Development of mass spectrometry-based relatively quantitative targeted method for amino acids and neurotransmitters: Applications in the diagnosis of major depression

Vacancy-Driven High-Performance Metabolic Assay for Diagnosis and Therapeutic Evaluation of Depression

Depression is one of the most common mental illnesses and is a well-known risk factor for suicide, characterized by low overall efficacy (<50%) and high relapse rate (40%). A rapid and objective approach for screening and prognosis of depression is highly desirable but still awaits further development. Herein, a high-performance metabolite-based assay to aid the diagnosis and therapeutic evaluation of depression by developing a vacancy-engineered cobalt oxide (Vo-Co3O4) assisted laser desorption/ionization mass spectrometer platform is presented. The easy-prepared nanoparticles with optimal vacancy achieve a considerable signal enhancement, characterized by favorable charge transfer and increased photothermal conversion. The optimized Vo-Co3O4 allows for a direct and robust record of plasma metabolic fingerprints (PMFs). Through machine learning of PMFs, high-performance depression diagnosis is achieved, with the areas under the curve (AUC) of 0.941-0.980 and an accuracy of over 92%. Furthermore, a simplified diagnostic panel for depression is established, with a desirable AUC value of 0.933. Finally, proline levels are quantified in a follow-up cohort of depressive patients, highlighting the potential of metabolite quantification in the therapeutic evaluation of depression. This work promotes the progression of advanced matrixes and brings insights into the management of depression.

The anti-depression effect and potential mechanism of the petroleum ether fraction of CDB: Integrated network pharmacology and metabolomics

The combination of Chaidangbo (CDB) is an antidepressant traditional Chinese medicine (TCM) prescription simplified by Xiaoyaosan (a classic antidepressant TCM prescription) through dismantling research, which has the effect of dispersing stagnated liver qi and nourishing blood in TCM theory. Although the antidepressant effect of CBD has been confirmed in animal studies, the material basis and possible molecular mechanism for antidepressant activity in CBD have not been clearly elucidated. Herein, we investigated the effects and potential mechanisms of CDB antidepressant fraction (petroleum ether fraction of CDB, PEFC) on chronic unpredictable mild stress (CUMS)-induced depression-like behavior in mice using network pharmacology and metabolomics. First, a UPLC-QE/MS was employed to identify the components of PEFC. To extract active ingredients, SwissADME screening was used to the real PEFC components that were found. Potential PEFC antidepressant targets were predicted based on a network pharmacology approach, and a pathway enrichment analysis was performed for the predicted targets. Afterward, a CUMS mouse depression model was established and LC-MS-based untargeted hippocampal metabolomics was performed to identify differential metabolites, and related metabolic pathways. Finally, the protein expressions in mouse hippocampi were determined by Western blot to validate the network pharmacology and metabolomics deduction. A total of 16 active compounds were screened in SwissADME that acted on 73 core targets of depression, including STAT3, MAPKs, and NR3C1; KEGG enrichment analysis showed that PEFC modulated signaling pathways such as PI3K-Akt signaling pathway, endocrine resistance, and MAPK to exert antidepressant effects. PEFC significantly reversed abnormalities of hippocampus metabolites in CUMS mice, mainly affecting the synthesis and metabolism of glycine, serine, and threonine, impacting catecholamine transfer and cholinergic synapses and regulating the activity of the mTOR signaling pathway. Furthermore, Western blot analysis confirmed that PEFC significantly influenced the main protein levels of the PI3K/Akt/mTOR signaling pathways in the hippocampus of mice subjected to CUMS. This study integrated metabolomics, network pharmacology and biological verification to explore the potential mechanism of PEFC in treating depression, which is related to the regulation of amino acid metabolism dysfunction and the activation of PI3K/Akt/mTOR signaling pathways in the hippocampus. The comprehensive strategy also provided a reasonable way for unveiling the pharmacodynamic mechanisms of multi-components, multi-targets, and multi-pathways in TCM with antidepressant effect.

Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

Metabolomics on depression: A comparison of clinical and animal research

BACKGROUND

Depression is a major cause of suicide and mortality worldwide. This study aims to conduct a systematic review to identify metabolic biomarkers and pathways for major depressive disorder (MDD), a prevalent subtype of clinical depression.

METHODS

We searched for metabolomics studies on depression published between January 2000 and January 2023 in the PubMed and Web of Science databases. The reported metabolic biomarkers were systematically evaluated and compared. Pathway analysis was implemented using MetaboAnalyst 5.0.

RESULTS

We included 26 clinical studies on MDD and 78 metabolomics studies on depressive-like animal models. A total of 55 and 77 high-frequency metabolites were reported consistently in two-thirds of clinical and murine studies, respectively. In the comparison between murine and clinical studies, we identified 9 consistently changed metabolites (tryptophan, tyrosine, phenylalanine, methionine, fumarate, valine, deoxycholic acid, pyruvate, kynurenic acid) in the blood, 1 consistently altered metabolite (indoxyl sulfate) in the urine and 14 disturbed metabolic pathways in both types of studies. These metabolic dysregulations and pathways are mainly implicated in enhanced inflammation, impaired neuroprotection, reduced energy metabolism, increased oxidative stress damage and disturbed apoptosis, laying solid molecular foundations for MDD.

LIMITATIONS

Due to unavailability of original data like effect-size results in many metabolomics studies, a meta-analysis cannot be conducted, and confounding factors cannot be fully ruled out.

CONCLUSIONS

This systematic review delineated metabolic biomarkers and pathways related to depression in the murine and clinical samples, providing opportunities for early diagnosis of MDD and the development of novel diagnostic targets.

The Role of Catecholamines in the Pathogenesis of Diseases and the Modified Electrodes for Electrochemical Detection of Catecholamines: A Review

Catecholamines (CAs), which include adrenaline, noradrenaline, and dopamine, are neurotransmitters and hormones that critically regulate the cardiovascular system, metabolism, and stress response in the human body. The abnormal levels of these molecules can lead to the development of various diseases, including pheochromocytoma and paragangliomas, Alzheimer's disease, and Takotsubo cardiomyopathy. Due to their low cost, high sensitivity, flexible detection strategies, ease of integration, and miniaturization, electrochemical techniques have been extensively employed in the detection of CAs, surpassing traditional analytical methods. Electrochemical detection of CAs in real samples is challenging due to the tendency of poisoning electrode. Chemically modified electrodes have been widely used to solve the problems of poor sensitivity and selectivity faced by bare electrodes. There are a few articles that provide an overview of electrochemical detection and efficient enrichment of CAs, but there is a dearth of updates on the role of CAs in the pathogenesis of diseases. Additionally, there is still a lack of systematic synthesis with a focus on modified electrodes for electrochemical detection. Thus, this review provides a summary of the recent clinical pathogenesis of CAs and the modified electrodes for electrochemical detection of CAs published between 2017 and 2022. Moreover, challenges and future perspectives are also highlighted. This work is expected to provide useful guidance to researchers entering this interdisciplinary field, promoting further development of CAs pathogenesis, and developing more novel chemically modified electrodes for the detection of CAs.

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.

Advanced Nanomaterials-Based Electrochemical Biosensors for Catecholamines Detection: Challenges and Trends

Catecholamines, including dopamine, epinephrine, and norepinephrine, are considered one of the most crucial subgroups of neurotransmitters in the central nervous system (CNS), in which they act at the brain's highest levels of mental function and play key roles in neurological disorders. Accordingly, the analysis of such catecholamines in biological samples has shown a great interest in clinical and pharmaceutical importance toward the early diagnosis of neurological diseases such as Epilepsy, Parkinson, and Alzheimer diseases. As promising routes for the real-time monitoring of catecholamine neurotransmitters, optical and electrochemical biosensors have been widely adopted and perceived as a dramatically accelerating development in the last decade. Therefore, this review aims to provide a comprehensive overview on the recent advances and main challenges in catecholamines biosensors. Particular emphasis is given to electrochemical biosensors, reviewing their sensing mechanism and the unique characteristics brought by the emergence of nanotechnology. Based on specific biosensors' performance metrics, multiple perspectives on the therapeutic use of nanomaterial for catecholamines analysis and future development trends are also summarized.

