Publications by authors named "Guowang Xu"

403 Publications

Deep Neural Network Pretrained by Weighted Autoencoders and Transfer Learning for Retention Time Prediction of Small Molecules.

Anal Chem 2021 Nov 15. Epub 2021 Nov 15.

School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.

Retention time (RT) prediction contributes to identification of small molecules measured by high-performance liquid chromatography coupled with high-resolution mass spectrometry. Deep learning algorithms based on big data can enhance the accuracy of RT prediction. But at different chromatographic conditions, RTs of compounds are different, and the number of compounds with known RTs is small in most cases. Therefore, the transfer of big data is necessary. In this work, a strategy using a deep neural network (DNN) pretrained by weighed autoencoders and transfer learning (DNNpwa-TL) was proposed to efficiently predict RTs of compounds. The loss function in the autoencoders was calculated with features weighted by mutual information. Then, a DNN pretrained by weighted autoencoders (DNNpwa) was produced. For other specific chromatographic methods, the transfer learning model DNNpwa-TLs were built through fine-tuning the DNNpwa with the help of some compounds with known RTs to conduct the RT prediction. With the above strategy, a DNNpwa was first built with the METLIN small molecule retention time data set containing 80 038 small molecule compounds. A median relative error of 3.1% and a mean relative error of 4.9% were achieved. Then, 17 data sets from different chromatographic methods were studied, and the results showed that the performance of DNNpwa-TL was better than those of other deep learning models. Besides, DNNpwa-TL outperformed random forest, gradient boost, least absolute shrinkage and selection operator regression, and DNN for most of the 17 data sets. Therefore, DNNpwa-TL can provide an efficient method to perform RT prediction of small molecule compounds for different chromatographic methods and conditions.
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http://dx.doi.org/10.1021/acs.analchem.1c03250DOI Listing
November 2021

Exercise prevents fatty liver by modifying the compensatory response of mitochondrial metabolism to excess substrate availability.

Mol Metab 2021 Oct 22:101359. Epub 2021 Oct 22.

Institute for Clinical Chemistry and Pathobiochemistry, Department for Diagnostic Laboratory Medicine, University Hospital Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Germany; Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tuebingen, Tuebingen, Germany. Electronic address:

Objective: Liver mitochondria adapt to high-calorie intake. We investigated how exercise alters the early compensatory response of mitochondria, thus preventing fatty liver disease as a long-term consequence of overnutrition.

Methods: We compared the effects of a steatogenic high-energy diet (HED) for six weeks on mitochondrial metabolism of sedentary and treadmill-trained C57BL/6N mice. We applied multi-OMICs analyses to study the alterations in the proteome, transcriptome, and lipids in isolated mitochondria of liver and skeletal muscle as well as in whole tissue and examined the functional consequences by high-resolution respirometry.

Results: HED increased the respiratory capacity of isolated liver mitochondria, both in sedentary and in trained mice. However, proteomics analysis of the mitochondria and transcriptomics indicated that training modified the adaptation of the hepatic metabolism to HED on the level of respiratory complex I, glucose oxidation, pyruvate, and acetyl-CoA metabolism, and lipogenesis. Training also counteracted the HED-induced increase in fasting insulin, glucose tolerance, and liver fat by lowering diacylglycerol species and c-Jun N-terminal kinase (JNK) phosphorylation in the livers of trained HED-fed mice, two mechanisms that can reverse hepatic insulin resistance. In skeletal muscle, the combination of HED and training improved the oxidative capacity to a greater extent than training alone by increasing respiration of isolated mitochondria and total mitochondrial protein content.

Conclusion: We provide a comprehensive insight into the early adaptations of mitochondria in the liver and skeletal muscle to HED and endurance training. Our results suggest that exercise disconnects the HED-induced increase in mitochondrial substrate oxidation from pyruvate and acetyl-CoA-driven lipid synthesis. This could contribute to the prevention of deleterious long-term effects of high fat and sugar intake on hepatic mitochondrial function and insulin sensitivity.
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http://dx.doi.org/10.1016/j.molmet.2021.101359DOI Listing
October 2021

Metabolome-wide association study of serum exogenous chemical residues in a cohort with 5 major chronic diseases.

Environ Int 2021 Oct 8;158:106919. Epub 2021 Oct 8.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address:

Background: Chronic diseases have become main killers affecting the health of human, and environmental pollution is a major health risk factor that cannot be ignored. It has been reported that exogenous chemical residues including pesticides, herbicides, fungicides, veterinary drugs and persistent organic pollutants are associated with chronic diseases. However, the evidence for their relationship is equivocal and the underlying mechanisms are unclear.

Objectives: We aim to investigate the linkages between serum exogenous chemical residues and 5 main chronic diseases including obesity, hyperuricemia, hypertension, diabetes and dyslipidemia, and further reveal the metabolic perturbations of chronic diseases related to exogenous chemical residue exposure, then gain potential mechanism insight at the metabolic level.

Methods: LC-MS-based targeted and nontargeted methods were respectively performed to quantify exogenous chemical residues and acquire metabolic profiling of 496 serum samples from chronic disease patients. Non-parametric test, correlation and regression analyses were carried out to investigate the association between exogenous chemical residues and chronic diseases. Metabolome-wide association study combined with the meeting-in-the-middle strategy and mediation analysis was performed to reveal and explain exposure-related metabolic disturbances and their risk to chronic diseases.

Results: In the association analysis of 106 serum exogenous chemical residues and 5 chronic diseases, positive associations of serum perfluoroalkyl substances (PFASs) with hyperuricemia were discovered while other associations were not significant. 240 exposure markers of PFASs and 84 disease markers of hyperuricemia were found, and 47 of them were overlapped and considered as putative effective markers. Serum uric acid, amino acids, cholesterol, carnitines, fatty acids, glycerides, glycerophospholipids, ceramides, and a part of sphingolipids were positively correlated with PFASs and associated with increased risk for hyperuricemia. Creatine, creatinine, glyceryl monooleate, phosphatidylcholine 36:6, phosphatidylethanolamine 40:6, cholesterol and sphingolipid 36:1;2O were significant markers which mediated the associations of the residues with hyperuricemia.

