Quantitative profiling and diagnostic potential of one-carbon and central metabolism pools in MODY2 and T1DM

BACKGROUND

Maturity-onset diabetes of the young type 2 (MODY2) is a rare genetic disorder characterized as mild fasting hyperglycemia with low risk of vascular complications caused by glucokinase gene mutation. This study aims to investigate metabolites alteration associated with MODY2, exploring possible mechanism underlying characteristic clinical manifestations and low cardiovascular risks of MODY2 and providing serum metabolite biomarkers to facilitating MODY2 diagnosis.

METHODS

Fasting serum samples from MODY2, type 1 diabetes (T1DM) and healthy individuals were collected. By using targeted metabolomics via liquid chromatography-tandem mass spectrometry platform, we quantified the metabolites involved in tricarboxylic acid (TCA) cycle and one-carbon metabolism.

RESULTS

Metabolomic profiling revealed significant difference of intermediates from central metabolism cycle, methionine cycle and several amino acids between MODY2 and T1DM groups. Among these, serum citrate, α-ketoglutaric acid, serine, glycine, glutamine and homocysteine were significantly elevated in MODY2 patients compared with T1DM patients; and compared with healthy subjects, malate and methionine levels were significantly increased in the two groups of diabetic patients. The correlation analysis with clinical indexes showed that α- ketoglutarate, serine, glycine, and glutamine were negatively correlated with blood glucose indicators including fasting blood glucose, HbA1c, and GA, while citrate was positively correlated with C-peptide. And homocysteine displayed positive correlation with HDL and negative with C-reactive protein, which shed light on the mechanism of mild symptoms and low risk of cardiovascular complications in MODY2 patients. A panel of 4 metabolites differentiated MODY2 from T1DM with AUC of 0.924, and a combination of clinical indices and metabolite also gained good diagnostic value with AUC 0.948.

CONCLUSION

In this research, we characterized the metabolite profiles of TCA cycle and one-carbon metabolism in MODY2 and T1DM and identified promising diagnostic biomarkers for MODY2. This study may provide novel insights into the pathogenesis and clinical manifestations of MODY2.

Unique and generic crossed metabolism in response to four sub-lethal environmental stresses in the oriental fruit fly, Bactrocera dorsalis Hendel

Bactrocera dorsalis is a well-known invasive pest that causes considerable ecological and economic losses worldwild. Although it has a wide environmental tolerance, few studies have reported its mechanism of adaptation to multiple sub-lethal environmental stresses. In this study, 38, 41, 39 and 34 metabolites changed significantly in B. dorsalis under four sub-lethal stresses (heat, cold, desiccation and hypoxia), as found by the metabolomic method. Therein, lactic acid and pyruvic acid were induced, whereas metabolites in the tricarboxylic acid (TCA) cycle such as citric acid, α-ketoglutarate acid, malic acid and fumaric acid were reduced under at least one of the stresses. Enzyme activity and quantitative polymerase chain reaction (qPCR) analyses verified the repression of pyruvic acid proceeding into the TCA cycle. In addition, the levels of several cryoprotectants and membrane fatty acids in B. dorsalis were altered. The findings indicated that B. dorsalis has evolved shared metabolic pathways to adapt to heat, hypoxia and desiccation stresses, such as reducing energy consumption by activating the anaerobic glycolytic metabolism. Cryoprotectants and membrane fatty acids were produced to improve the efficiency of stress resistance. This study revealed the unique and generic crossed physiological mechanism of insects to adapt to various environmental stresses.

Lipidome, central carbon metabolites, and sleep rhythm in coronary heart disease with nontraditional risks: An exploratory pilot study

Aims

Altered lipid, energy metabolism and sleep disorders had been linked with coronary heart disease (CHD), however, the metabolic signatures and sleep rhythm in non-obstructive coronary atherosclerosis-CHD remain unclear. This pilot study aims to investigate the lipidome and central carbon metabolites profiles and associated sleep characteristics among CHD patients without traditional risk factors.

Methods

From January to July 2021, 15 CHD patients and 15 healthy controls were randomly selected from the cardiology unit of Zhongshan Hospital, Shanghai. A total of 464 lipids and 45 central carbon metabolites (CCM) were quantified in blood plasma. Metabolic signatures were selected through orthogonal projections to latent structures discriminant analysis (OPLS-DA) and principal component analysis (PCA) was conducted to link the profiles of identified metabolites with CHD risk, sleep patterns, cardiometabolic traits and cardiac electrophysiologic parameters.