Untargeted and targeted mass spectrometry reveal the effects of theanine on the central and peripheral metabolomics of chronic unpredictable mild stress-induced depression in juvenile rats

l-theanine has been shown to have a therapeutic effect on depression. However, whether l-theanine has an excellent preventive effect on depression in children and adolescents and what its mechanism is have not been well explained. Given the complexity of the pathogenesis of depression, this study investigated the preventive effect and mechanism of l-theanine on depression in juvenile rats by combining serum and hippocampal metabolomic strategies. Behavioral tests, hippocampal tissue sections, and serum and hippocampal biochemical indexes were studied, and the results confirmed the preventive effect of l-theanine. Untargeted reversed-phase liquid chromatography-quadrupole-time-of-flight mass spectrometry and targeted hydrophilic interaction liquid chromatography-triple quadrupole mass spectrometry were developed to analyze the metabolism changes in the serum and hippocampus to screen for potential biomarkers related to l-theanine treatment. The results suggested that 28 abnormal metabolites in the serum and hippocampus that were considered as potential biomarkers returned to near-normal levels after l-theanine administration. These biomarkers were involved in various metabolic pathways, mainly including amino acid metabolism and lipid metabolism. The levels of amino acids and neurotransmitters in the phenylalanine, tryptophan, and glutamic acid pathways were significantly reduced after l-theanine administration compared with chronic unpredictable mild stress-induced rats. In summary, l-theanine had a significant preventive effect on depression and achieved its preventive results on depression by regulating various aspects of the body, such as amino acids, lipids, and inflammation. This research systematically analyzed the mechanism of l-theanine in preventing depression and laid the foundation for applying l-theanine to prevent depression in children and adolescents.

In-depth investigation of the Silymarin effect on the pharmacokinetic parameters of sofosbuvir, GS-331007 and ledipasvir in rat plasma using LC-MS

The use of complementary medicine (CMD) for liver support in Hepatitis C virus (HCV) patients sometimes coincides with the administration of oral antiviral drugs to eradicate the virus. This calls for a deep investigation of CMD effects on the pharmacokinetic parameters of these drugs to ensure their safety and efficacy. Silymarin (SLY), as a CMD, was selected to be given orally to healthy male rats with sofosbuvir (SFB) and ledipasvir (LED), a common regimen in HCV treatment. A new and sensitive LC-MS method was validated for the bioassay of SLY, LED, SFB and its inactive metabolite, GS-331007, in spiked plasma with lower limits of quantitation of 10, 1, 4 and 10 ng/ml, respectively. Moreover, the method was further applied to conduct a full pharmacokinetic profile of SFB, GS-331007 and ledipasvir with and without SLY. It was found that co-administration of SLY may expose the patient to unplanned high serum concentrations of SFB and LED. This could be accompanied by a decrease in SFB efficacy, potentially leading to therapeutic failure and the emergence of viral resistance.

Development of a Simple, Underivatized Method for Rapid Determination of Free Amino Acids in Honey Using Dilute-and-Shoot Strategy and Liquid Chromatography-Tandem Mass Spectrometry

A simple, fast and reliable analytical method was developed for 20 free amino acids (FAAs) determination in honey samples through a dilute-and-shoot strategy and hydrophilic interaction liquid chromatography tandem mass spectrometry. Compared with previous reports, direct dilution by water has significantly reduced the matrix effect and facilitated full extraction of FAAs. Further, a 5 min determination method was established with an acetonitrile–water mobile phase system with 0.1% formic acid addition. The established method was validated and demonstrated several advantages including short detection time, wide linear range over 3–4 orders of magnitude, high sensitivity down to 0.1 ng/mL and negligible matrix effect. Twenty FAAs were determined in 10 honey samples from different botanical origins by this method, and 19 FAAs were found. This general applicable method was also promising for fast determination of FAAs in other practical samples.