Conclusions: Our study demonstrated a significantly positive association between PFASs exposure and hyperuricemia. The most significant metabolic abnormality was lipid metabolism which not only was positively associated with PFASs, but also increased the risk of hyperuricemia.
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http://dx.doi.org/10.1016/j.envint.2021.106919DOI Listing
October 2021

Novel Stable Isotope-Resolved Metabolomics Method for a Small Number of Cells Using Chip-Based Nanoelectrospray Mass Spectrometry.

Anal Chem 2021 10 4;93(41):13765-13773. Epub 2021 Oct 4.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

Stable isotope-resolved metabolomics (SIRM) can provide metabolic conversion information of specific targets; it is a powerful tool for cell metabolism studies. The common analytical platform for SIRM is chromatography-mass spectrometry, which requires a large number of cells and is not suitable for precious rare cell analysis. To study a small number of cells, we established a novel SIRM method using chip-based nanoelectrospray mass spectrometry (MS). C-glutamine was taken as an example; the unlabeled and C-labeled cells were cultured and extracted in a 96-well plate and then directly injected into MS and analyzed in full scan mode and parallel reaction monitoring (PRM) mode targeting 44 glutamine-derived metabolites and their isotopologues. To define focused metabolite-related MS2 fragments produced in the PRM, a new strategy was proposed including MS2 exact / matching, MS2 false positive filtering, and MS2 fragment grouping to remove the interfering MS2 ions. In total, 292 and 349 pairs of paired MS2 ions were obtained in positive and negative ionization modes, respectively. By searching spectra databases, 31 targeted metabolites with their isotopologues were identified and their characteristic product ions were confirmed for MS2 quantification. The relative quantification was achieved by MS2 quantification, which showed better sensitivity and accuracy than common MS1-based quantification. Finally, this method was applied to isocitrate dehydrogenase I-mutated glioma cells for revealing the effects of triptolide on glioma cell metabolism using U-C-glutamine as a labeling substrate.
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http://dx.doi.org/10.1021/acs.analchem.1c01507DOI Listing
October 2021

Association of plasma branched-chain amino acids with overweight: A Mendelian randomization analysis.

Obesity (Silver Spring) 2021 Oct 7;29(10):1708-1718. Epub 2021 Sep 7.

Institute of Health Sciences, China Medical University, Shenyang, Liaoning Province, China.

Objective: A Mendelian randomization (MR) framework was applied to disentangle the causal effect of branched-chain amino acids (BCAAs) and overweight/obesity in Chinese adolescents.

Methods: Circulating BCAA levels were measured by liquid chromatography coupled with mass spectrometry. A total of 7 BCAAs and 12 BMI-associated common variants identified from released genome-wide association study results were genotyped. Furthermore, a bidirectional MR approach was undertaken to disentangle the causal effect of BCAAs and overweight/obesity, using two-stage regression.

Results: Using the inverse variance-weighted strategy and the weighted genetic scoring instruments, the estimated odds ratio per 1-arbitrary-unit increase in the total BCAA level on overweight and obesity odds after adjusting for age and sex was 2.40 (95% CI: 1.38 to 3.42, p < 0.001) and 2.55 (95% CI: 1.35 to 4.82, p = 0.004), respectively. Furthermore, additional MR tests were undertaken using a reversed model, testing the causal effect of increasing BMI variants on total BCAA level. By contrast, no evidence that increased BMI was causally associated with the total BCAA level (estimated β associated with 1-kg/m increase in BMI = 0.05, 95% CI: -0.17 to 0.28, p = 0.642) was observed.

Conclusions: In summary, BCAAs may be causally associated with overweight/obesity or, rather, a congenital dysmetabolism of BCAAs could be a cause of overweight/obesity in adolescents.
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http://dx.doi.org/10.1002/oby.23240DOI Listing
October 2021

Low-dose PCB126 exposure disrupts cardiac metabolism and causes hypertrophy and fibrosis in mice.

Environ Pollut 2021 Dec 31;290:118079. Epub 2021 Aug 31.

Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China. Electronic address:

The residue of polychlorinated biphenyls (PCBs) exists throughout the environment and humans are subject to long-term exposure. As such, the potential environmental and health risk caused by low-dose exposure to PCBs has attracted much attention. 3, 3', 4, 4', 5-pentachlorobiphenyl (PCB126), the highest toxicity compound among dioxin-like-PCBs, has been widely used and mass-produced. Cardiotoxicity is PCB126's crucial adverse effect. Maintaining proper metabolism underlies heart health, whereas the impact of PCB126 exposure on cardiac metabolic patterns has yet to be elucidated. In this study, we administered 0.5 and 50 μg/kg bw of PCB126 to adult male mice weekly by gavage for eight weeks. Pathological results showed that low-dose PCB126 exposure induced heart injury. Metabolomic analysis of the heart tissue exposed to low-dose PCB126 identified 59 differential metabolites that were involved in lipid metabolism, amino acid metabolism, and the tricarboxylic acid (TCA) cycle. Typical metabolomic characteristic of cardiac hypertrophy was reflected by accumulation of fatty acids (e.g. palmitic, palmitoleic, and linoleic acid), and disturbance of carbohydrates including D-glucose and intermediates in TCA cycle (fumaric, succinic, and citric acid). Low-dose PCB126 exposure increased glycine and threonine, the amino acids necessary for the productions of collagen and elastin. Besides, PCB126-exposed mice exhibited upregulation of collagen synthesis enzymes and extracellular matrix proteins, indicative of cardiac fibrosis. Moreover, the expression of genes related to TGFβ/PPARγ/MMP-2 signaling pathway was perturbed in the PCB126-treated hearts. Together, our results reveal that low-dose PCB126 exposure disrupts cardiac metabolism correlated with hypertrophy and fibrosis. This study sheds light on the underlying mechanism of PCBs' cardiotoxicity and identifies potential sensitive biomarkers for environmental monitoring.
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http://dx.doi.org/10.1016/j.envpol.2021.118079DOI Listing
December 2021

[Advances in application of molecularly imprinted polymers to the detection of polar pesticide residues].