Results

Using OPLS-DA, we identified 40 metabolites (variable influence on projection >1) that were altered in CHD patients, with 38 lipids, including 25 triacylglycerols (TAGs), 8 diacylglycerols (DAGs), being elevated and two CCM metabolites (i.e., succinic acid and glycolic acid) being reduced. Using PCA, four principal components (PCs) were identified and associated with increased risk of CHD. Specifically, one standard unit increasement in the PC that was characterized by high levels of DAG (18:1) and low succinic acid and the PC that was characterized by high levels of two sphingomyelins [SM (26:0) and SM (24:0)] was associated with 21% [odds ratio (OR) = 1.21, 95% CI: 1.02,1.43] and 14% (OR = 1.14,1.02,1.29) increased risk of CHD, respectively. Further regression analyses confirmed that the identified metabolites and the four PCs were positively associated with TG and ALT. Interestingly, glycolic acid was negatively associated with sleep quality and PSQI. Participants with night sleep mode tended to have a high level of the identified lipids, especially FFA (20:4).

Conclusion

In the present pilot study, our findings provide clues on alterations of lipid and energy metabolism in CHD patients without traditional risk factors, with multiple triacylglycerols and diacylglycerols metabolites seemingly elevated and certain nonlipids metabolites (e.g., succinic acid and glycolic acid) decreased in cases. Considering the limit sample size, further studies are warranted to confirm our results.

Circulating citric acid cycle metabolites and risk of cardiovascular disease in the PREDIMED study

BACKGROUND AND AIM

Plasma citric acid cycle (CAC) metabolites might be likely related to cardiovascular disease (CVD). However, studies assessing the longitudinal associations between circulating CAC-related metabolites and CVD risk are lacking. The aim of this study was to evaluate the association of baseline and 1-year levels of plasma CAC-related metabolites with CVD incidence (a composite of myocardial infarction, stroke or cardiovascular death), and their interaction with Mediterranean diet interventions.

METHODS AND RESULTS

Case-cohort study from the PREDIMED trial involving participants aged 55-80 years at high cardiovascular risk, allocated to MedDiets or control diet. A subcohort of 791 participants was selected at baseline, and a total of 231 cases were identified after a median follow-up of 4.8 years. Nine plasma CAC-related metabolites (pyruvate, lactate, citrate, aconitate, isocitrate, 2-hydroxyglutarate, fumarate, malate and succinate) were measured using liquid chromatography-tandem mass spectrometry. Weighted Cox multiple regression was used to calculate hazard ratios (HRs). Baseline fasting plasma levels of 3 metabolites were associated with higher CVD risk, with HRs (for each standard deviation, 1-SD) of 1.46 (95%CI:1.20-1.78) for 2-hydroxyglutarate, 1.33 (95%CI:1.12-1.58) for fumarate and 1.47 (95%CI:1.21-1.78) for malate (p of linear trend <0.001 for all). A higher risk of CVD was also found for a 1-SD increment of a combined score of these 3 metabolites (HR = 1.60; 95%CI: 1.32-1.94, p trend <0.001). This result was replicated using plasma measurements after one-year. No interactions were detected with the nutritional intervention.

CONCLUSION

Plasma 2-hydroxyglutarate, fumarate and malate levels were prospectively associated with increased cardiovascular risk.

CLINICAL TRIAL NUMBER

ISRCTN35739639.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

Tricarboxylic acid cycle related-metabolites and risk of atrial fibrillation and heart failure

BACKGROUND

Tricarboxylic acid (TCA) cycle deregulation may predispose to cardiovascular diseases, but the role of TCA cycle-related metabolites in the development of atrial fibrillation (AF) and heart failure (HF) remains unexplored. This study sought to investigate the association of TCA cycle-related metabolites with risk of AF and HF.

METHODS

We used two nested case-control studies within the PREDIMED study. During a mean follow-up for about 10 years, 512 AF and 334 HF incident cases matched by age (±5 years), sex and recruitment center to 616 controls and 433 controls, respectively, were included in this study. Baseline plasma levels of citrate, aconitate, isocitrate, succinate, malate and d/l-2-hydroxyglutarate were measured with liquid chromatography-tandem mass spectrometry. Multivariable conditional logistic regression models were fitted to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for metabolites and the risk of AF or HF. Potential confounders included smoking, family history of premature coronary heart disease, physical activity, alcohol intake, body mass index, intervention groups, dyslipidemia, hypertension, type 2 diabetes and medication use.