Brain-Type Glycogen Phosphorylase Is Crucial for Astrocytic Glycogen Accumulation in Chronic Social Defeat Stress-Induced Depression in Mice

Astrocytic glycogen plays an important role in brain energy metabolism. However, the contribution of glycogen metabolism to stress-induced depression remains unclear. Chronic social defeat stress was used to induce depression-like behaviors in mice, assessed with behavioral tests. Glycogen concentration in the medial prefrontal cortex (mPFC) and the expression of key enzymes of the glycogen metabolism were investigated using Western blots, immunofluorescent staining, electron microscopy, and biochemical assays. Stereotaxic surgery and viral-mediated gene transfer were applied to knockdown or overexpress brain-type glycogen phosphorylase (PYGB) in the mPFC. The glycogen content increased in the mPFC after stress. Glycogenolytic dysfunction due to inactivation of PYGB was responsible for glycogen accumulation. Behavioral tests on astrocyte-specific PYGB overexpression mice showed that augmenting astrocytic PYGB reduces susceptibility to depression when compared with stress-susceptible mice. Conversely, PYGB genetic down-regulation in the mPFC was sufficient to induce glycogen accumulation and depression-like behaviors. Furthermore, PYGB overexpression in the mPFC decreases susceptibility to depression, at least partially by rescuing glycogen phosphorylase activity to maintain glycogen metabolism homeostasis during stress. These findings indicate that (1) glycogen accumulation occurs in mice following stress and (2) glycogenolysis reprogramming leads to glycogen accumulation in astrocytes and PYGB contributes to stress-induced depression-like behaviors. Pharmacological tools acting on glycogenolysis might constitute a promising therapy for depression.

Association Between Non-Suicidal Self-Injury and Gut Microbial Characteristics in Chinese Adolescent

PURPOSE

By exploring the gut-related microbiota differences of adolescents with non-suicidal self-injury (NSSI) and depression (without NSSI) and healthy volunteers, we provide a theoretical basis for the prevention and control of NSSI in adolescents through intestinal microecological regulation.

PATIENTS AND METHODS

A total of 99 subjects were recruited in Guangdong Province, China, including 51 adolescents with NSSI (KD), 24 healthy adolescents (NOR1), and 24 depression adolescents without NSSI (NOR2). General clinical data and fecal samples were collected from all subjects, who were assessed using the NSSI Behavioral Questionnaire and the 24-item Hamilton Depression Scale. The taxonomic composition of the gut microbiota was determined using the 16S rDNA gene sequencing method.

RESULTS

There were significant differences in diversity between the KD and NOR1, and the species uniformity index of the KD according to the Shannon and Simpson indices was significantly reduced compared with that of the NOR1 (4.81 vs 5.21, p<0.01; 0.02 vs 0.01, p<0.05). The relative abundances were different among the KD, NOR1 and NOR2, as reflected at the taxonomic levels of class, order, family, genus, and species. Bacteroides were the dominant flora of the KD and NOR2, while Mitsuokella was the dominant flora that distinguished the KD from the NOR2.

CONCLUSION

We found that gut microbiota diversity was decreased in adolescents with NSSI, and the relative abundance was altered at different taxonomic levels. These results enrich the understanding of the relationship between NSSI and depression and the gut microbiota, Supporting that NSSI and depression are not homologous disorders. What is more, it establishes the basis for exploring the mechanisms of flora action in NSSI, providing a possible direction for NSSI to achieve a better prognosis and prevent relapse.