Se Pu 2021 Sep;39(9):930-940

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

Polar pesticides can be primarily classified as fungicides, herbicides, and insecticides; their rich variety and low cost have led to their extensive utilization in agriculture. However, the overuse of polar pesticides can lead to environmental contamination, such as water or soil pollution, which can also increase the risk of pesticide exposure among human life directly, or indirectly through contact with animal and plant-derived food. There are considerable differences in the physical and chemical properties of polar pesticides, as well as their trace amounts in complex food and environmental samples, posing immense challenges to their accurate detection. As a kind of artificially prepared selective adsorbent, molecularly imprinted polymers (MIPs) possess specific recognition sites complementary to template molecules in terms of the spatial structure, size, and chemical functional groups. With many advantages such as easy preparation, low cost, as well as good chemical and mechanical stability, MIPs have been widely applied in sample pretreatment and the analysis of polar pesticide residues. MIPs are typically used as adsorption materials in solid phase extraction (SPE) methods, including magnetic solid phase extraction (MSPE), dispersed solid phase extraction (DSPE), and stir bar sorptive extraction (SBSE). To rapidly detect polar pesticide residues with high sensitivity, MIPs are also used in the preparation of fluorescent sensors and electrochemical sensors. Furthermore, MIPs can be employed as the substrate in surface-enhanced Raman spectroscopy and as the substrate for the ion source in mass spectrometry for polar pesticide residue analysis. Thus far, various molecularly imprinted materials have been reported for the efficient separation and analysis of polar pesticide residues in various complex matrices. However, there is no review that summarizes the recent advances in MIPs for the determination of polar pesticides. This review introduces imprinting strategies and polymerization methods for MIPs, and briefly summarizes some new molecular imprinting strategies and preparation technologies. The application of MIPs in recent years (particularly the last five years) to the detection of polar pesticide residues including neonicotinoids, organophosphorus, triazines, azoles, and urea is then systematically summarized. Finally, the future development direction and trends for MIPs are proposed considering existing challenges, with the aim of providing reference to guide future research on MIPs in the field of polar pesticide residue detection.
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http://dx.doi.org/10.3724/SP.J.1123.2021.03005DOI Listing
September 2021

Nontargeted screening method for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry.

Food Chem 2022 Feb 21;369:130928. Epub 2021 Aug 21.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address:

Nontargeted screening of both veterinary drugs and their metabolites is important for comprehensive safety evaluation of animal-derived foods. In this study, a novel nontargeted screening strategy was developed for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry. First, an in-house database of mass spectra including 3,710 veterinary drugs and their metabolites was constructed. Second, fragmentation characteristics of parent drugs and their metabolites in mass spectrometry were investigated and summarized. Then, a nontargeted screening procedure was established based on fragmentation characteristics to screen unknown parent drugs and their metabolites. Finally, the strategy was applied to 33 egg samples, and four veterinary drugs and three drug metabolites were determined and identified. These results showed that the developed strategy can realize suspect and nontargeted screening of veterinary drugs and their metabolites, and can also be applied to other animal-derived foods.
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http://dx.doi.org/10.1016/j.foodchem.2021.130928DOI Listing
February 2022

Proline metabolism in cancer.

Amino Acids 2021 Aug 14. Epub 2021 Aug 14.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.

Cancer cells often change their metabolism to support uncontrolled proliferation. Proline is the only proteogenic secondary amino acid that is abundant in the body. Recent studies have shown that proline metabolism plays an important role in metabolic reprogramming and affects the occurrence and development of cancer. Proline metabolism is related to ATP production, protein and nucleotide synthesis, and redox homeostasis in tumor cells. Proline can be synthesized by aldehyde dehydrogenase family 18 member A1 (ALDH18A1) and delta1-pyrroline-5-carboxylate reductase (PYCR), up-regulating ALDH18A1 and PYCR can promote the proliferation and invasion of cancer cells. As the main storage of proline, collagen can influence cancer cells proliferation, invasion, and metastasis. Its synthesis depends on the hydroxylation of proline catalyzed by prolyl 4-hydroxylases (P4Hs), which will affect the plasticity and metastasis of cancer cells. The degradation of proline occurs in the mitochondria and involves an oxidation step catalyzed by proline dehydrogenase/proline oxidase (PRODH/POX). Proline catabolism has a dual role in cancer, linking apoptosis with the survival and metastasis of cancer cells. In addition, it has been demonstrated that the regulation of proline metabolic enzymes at the genetic and post-translational levels is related to cancer. This article reviews the role of proline metabolic enzymes in cancer proliferation, apoptosis, metastasis, and development. Research on proline metabolism may provide a new strategy for cancer treatment.
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http://dx.doi.org/10.1007/s00726-021-03060-1DOI Listing
August 2021

Comparison of the metabolome in urine prior and eight weeks after radical prostatectomy uncovers pathologic and molecular features of prostate cancer.

J Pharm Biomed Anal 2021 Oct 31;205:114288. Epub 2021 Jul 31.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, 116023, China. Electronic address:

Prostate cancer (PCa) is associated with cellular metabolism alterations leading to changes of the metabolome. So far, studies investigating these alterations mainly focused on comparisons of metabolite profiles of PCa patients and healthy controls. In the present study we compared for the first time metabolite profiles in a significant number of paired urine samples collected before and eight weeks after radical prostatectomy (rPX) in 34 patients with PCa. Our comprehensive non-targeted liquid chromatographic-mass spectrometric metabolomics approach covered > 3000 metabolite ion masses. We annotated 23 metabolites showing significant changes eight weeks after rPX. While the levels of uridine and six acylcarnitines in urine were increased before surgery, lower levels were detected for 16 metabolites, like e.g. citrate, phenyl-lactic acid, choline, myo-inositol, emphasizing a relevant pathophysiological role of these biomarkers and the associated metabolic pathways. These results have important implications for potential use of metabolome analyses for detection of prostate cancer and related pathologic and molecular features.
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http://dx.doi.org/10.1016/j.jpba.2021.114288DOI Listing
October 2021

Development of a novel analytical method for inflammation and immunity-related metabolites in serum based on liquid chromatography tandem mass spectrometry.

