptomics, and proteomics analyses; all of these studies used common post-mortem brain samples.

Methods

We collected the data from three aforementioned omics studies on 6 common post-mortem samples (3 schizophrenia patients and 3 controls), and analyzed them as a whole group sample. Three correlation analyses were performed for each of the two of three omics studies in these samples. In order to discuss the strength of the correlations in a limited sample size, the p-values of each correlation coefficient were confirmed using the Student's t-test. In addition, partial correlation analysis was also performed for some correlations, to verify the strength of the impact of each factor on the correlations.

Results

The following three factors were strongly correlated with each other: the lipid level of phosphatidylinositol (PI) (16:0/20:4), the amount of TNC mRNA, and the quantitative signal intensity of APOA1 protein. PI (16:0/20:4) and TNC showed a positive correlation, while PI (16:0/20:4) and APOA1, and TNC and APOA1 showed negative correlations. All of these correlations reached at p < 0.01. PI (16:0/20:4) and TNC were decreased in the prefrontal cortex of schizophrenia samples, while APOA1 was increased. Partial correlation analyses among them suggested that PI (16:0/20:4) and TNC have no direct correlation, but their relationships are mediated by APOA1.

Conclusion

The current results suggest that these three factors may provide new clues to elucidate the relationships among the candidate mechanisms of schizophrenia, and support the potential of trans-omics analyses as a new analytical method.

Levetiracetam Modulates EEG Microstates in Temporal Lobe Epilepsy

To determine the effects of Levetiracetam (LEV) therapy using EEG microstates analysis in a population of newly diagnosed Temporal Lobe Epilepsy (TLE) patients. We hypothesized that the impact of LEV therapy on the electrical activity of the brain can be globally explored using EEG microstates. Twenty-seven patients with TLE were examined. We performed resting-state microstate EEG analysis and compared microstate metrics between the EEG performed at baseline (EEG_pre) and after 3 months of LEV therapy (EEG_post). The microstates A, B, C and D emerged as the most stable. LEV induced a reduction of microstate B and D mean duration and occurrence per second (p < 0.01). Additionally, LEV treatment increased the directional predominance of microstate A to C and microstate B to D (p = 0.01). LEV treatment induces a modulation of resting-state EEG microstates in newly diagnosed TLE patients. Microstates analysis has the potential to identify a neurophysiological indicator of LEV therapeutic activity. This study of EEG microstates in people with epilepsy opens an interesting path to identify potential LEV activity biomarkers that may involve increased neuronal inhibition of the epileptic network.

Discovery and validation of acetyl-L-carnitine in serum for diagnosis of major depressive disorder and remission status through metabolomic approach

Major depressive disorder (MDD) is one of the most common psychiatric disorders that accompany psychophysiological and mood changes. However, the pathophysiology-based disease mechanism of MDD is not yet fully understood, and diagnosis is also conducted through interviews with clinicians and patients. Diagnosis and treatment of MDD are limited due to the absence of biomarkers underlying the pathophysiological mechanisms of MDD. Although various attempts have been made to discover metabolite biomarkers for the diagnosis and treatment response of MDD, problems with sample size and consistency of results have limited clinical application. In addition, it was reported that future biomarker studies must consider exposure to antidepressants, which is the main cause of heterogeneity in depression subgroups. Therefore, the purpose of this study is to discover and validate biomarkers for the diagnosis of depression in consideration of exposure to drug treatment including antidepressants that contribute to the heterogeneity of the MDD subgroup. In the biomarker discovery and validation set, the disease group consisted of a mixture of patients exposed and unexposed to drug treatment including antidepressants for the treatment of MDD. The serum metabolites that differed between the MDD patients and the control group were profiled using mass spectrometry. The validation set including the remission group was used to verify the effectiveness as a biomarker for the diagnosis of depression and determination of remission status. The presence of different metabolites between the two groups was confirmed through serum metabolite profiling between the MDD patient group and the control group. Finally, Acetylcarnitine was selected as a biomarker. In validation, acetylcarnitine was significantly decreased in MDD and was distinguished from remission status. This study confirmed that the discovered acetylcarnitine has potential as a biomarker for diagnosing depression and determining remission status, regardless of exposure to drug treatment including antidepressants.