Integrated Network Pharmacology and GC-MS-Based Metabolomics to Investigate the Effect of Xiang-Su Volatile Oil Against Menopausal Depression

Menopausal depression perplexes a great number of women in later life. Xiangfu-Zisu (Xiang-Su), a traditional Chinese herbal pair composed of rhizomes of Cyperus rotundus L. (Xiangfu) and leaves of Perilla frutescens (L.) Britt. (Zisu), is frequently reported with antidepressant-like effects. The volatile oil from Xiangfu and Zisu has shown good antidepressant action, but its mechanism is still unclear. This study aimed to investigate the pharmacological mechanism of Xiang-Su (XS) volatile oil against menopausal depression through gas chromatography–mass spectrometry (GC-MS)-based network pharmacology and metabolomics. First, ADME screening was performed on actual detected components of XS volatile oil to obtain active constituents, and then duplicates of active constituent–related targets and menopausal depression–related targets were collected. These duplicates were considered as targets for XS volatile oil against menopausal depression, followed by GO and KEGG enrichment analyses. It showed that a total of 64 compounds were identified in XS volatile oil, and 38 active compounds were screened out. 42 overlapping genes between 144 compound-related genes and 780 menopausal depression–related genes were obtained. Results showed that targets of SLC6A4 and SLC6A3, regulation of serotonergic and dopaminergic synapses, were involved in the antidepressant mechanism of XS volatile oil. Next, antidepressant-like effect of XS volatile oil was validated in menopausal rats by ovariectomy (OVX) combined with chronic unpredictable mild stress (CUMS). Behavioral tests, biochemical analysis, and GC-MS–based non-targeted plasma metabolomics were employed to validate the antidepressant effect of XS volatile oil. Experimental evidence demonstrated that XS volatile oil reversed behavioral parameters in the sucrose preference test (SPT), open-field test (OFT), forced swim test (FST), and serum estradiol levels in OVX rats. Furthermore, results of metabolomics indicated that XS volatile oil mainly acts on regulating metabolic pathways of phenylalanine, tyrosine and tryptophan biosynthesis, tyrosine metabolism, and tryptophan metabolism, which were corresponding with the above-predicted results. These data suggest that network pharmacology combined with metabolomics provides deep insight into the antidepressant effect of XS volatile oil, which includes regulating key targets like SLC6A4 and SLC6A3, and pathways of serotonergic and dopaminergic synapses.

Development and application of sequential window acquisition of all theoretical mass spectra data acquisition modes on ultra-high-performance liquid chromatography triple-quadrupole/time-of-flight mass spectrometry for metabolic profiling of amino acids in human plasma

Accumulating evidence suggests that amino acids are important indicators of nutritional and metabolic status. A high-resolution mass spectrometry method based on sequential window acquisition of all theoretical mass spectra acquisition was developed for the simultaneous determination of 16 amino acids in human plasma. Sample preparation by protein precipitation using a mixture of acetonitrile and formic acid was followed by a BEH Amide column. The superiority of this method was investigated by comparing it to time-of-flight scan and multiple reaction monitoring modes. The limit of detection in sequential window acquisition of all theoretical mass spectra mode for threonine, methionine, histidine, citrulline, and tryptophan is 0.1 ng on the column; for lysine and asparagine is 0.2 ng; for alanine, pyroglutamic acid, leucine, ornithine, and aspartate is 0.5 ng, for arginine is 1.0 ng; for glutamate and serine is 2.0 ng; for glutamine is 10.0 ng. This method was linear in the range 0.8-40 μg/mL for arginine, citrulline, glutamate, histidine, leucine, methionine, pyroglutamic acid, threonine, tryptophan; 2-100 μg/mL for asparagine, aspartate, lysine, ornithine, serine; and 4-200 μg/mL for alanine, glutamine with good accuracy and precision. Significantly different levels in 11 amino acids were observed between childhood and adulthood, representing the growth and development of individuals relating to the level of amino acids.