Talanta 2021 Nov 24;234:122631. Epub 2021 Jun 24.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China. Electronic address:

Some metabolites have been found to play key roles in inflammation and immunity events that are associated with diseases such as cancer, diabetes and cytokine release syndrome. Characterization upon the inflammation and immunity-related metabolites (IIMs) will be helpful to the assessment of related pathological states. Although these metabolites have been partially reported in previous studies, the methods for specific measurement of them remain lacking. In the present study, a liquid chromatography - mass spectrometry based method was developed for the targeted analyses of 45 IIMs including amino acids, organic acids, phosphatidylcholines (PCs), polyunsaturated fatty acids and hormones selected based on the literature knowledge. Direct extraction with dansyl-chloride in acetonitrile was proved to be the most efficient and time-saving strategy, in which precipitation, extraction and derivatization were integrated. IIMs derivatized for 4 min and quenched for 2 min revealed the most comprehensive abundance. Based on the defined conditions, all the IIMs had a low limit of detection smaller than 1 ng/mL with the linear range greater than three orders of magnitude. The relative standard derivations of intra-day and inter-day precisions were ranged from 2.2% to 13.4% and 1.7% to 19.5%, respectively. The recovery rates and accuracy in low concentration were 98.9% ± 5.6% and 106.7% ± 11.6%, in medium concentration were 97.1% ± 6.8% and 106.9% ± 9.5%, and in high concentration were 98.4% ± 8.9% and 98.1% ± 8.1%, respectively. Matrix effect and stability were ranged from -37.8% to 35.6% and 2.9% to 14.2%, respectively. To show the usefulness of the method, serum IIMs in hepatitis B virus (HBV) infected patients and healthy subjects were determined and compared. Bile acids, lipoxygenase-mediated lipid mediators and non-enzymatic products showed global increases, whereas most of LysoPCs and cyclooxygenase-mediated prostaglandin D2 decreased in HBV serum samples. This study provided a robust approach for the characterization of IIMs.
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http://dx.doi.org/10.1016/j.talanta.2021.122631DOI Listing
November 2021

Facile Synthesis of Antibody-Coupled Polydopamine-Coated Magnetic Graphene Oxide Composites for Efficient Immunopurification and Metabolomics Analysis of Mitochondria.

Anal Chem 2021 08 4;93(32):11099-11107. Epub 2021 Aug 4.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

As a vital hub, a mitochondrion houses metabolic pathways that play important roles in cellular physiology. Aberrant metabolites occurring in mitochondria are closely associated with the emergence and progression of various mitochondria-related diseases. Therefore, a simple and versatile approach to efficiently purify intact mitochondria is urgently needed to precisely and comprehensively characterize the composition and abundance of the mitochondrial metabolome in different physiological and pathological states. In this work, novel immunoaffinitive magnetic composites [email protected]@[email protected] were prepared to achieve highly selective isolation of intact mitochondria from three different hepatocytes (LO2, HepG2, and Huh7). The prepared composites inherit combined merits, including strong magnetic responsiveness, excellent stability, and specific and high affinity between antibody TOM20 and mitochondrial outer membrane protein. These mitochondria attached on [email protected]@[email protected] were characterized by the western blot and fluorescence microscopy to confirm their purity and integrity, which are vital for reliable mitochondrial metabolic analysis. Subsequently, ultrahigh-performance liquid chromatography-high-resolution mass spectrometry-based untargeted metabolomics analysis was conducted to characterize the metabolomes in the immunopurified mitochondria and whole cells. Notably, the metabolite profiles of whole cells and mitochondria including itaconic acid, acetylcarnitine, malic acid, etc., were significantly different. These data underscore the importance of determining metabolites at the mitochondrial level, which would supplement us new knowledge at the subcellular level.
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http://dx.doi.org/10.1021/acs.analchem.1c01101DOI Listing
August 2021

Systematic, Modifying Group-Assisted Strategy Expanding Coverage of Metabolite Annotation in Liquid Chromatography-Mass Spectrometry-Based Nontargeted Metabolomics Studies.

Anal Chem 2021 08 30;93(31):10916-10924. Epub 2021 Jul 30.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

From microbes to human beings, nontargeted metabolic profiling by liquid chromatography (LC)-mass spectrometry (MS) has been commonly used to investigate metabolic alterations. Still, a major challenge is the annotation of metabolites from thousands of detected features. The aim of our research was to go beyond coverage of metabolite annotation in common nontargeted metabolomics studies by an integrated multistep strategy applying data-dependent acquisition (DDA)-based ultrahigh-performance liquid chromatography (UHPLC)-high-resolution mass spectrometry (HRMS) analysis followed by comprehensive neutral loss matches for characteristic metabolite modifications and database searches in a successive manner. Using pooled human urine as a model sample for method establishment, we found 22% of the detected compounds having modifying structures. Major types of metabolite modifications in urine were glucuronidation (33%), sulfation (20%), and acetylation (6%). Among the 383 annotated metabolites, 100 were confirmed by standard compounds and 50 modified metabolites not present in common databases such as human metabolite database (HMDB) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were structurally elucidated. Practicability was tested by the investigation of urines from pregnant women diagnosed with gestational diabetes mellitus vs healthy controls. Overall, 83 differential metabolites were annotated and 67% of them were modified metabolites including five previously unreported compounds. To conclude, the systematic modifying group-assisted strategy can be taken as a useful tool to extend the number of annotated metabolites in biological and biomedical nontargeted studies.
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http://dx.doi.org/10.1021/acs.analchem.1c01715DOI Listing
August 2021

Strategy for Nontargeted Metabolomic Annotation and Quantitation Using a High-Resolution Spectral-Stitching Nanoelectrospray Direct-Infusion Mass Spectrometry with Data-Independent Acquisition.

Anal Chem 2021 08 22;93(30):10528-10537. Epub 2021 Jul 22.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.