RESULTS

Comparing extreme quartiles of metabolites, elevated levels of succinate, malate, citrate and d/l-2-hydroxyglutarate were associated with a higher risk of AF [OR_{Q4 vs. Q1} (95% CI): 1.80 (1.21-2.67), 2.13 (1.45-3.13), 1.87 (1.25-2.81) and 1.95 (1.31-2.90), respectively]. One SD increase in aconitate was directly associated with AF risk [OR (95% CI): 1.16 (1.01-1.34)]. The corresponding ORs (95% CI) for HF comparing extreme quartiles of malate, aconitate, isocitrate and d/l-2-hydroxyglutarate were 2.15 (1.29-3.56), 2.16 (1.25-3.72), 2.63 (1.56-4.44) and 1.82 (1.10-3.04), respectively. These associations were confirmed in an internal validation, except for aconitate and AF.

CONCLUSION

These findings underscore the potential role of the TCA cycle in the pathogenesis of cardiac outcomes.

The Echocardiographic Parameters of Systolic Function Are Associated with Specific Metabolomic Fingerprints in Obstructive and Non-Obstructive Hypertrophic Cardiomyopathy

The purpose of this study was to assess whether metabolomics, associated with echocardiography, was able to highlight pathophysiological differences between obstructive (OHCM) or non-obstructive (NOHCM) hypertrophic cardiomyopathy. Thirty-one HCM patients underwent standard and advanced echocardiography; a plasma sample was collected for metabolomic analysis. Results. Patients with OHCM compared with subjects with NOHCM had higher values of 2DLVEF (66.5 ± 3.3% vs. 60.6 ± 1.8%, p < 0.01), S wave (7.6 ± 1.1 vs. 6.3 ± 0.7 cm/s, p < 0.01) and 3D global longitudinal strain (17.2 ± 4.2%, vs. 13.4 ± 1.3%, p < 0.05). A 2-group PLS-Discriminant Analysis was performed to verify whether the two HCM groups differed also based on the metabolic fingerprint. A clear clustering was shown (ANOVA p = 0.014). The most discriminating metabolites resulted as follows: in the NOHCM Group, there were higher levels of threitol, aminomalonic acid, and sucrose, while the OHCM Group presented higher levels of amino acids, in particular those branched chains, of intermediates of glycolysis (lactate) and the Krebs cycle (fumarate, succinate, citrate), of fatty acids (arachidonic acid, palmitoleic acid), of ketone bodies (2-OH-butyrate). Our data point out a different systolic function related to a specific metabolic activity in the two HCM phenotypic forms, with specific metabolites associated with better contractility in OHCM.

Identification of Ophiopogonis Radix from different producing areas by headspace-gas chromatography-ion mobility spectrometry analysis

Ophiopogonis Radix can be divided into Zhemaidong (ZMD) and Chuanmaidong (CMD). The main planting areas of ZMD are Cixi City and Sanmen county. The quality and price of Ophiopogonis Radix from different producing areas are different. In this study, the headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) method is used to rapidly identify ZMD and CMD. The method is also used to identify ZMD from Cixi and Sanmen by analyzing volatile organic compounds (VOCs). A total of 58 VOCs was obtained from ZMD samples with more abundant signals of which 41 were identified. The peak intensities of all VOCs in ZMD and CMD, Cixi and Sanmen data were averaged and then those VOCs whose peak intensities were distributed outside of mean ± 2 standard deviation (μ ± 2σ) were selected as characteristic markers. We selected 14 characteristic markers to establish the characteristic fingerprint of ZMD and CMD, among the 14 VOCs, ZMD contained more eucalyptus oil compounds than CMD, CMD contained more volatile aldehydes than ZMD. We selected 12 characteristic markers for the establishment of the characteristic fingerprint of ZMD from Cixi and Sanmen. The principal component analysis (PCA) results indicated that both ZMD and CMD or ZMD from Cixi and Sanmen could be effectively divided. The ZMD and CMD as well as ZMD from Cixi and Sanmen were evaluated by partial least squares regression-discriminants analysis (PLS-DA) resulting to be excellent chemical descriptors for sample discrimination. One hundred percent classification rates for both PLS-DA calibration and prediction models were obtained. These results provided a reference for the traceability of species and origin and market standard of Ophiopogonis Radix. PRACTICAL APPLICATIONS: Ophiopogonis Radix can be divided into Zhejiang Ophiopogonis Radix (ZMD) and Sichuan Ophiopogonis Radix (CMD). As far as ZMD is concerned, its producing areas mainly include the traditional planting areas (Cixi City) and new growth areas (Sanmen county). In this paper, the HS-GC-IMS method was adopted to analyze VOCs in Ophiopogonis Radix from different producing areas and then we screen out the respective characteristic VOCs of ZMD and CMD as well as ZMD from Cixi and Sanmen. These characteristic VOCs can effectively identify ZMD and CMD as well as ZMD from Cixi City and Sanmen country to provide a scientific basis for the origin identification of Ophiopogonis Radix.