Altered Fecal Metabolites and Colonic Glycerophospholipids Were Associated With Abnormal Composition of Gut Microbiota in a Depression Model of Mice

The microbiota–gut–brain axis has been considered to play an important role in the development of depression, but the underlying mechanism remains unclear. The gastrointestinal tract is home to trillions of microbiota and the colon is considered an important site for the interaction between microbiota and host, but few studies have been conducted to evaluate the alterations in the colon. Accordingly, in this study, we established a chronic social defeated stress (CSDS) mice model of depression. We applied 16S rRNA gene sequencing to assess the gut microbial composition and gas and liquid chromatography–mass spectroscopy to identify fecal metabolites and colonic lipids, respectively. Meanwhile, we used Spearman’s correlation analysis method to evaluate the associations between the gut microbiota, fecal metabolites, colonic lipids, and behavioral index. In total, there were 20 bacterial taxa and 18 bacterial taxa significantly increased and decreased, respectively, in the CSDS mice. Further, microbial functional prediction demonstrated a disturbance of lipid, carbohydrate, and amino acid metabolism in the CSDS mice. We also found 20 differential fecal metabolites and 36 differential colonic lipids (in the category of glycerolipids, glycerophospholipids, and sphingolipids) in the CSDS mice. Moreover, correlation analysis showed that fecal metabolomic signature was associated with the alterations in the gut microbiota composition and colonic lipidomic profile. Of note, three lipids [PC(16:0/20:4), PG(22:6/22:6), and PI(18:0/20:3), all in the category of glycerophospholipids] were significantly associated with anxiety- and depression-like phenotypes in mice. Taken together, our results indicated that the gut microbiota might be involved in the pathogenesis of depression via influencing fecal metabolites and colonic glycerophospholipid metabolism.

Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model

As an important agricultural production area in China, the Yangtze River Economic Belt has a large amount of water resources and rich types of energy. Water and energy resources are the supporting basis of food production, and the production and use of energy also need to consume a large amount of water resources. The three affect each other and are interdependent. Paying attention to the synergistic security of water-energy-food system in the Yangtze River Economic Belt is important for regional economic development. This paper uses the pressure-state-response (PSR) model and selects 27 indicators to build an evaluation index system of the regional water-energy-food system. We use the random forest model to evaluate the security level of the Yangtze River Economic Belt from 2008 to 2017, and the Haken model is employed to identify the driving factors that dominate the synergistic evolution of the system. Then we take the identified factors as the key control variables under each scenario and launch a scenario simulation of some provinces in the Yangtze River Economic Belt in 2025. The results show that due to the improvement of water and energy utilization efficiency and the advancement of agricultural production technology, the level of water-energy-food security in the Yangtze River Economic Belt improved significantly from 2008 to 2017. Each province performs differently in different subsystems, with water resources security being better in the upper reaches and Zhejiang and Shanghai in the lower reaches, and food security being better in the middle and lower reaches. The level of energy security is high in Sichuan, Yunnan, and Guizhou in the upper reaches and Shanghai and Anhui in the lower reaches. According to the results of scenario prediction for Jiangsu Province and Hubei Province in 2025, implementing moderate management in accordance with current management objectives can increase the overall security of the system to level 4. The two provinces should focus on controlling water resources and energy consumption and improving the utilization efficiency of water and energy in agricultural production.

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

BACKGROUND

Major depressive disorder (MDD) is a neuropsychiatric disorder caused by multiple factors. Although there are clear guidelines for the diagnosis of MDD, the direct and objective diagnostic methods remain inadequate thus far.

METHODS

This study aims to discover peripheral biomarkers in patients with MDD and promote the diagnosis of MDD. Plasma samples of healthy controls (HCs, n = 52) and patients with MDD (n = 38) were collected, and then, metabolism analysis was performed using ultrahigh-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Heatmap analysis was performed to identify the different metabolites. Meanwhile, receiver operating characteristic (ROC) curves of these differential metabolites were generated.

RESULTS

Six differential metabolites were found by LC-MS/MS analysis. Three of these were increased, including L-aspartic acid (Asp), diethanolamine, and alanine. Three were decreased, including O-acetyl-L-carnitine (LAC), cystine, and fumarate. In addition, LAC, Asp, fumarate, and alanine showed large areas under the curve (AUCs) by ROC analysis.

CONCLUSION

The study explored differences in peripheral blood between depressed patients and HCs. These results indicated that differential metabolites with large AUCs may have the potential to be promising biomarkers for the diagnosis of MDD.