Direct-infusion nanoelectrospray ionization high-resolution mass spectrometry (DI-nESI-HRMS) is an alternative approach to chromatography-MS-based techniques for nontargeted metabolomics, offering a high sample throughout. However, its annotation accuracy of analytes is still full of challenges. In this study, we proposed a strategy for the annotation and quantitation of nontargeted metabolomic data using a spectral-stitching DI-nESI-HRMS with data-independent acquisition. The metabolite annotation strategy included the isotopic distribution, MS/MS spectrum similarity, and precursor and product ion correlation as well as matching of the extracted metabolite features along with the targeted metabolite precursors. Two groups of mixed standard solutions containing 40 and 79 metabolites were, respectively, used to establish the metabolite annotation strategy and validate its reliability. The results showed that the detected standards could be well annotated at top three explanations and total qualitative percentages were 100% (40 of 40) for the standard solution and 94.9% (74 of 78) for the standards spiked into the serum matrix. The intensity of the precursor ions was used for quantitation except for isomers, which were quantified by the intensities of the characteristic product ions if available. Finally, the strategy was applied to study serum metabolomics in diabetes, and the results demonstrated that it is promising for a large-scale cohort metabolomic study.
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http://dx.doi.org/10.1021/acs.analchem.1c01480DOI Listing
August 2021

Lipid Profiling of 20 Mammalian Cells by Capillary Microsampling Combined with High-Resolution Spectral Stitching Nanoelectrospray Ionization Direct-Infusion Mass Spectrometry.

Anal Chem 2021 07 16;93(29):10031-10038. Epub 2021 Jul 16.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

Studies of cellular metabolism can provide profound insights into the underlying molecular mechanisms and metabolic function. To date, the majority of cellular metabolism studies based on chromatography-mass spectrometry (MS) require population cells to obtain informative metabolome. These methods are not only time-consuming but also not suitable for amount-limited cell samples such as circulating tumor cells, stem cells, and neurons. Therefore, it is extremely essential to develop analytical methods enabling to detect metabolome from tens of cells in a high-throughput and high-sensitivity way. In this work, a novel platform for rapid and sensitive detection of lipidome in 20 mammalian cells was proposed using capillary microsampling combined with high-resolution spectral stitching nanoelectrospray ionization direct-infusion MS. It can be used to collect cells rapidly and accurately via the capillary microprobe, extract lipids directly in a 96-well plate using a spray solvent, and detect more than 500 lipids covering 19 lipid subclasses within 3 min. This novel platform was successfully applied to study the lipid features of different cancer cell types and subtypes as well as target cells from tissue samples. This study provides a strategy for determining the lipid species with rich information in tens of cells and demonstrates great potential for clinical applications.
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http://dx.doi.org/10.1021/acs.analchem.1c00373DOI Listing
July 2021

Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices.

Nat Methods 2021 07 8;18(7):747-756. Epub 2021 Jul 8.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.

Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome. Simultaneous quantification of many metabolites within complex mixtures can additionally be complicated by ion suppression, fragmentation and the presence of isomers. Here we present guidelines covering sample preparation, replication and randomization, quantification, recovery and recombination, ion suppression and peak misidentification, as a means to enable high-quality reporting of liquid chromatography- and gas chromatography-mass spectrometry-based metabolomics-derived data.
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http://dx.doi.org/10.1038/s41592-021-01197-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8592384PMC
July 2021

Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry.

Cancers (Basel) 2021 Jun 23;13(13). Epub 2021 Jun 23.

Sorbonne Paris Nord University, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center Inserm U1153, Inrae U1125, Cnam, University of Paris (CRESS), 74 Rue Marcel Cachin, CEDEX, 93017 Bobigny, France.

Background: The prevention and early screening of PCa is highly dependent on the identification of new biomarkers. In this study, we investigated whether plasma metabolic profiles from healthy males provide novel early biomarkers associated with future risk of PCa.

Methods: Using the (SU.VI.MAX) cohort, we identified plasma samples collected from 146 PCa cases up to 13 years prior to diagnosis and 272 matched controls. Plasma metabolic profiles were characterized using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS).

Results: Orthogonal partial least squares discriminant analysis (OPLS-DA) discriminated PCa cases from controls, with a median area under the receiver operating characteristic curve (AU-ROC) of 0.92 using a 1000-time repeated random sub-sampling validation. Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) identified the top 10 most important metabolites ( < 0.001) discriminating PCa cases from controls. Among them, phosphate, ethyl oleate, eicosadienoic acid were higher in individuals that developed PCa than in the controls during the follow-up. In contrast, 2-hydroxyadenine, sphinganine, L-glutamic acid, serotonin, 7-keto cholesterol, tiglyl carnitine, and sphingosine were lower.

Conclusion: Our results support the dysregulation of amino acids and sphingolipid metabolism during the development of PCa. After validation in an independent cohort, these signatures may promote the development of new prevention and screening strategies to identify males at future risk of PCa.
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http://dx.doi.org/10.3390/cancers13133140DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8268247PMC
June 2021

How to Screen and Prevent Metabolic Syndrome in Patients of PCOS Early: Implications From Metabolomics.

Front Endocrinol (Lausanne) 2021 2;12:659268. Epub 2021 Jun 2.

Department of Gynecology, the First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China.

Background: Polycystic ovary syndrome (PCOS) is a complex reproductive endocrine disorder. And metabolic syndrome (MS) is an important bridge for PCOS patients to develop other diseases, such as diabetes and coronary heart disease. Our aim was to study the potential metabolic characteristics of PCOS-MS and identify sensitive biomarkers so as to provide targets for clinical screening, diagnosis, and treatment.

Methods: In this study, 44 PCOS patients with MS, 34 PCOS patients without MS, and 32 healthy controls were studied. Plasma samples of subjects were tested by ultraperformance liquid chromatography (UPLC) system combined with LTQ-orbi-trap mass spectrometry. The changes of metabolic characteristics from PCOS to PCOS-MS were systematically analyzed. Correlations between differential metabolites and clinical characteristics of PCOS-MS were assessed. Differential metabolites with high correlation were further evaluated by the receiver operating characteristic (ROC) curve to identify their sensitivity as screening indicators.

Results: There were significant differences in general characteristics, reproductive hormone, and metabolic parameters in the PCOS-MS group when compared with the PCOS group and healthy controls. We found 40 differential metabolites which were involved in 23 pathways when compared with the PCOS group. The metabolic network further reflected the metabolic environment, including the interaction between metabolic pathways, modules, enzymes, reactions, and metabolites. In the correlation analysis, there were 11 differential metabolites whose correlation coefficient with clinical parameters was greater than 0.4, which were expected to be taken as biomarkers for clinical diagnosis. Besides, these 11 differential metabolites were assessed by ROC, and the areas under curve (AUCs) were all greater than 0.7, with a good sensitivity. Furthermore, combinational metabolic biomarkers, such as glutamic acid + leucine + phenylalanine and carnitine C 4: 0 + carnitine C18:1 + carnitine C5:0 were expected to be sensitive combinational biomarkers in clinical practice.

Conclusion: Our study provides a new insight to understand the pathogenesis mechanism, and the discriminating metabolites may help screen high-risk of MS in patients with PCOS and provide sensitive biomarkers for clinical diagnosis.
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http://dx.doi.org/10.3389/fendo.2021.659268DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8207510PMC
June 2021

A high throughput lipidomics method and its application in atrial fibrillation based on 96-well plate pretreatment and liquid chromatography-mass spectrometry.

J Chromatogr A 2021 Aug 24;1651:462271. Epub 2021 May 24.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, P. R. China. Electronic address:

Successful applications of lipidomics in clinic need study large-scale samples, and the bottlenecks are in throughput and robustness of the lipid analytical method. Here, we report an untargeted lipidomics method by combining high throughput pretreatment in the 96-well plate with ultra-high performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry. The developed method was validated to have satisfactory analytical characteristics in terms of linearity, repeatability and extraction recovery. It can be used to handle 96 samples simultaneously in 25 min and detect 441 lipids in plasma sample. Storage stability investigation on lipid extracts provided an operable procedure for large-scale sample analysis and demonstrated most lipids were stable in autosampler at 10 °C within 36 h and at -80 °C within 72 h after the pretreatment. To prove the usefulness, the method was employed to investigate abnormal plasma lipidome related to atrial fibrillation. A biomarker panel with the area under the curve (AUC) values of 0.831 and 0.745 was achieved in the discovery and external validation sets, respectively. These results showed that the developed method is applicable for large-scale biological sample handling and lipid analysis of plasma.
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http://dx.doi.org/10.1016/j.chroma.2021.462271DOI Listing
August 2021

Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis.

Front Oncol 2021 7;11:666320. Epub 2021 May 7.

Department of Urology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai, China.

Objectives: To identify and validate a biomarker panel by serum metabolic profiling for improvement of PCa diagnosis.

Materials And Methods: Totally, 134 individuals were included in this study. Among them, 39 PCa patients and 45 control patients (negative prostate biopsy) were involved in the discovery phase and 50 healthy controls were enrolled for validation phase of metabolomics study. LC-MS Analysis was used for the identification of the serum metabolites of patients.

Results: Logistics regression analysis shows that 5 metabolites [dMePE(18:0/18:2), PC(16:0/20:2), PS(15:0/18:2), SM(d16:0/24:1], Carnitine C14:0) were significantly changed in PCa patients compared with control patients. A metabolic panel (MET) was calculated, showing a significantly higher diagnostic performance than PSA in differentiating PCa from control patients [AUC (MET . PSA): 0.823 ± 0.046 . 0.712 ± 0.057, p<0.001]. Moreover, this panel was superior to PSA in distinguishing PCa from negative prostate biopsies when PSA levels were less than 20 ng/ml [AUC (MET . PSA]: 0.836 ± 0.050 . 0.656 ± 0.067, p<0.001]. In the validation set, the MET panel yielded an AUC of 0.823 in distinguishing PCa patients from healthy controls, showing a significant improvement of PCa detection.

Conclusions: The metabolite biomarker panel discovered in this study presents a good diagnostic performance for the detection of PCa.
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http://dx.doi.org/10.3389/fonc.2021.666320DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138432PMC
May 2021

Metabolome-Genome-Wide Association Study (mGWAS) Reveals Novel Metabolites Associated with Future Type 2 Diabetes Risk and Susceptibility Loci in a Case-Control Study in a Chinese Prospective Cohort.

Glob Chall 2021 Apr 23;5(4):2000088. Epub 2021 Mar 23.

CAS Key Laboratory of Separation Science for Analytical Chemistry Dalian Institute of Chemical Physics Chinese Academy of Sciences 457 Zhongshan Road Dalian 116023 China.

In a Chinese prospective cohort, 500 patients with new-onset type 2 diabetes (T2D) within 4.61 years and 500 matched healthy participants are selected as case and control groups, and randomized into discovery and validation sets to discover the metabolite changes before T2D onset and the related diabetogenic loci. A serum metabolomics analysis reveals that 81 metabolites changed significantly before T2D onset. Based on binary logistic regression, eight metabolites are defined as a biomarker panel for T2D prediction. Pipecolinic acid, carnitine C14:0, epinephrine and phosphatidylethanolamine 34:2 are first found associated with future T2D. The addition of the biomarker panel to the clinical markers (BMI, triglycerides, and fasting glucose) significantly improves the predictive ability in the discovery and validation sets, respectively. By associating metabolomics with genomics, a significant correlation ( < 5.0 × 10) between eicosatetraenoic acid and the FADS1 (rs174559) gene is observed, and suggestive correlations ( < 5.0 × 10) between pipecolinic acid and CHRM3 (rs535514), and leucine/isoleucine and WWOX (rs72487966) are discovered. Elevated leucine/isoleucine levels increased the risk of T2D. In conclusion, multiple metabolic dysregulations are observed to occur before T2D onset, and the new biomarker panel can help to predict T2D risk.
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http://dx.doi.org/10.1002/gch2.202000088DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8025395PMC
April 2021

Serum lipid profiling analysis and potential marker discovery for ovarian cancer based on liquid chromatography-Mass spectrometry.

J Pharm Biomed Anal 2021 May 26;199:114048. Epub 2021 Mar 26.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.

Low early diagnosis rate and unclear pathogenesis are the primary reasons for the high mortality of epithelial ovarian cancer (EOC). Lipidomics is a powerful tool for marker discovery and mechanism explanation. Hence, a ultra high-performance liquid chromatography-mass spectrometry based non-targeted lipidomics analysis was performed to acquire lipid profiling of 153 serum samples including healthy control (HC, n = 50), benign ovarian tumor (BOT, n = 41), and EOC (n = 62) to reveal lipid disturbance, then differential lipids were verified in another sample set including 187 sera. Significant lipid disturbance occurred in BOT and EOC, fatty acid, lyso-phosphatidylcholine, and lyso-phosphatidylethanolamine were observed to be increased in BOT and EOC subjects, while phosphatidylcoline, ether phosphatidylcoline (PC-O), ether phosphatidylethanolamine (PE-O), and sphingomyelin significantly decreased. Compared with BOT, PC-Os and PE-Os presented a greater reduction in EOC, and serum ceramide increased only in EOC. Moreover, potential markers consisting of 4 lipids were defined and validated for EOC diagnosis. High areas under the curve (0.854∼0.865 and 0.903∼0.923 for distinguishing EOC and early EOC from non-cancer, respectively) as well as good specificity and sensitivity were obtained. This study not only revealed the characteristics of lipid metabolism in EOC, but also provided a potential marker pattern for aiding EOC diagnosis.
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http://dx.doi.org/10.1016/j.jpba.2021.114048DOI Listing
May 2021

Prognosis prediction of hepatocellular carcinoma after surgical resection based on serum metabolic profiling from gas chromatography-mass spectrometry.

Anal Bioanal Chem 2021 May 2;413(12):3153-3165. Epub 2021 Apr 2.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, Liaoning, China.

Comprehensive prognostic risk prediction of hepatocellular carcinoma (HCC) after surgical treatment is particularly important for guiding clinical decision-making and improving postoperative survival. Hence, we aimed to build prognostic models based on serum metabolomics data, and assess the prognostic risk of HCC within 5 years after surgical resection. A pseudotargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomics method was applied to analyze serum profiling of 78 HCC patients. Important metabolic features with discriminant ability were identified by a novel network-based metabolic feature selection method based on combinational significance index (N-CSI). Subsequently, phenylalanine and galactose were further identified to be relevant with mortality by the Cox regression analysis, while galactose and tyrosine were associated with recurrence and metastasis. Two models to predict risk of mortality (risk score of overall survival, RS) and risk of recurrence and metastasis (risk score of disease-free survival, RS) were generated based on two panels of metabolites, respectively, which present favorable ability to predict prognosis of HCC, especially when combined with clinical staging system. The performance of models was further validated in an external independent cohort from 91 HCC patients. This study demonstrated that metabolomics is a powerful tool for risk screening of HCC prognosis.
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http://dx.doi.org/10.1007/s00216-021-03281-zDOI Listing
May 2021

Improving the lipid extraction yield from Chlorella based on the controllable electroporation of cell membrane by pulsed electric field.

Bioresour Technol 2021 Jun 6;330:124933. Epub 2021 Mar 6.

Laboratory of Advanced Technology of Power & Electrical Engineering, Tsinghua Shenzhen International Graduate School(SIGS), Tsinghua University, Shenzhen, Guangdong, 518055, China.

In order to solve the increasingly serious problems of energy and environment, microalgae are used as a raw material for extracting lipids to produce biodiesel. Prior to the extraction of lipids, microalgae were treated with high-voltage pulsed electric field (PEF) to break the cell membrane. It was found that the lipid extraction yield depends on the electric field strength (E) and the specific energy input (Wsp), and has a certain relationship with the cell disintegration rate of Chlorella. The perforation degree of the Chlorella's cell membrane by PEF treatment is controllable, moderate perforation can be ensured by controlling the power parameters. PEF treatment significantly improved the extraction yield of lipids. Compared with the test samples without PEF treatment, PEF treatment increased the lipid extraction yields by up to 166.67%. However, an excessively high voltage will cause the quality of the extracted biodiesel to decrease.
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http://dx.doi.org/10.1016/j.biortech.2021.124933DOI Listing
June 2021

Comprehensive metabolic profiling of Parkinson's disease by liquid chromatography-mass spectrometry.

Mol Neurodegener 2021 01 23;16(1). Epub 2021 Jan 23.

Center for Clinical Research on Neurological Diseases, The First Affiliated Hospital, Dalian Medical University, 193 Lianhe Road, Dalian, China.

Background: Parkinson's disease (PD) is a prevalent neurological disease in the elderly with increasing morbidity and mortality. Despite enormous efforts, rapid and accurate diagnosis of PD is still compromised. Metabolomics defines the final readout of genome-environment interactions through the analysis of the entire metabolic profile in biological matrices. Recently, unbiased metabolic profiling of human sample has been initiated to identify novel PD metabolic biomarkers and dysfunctional metabolic pathways, however, it remains a challenge to define reliable biomarker(s) for clinical use.

Methods: We presented a comprehensive metabolic evaluation for identifying crucial metabolic disturbances in PD using liquid chromatography-high resolution mass spectrometry-based metabolomics approach. Plasma samples from 3 independent cohorts (n = 460, 223 PD, 169 healthy controls (HCs) and 68 PD-unrelated neurological disease controls) were collected for the characterization of metabolic changes resulted from PD, antiparkinsonian treatment and potential interferences of other diseases. Unbiased multivariate and univariate analyses were performed to determine the most promising metabolic signatures from all metabolomic datasets. Multiple linear regressions were applied to investigate the associations of metabolites with age, duration time and stage of PD. The combinational biomarker model established by binary logistic regression analysis was validated by 3 cohorts.

Results: A list of metabolites including amino acids, acylcarnitines, organic acids, steroids, amides, and lipids from human plasma of 3 cohorts were identified. Compared with HC, we observed significant reductions of fatty acids (FFAs) and caffeine metabolites, elevations of bile acids and microbiota-derived deleterious metabolites, and alterations in steroid hormones in drug-naïve PD. Additionally, we found that L-dopa treatment could affect plasma metabolome involved in phenylalanine and tyrosine metabolism and alleviate the elevations of bile acids in PD. Finally, a metabolite panel of 4 biomarker candidates, including FFA 10:0, FFA 12:0, indolelactic acid and phenylacetyl-glutamine was identified based on comprehensive discovery and validation workflow. This panel showed favorable discriminating power for PD.

Conclusions: This study may help improve our understanding of PD etiopathogenesis and facilitate target screening for therapeutic intervention. The metabolite panel identified in this study may provide novel approach for the clinical diagnosis of PD in the future.
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http://dx.doi.org/10.1186/s13024-021-00425-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7825156PMC
January 2021

Alteration of lipids and amino acids in plasma distinguish schizophrenia patients from controls: A targeted metabolomics study.

Psychiatry Clin Neurosci 2021 Apr 5;75(4):138-144. Epub 2021 Feb 5.

NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Background: Schizophrenia (SCZ) is a serious psychiatric disorder. Metabolite disturbance is an important pathogenic factor in schizophrenic patients. In this study, we aim to identify plasma lipid and amino acid biomarkers for SCZ using targeted metabolomics.

Methods: Plasma from 76 SCZ patients and 50 matched controls were analyzed using the LC/MS-based multiple reaction monitoring (MRM) metabolomics approach. A total of 182 targeted metabolites, including 22 amino acids and 160 lipids or lipid-related metabolites were observed. We used binary logistic regression analysis to determine whether the lipid and amino acid biomarkers could discriminate SCZ patients from controls. The area under the curve (AUC) from receiver operation characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the biomarkers panel.

Results: We identified 19 significantly differentially expressed metabolites between the SCZ patients and the controls (false discovery rate < 0.05), including one amino acid and 18 lipids or lipid-related metabolites. The binary logistic regression-selected panel showed good diagnostic performance in the drug-naïve group (AUC = 0.936) and all SCZ patients (AUC = 0.948), especially in the drug-treated group (AUC = 0.963).

Conclusions: Plasma lipids and amino acids showed significant dysregulation in SCZ, which could effectively discriminate SCZ patients from controls. The LC/MS/MS-based approach provides reliable data for the objective diagnosis of SCZ.
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http://dx.doi.org/10.1111/pcn.13194DOI Listing
April 2021

Association of Serum Bile Acids Profile and Pathway Dysregulation With the Risk of Developing Diabetes Among Normoglycemic Chinese Adults: Findings From the 4C Study.

Diabetes Care 2021 02 18;44(2):499-510. Epub 2020 Dec 18.

The First Hospital of Jilin University, Changchun, China

Objective: Comprehensive assessment of serum bile acids (BAs) aberrations before diabetes onset remains inconclusive. We examined the association of serum BA profile and coregulation with the risk of developing type 2 diabetes mellitus (T2DM) among normoglycemic Chinese adults.

Research Design And Methods: We tested 23 serum BA species in subjects with incident diabetes ( = 1,707) and control subjects ( = 1,707) matched by propensity score (including age, sex, BMI, and fasting glucose) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study, which was composed of 54,807 normoglycemic Chinese adults with a median follow-up of 3.03 years. Multivariable-adjusted odds ratios (ORs) for associations of BAs with T2DM were estimated using conditional logistic regression.

Results: In multivariable-adjusted logistic regression analysis, per SD increment of unconjugated primary and secondary BAs were inversely associated with incident diabetes, with an OR (95% CI) of 0.89 (0.83-0.96) for cholic acid, 0.90 (0.84-0.97) for chenodeoxycholic acid, and 0.90 (0.83-0.96) for deoxycholic acid ( < 0.05 and false discovery rate <0.05). On the other hand, conjugated primary BAs (glycocholic acid, taurocholic acid, glycochenodeoxycholic acid, taurochenodeoxycholic acid, and sulfated glycochenodeoxycholic acid) and secondary BA (tauroursodeoxycholic acid) were positively related with incident diabetes, with ORs ranging from 1.11 to 1.19 (95% CIs ranging between 1.05 and 1.28). In a fully adjusted model additionally adjusted for liver enzymes, HDL cholesterol, diet, 2-h postload glucose, HOMA-insulin resistance, and waist circumference, the risk estimates were similar. Differential correlation network analysis revealed that perturbations in intraclass (i.e., primary and secondary) and interclass (i.e., unconjugated and conjugated) BA coregulation preexisted before diabetes onset.

Conclusions: These findings reveal novel changes in BAs exist before incident T2DM and support a potential role of BA metabolism in the pathogenesis of diabetes.
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http://dx.doi.org/10.2337/dc20-0884DOI Listing
February 2021

Metabolite Triplet in Serum Improves the Diagnostic Accuracy of Prediabetes and Diabetes Screening.

J Proteome Res 2021 01 21;20(1):1005-1014. Epub 2020 Dec 21.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.

Large-scale population screenings are not feasible by applying laborious oral glucose tolerance tests, but using fasting blood glucose (FPG) and glycated hemoglobin (HbA), a considerable number of diagnoses are missed. A novel marker is urgently needed to improve the diagnostic accuracy of broad-scale diabetes screening in easy-to-collect blood samples. In this study, by applying a novel knowledge-based, multistage discovery and validation strategy, we scaled down from 108 diabetes-associated metabolites to a diagnostic metabolite triplet (Met-T), namely hexose, 2-hydroxybutyric/2-hydroxyisobutyric acid, and phenylalanine. Met-T showed in two independent cohorts, each comprising healthy controls, prediabetic, and diabetic individuals, distinctly higher diagnostic sensitivities for diabetes screening than FPG alone (>79.6 vs <68%). Missed diagnoses decreased from >32% using fasting plasma glucose down to <20.4%. Combining Met-T and fasting plasma glucose further improved the diagnostic accuracy. Additionally, a positive association of Met-T with future diabetes risk was found (odds ratio: 1.41; = 1.03 × 10). The results reveal that missed prediabetes and diabetes diagnoses can be markedly reduced by applying Met-T alone or in combination with FPG and it opens perspectives for higher diagnostic accuracy in broad-scale diabetes-screening approaches using easy to collect sample materials.
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http://dx.doi.org/10.1021/acs.jproteome.0c00786DOI Listing
January 2021

Recent development of nanoparticle-assisted metabolites analysis with mass spectrometry.

J Chromatogr A 2021 Jan 5;1636:461785. Epub 2020 Dec 5.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. Electronic address:

Metabolomics systematically studies the changes of metabolites in biological systems in the temporal or spatial dimensions. It is a challenging task for comprehensive analysis of metabolomics because of diverse physicochemical properties and wide concentration distribution of metabolites. Used as enrichment sorbents, chemoselective probes, chromatographic stationary phases, MS ionization matrix, nanomaterials play excellent roles in improving the selectivity, separation performance, detection sensitivity and identification efficiency of metabolites when mass spectrometry is employed as the detection technique. This review summarized the recent development of nanoparticle-assisted metabolites analysis in terms of assisting the pretreatment of biological samples, improving the separation performance and enhancing the MALDI-MS detection.
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http://dx.doi.org/10.1016/j.chroma.2020.461785DOI Listing
January 2021
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