Metabolomic correlates of coronary atherosclerosis, cardiovascular risk, both or neither. Results of the 2 × 2 phenotypic CAPIRE study

BACKGROUND

Traditional cardiovascular risk factors (RFs) and coronary artery disease (CAD) do not always run parallel. We investigated functional-metabolic correlations of CAD, RFs, or neither in the CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation) 2 × 2 phenotypic observational study.

METHODS

Two hundred and fortyone subjects were included based on RF burden, presence/absence of CAD (assessed by computed tomography angiography), age and sex. Participants displayed one of four phenotypes: CAD with ≥3 RFs, no-CAD with ≥3 RFs, CAD with ≤1 RF and no-CAD with ≤1 RF. Metabolites were identified by gas chromatography-mass spectrometry and pathways by metabolite set enrichment analysis.

RESULTS

Characteristic patterns and specific pathways emerged for each phenotypic group: amino sugars for CAD/high-RF; urea cycle for no-CAD/high-RF; glutathione for CAD/low-RF; glycine and serine for no-CAD/low-RF. Presence of CAD correlated with ammonia recycling; absence of CAD with the transfer of acetyl groups into mitochondria; high-risk profile with alanine metabolism (all p < 0.05). The comparative case-control analyses showed a statistically significant difference for the two pathways of phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism in the CAD/Low-RF vs NoCAD/Low-RF comparison.

CONCLUSIONS

The present 2 × 2 observational study identified specific metabolic pathways for each of the four phenotypes, providing novel functional insights, particularly on CAD with low RF profiles and on the absence of CAD despite high-risk factor profiles.

Metabolomics and its application in the treatment of coronary heart disease with traditional Chinese medicine

Traditional Chinese Medicine (TCM) is the treasure of Chinese Nation and gained the gradual acceptance of the international community. However, the methods and theories of TCM understanding of diseases are lack of appropriate modern scientific characterization systems. Moreover, traditional risk factors cannot promote to detection and prevent those patients with coronary artery disease (CAD) who have not developed acute myocardial infarction (MI) in time. To sum up, there is still no objective systematic evaluation system for the therapeutic mechanism of TCM in the prevention and cure of cardiovascular disease. Thus, new ideas and technologies are needed. The development of omics technology, especially metabolomics, can be used to predict the level of metabolites in vivo and diagnose the physiological state of the body in time to guide the corresponding intervention. In particular, metabolomics is also a very powerful tool to promote the modernization of TCM and the development of TCM in personalized medicine. This article summarized the application of metabolomics in the early diagnosis, the discovery of biomarkers and the treatment of TCM in CAD.

Omics strategies decipher therapeutic discoveries of traditional Chinese medicine against different diseases at multiple layers molecular-level

Traditional Chinese medicine (TCM) has been broadly used for the personalized treatment of many diseases in China for thousands of years. In the past century, TCM was also introduced to other Asian countries and even the Western world. Increasing evidence has shown that TCM has the capacity to treat numerous complex diseases in the clinic, such as cardiovascular diseases (CVDs), infectious diseases, metabolic diseases, and neurodegenerative diseases. However, the earlier lack of analytical strategies to annotate the chemical complexity has severely impeded the modern study and translational application of TCM. This critical review aims to explore and exploit applications of systems biology-driven omics methods in TCM against a diversity of diseases, toward the specific use of TCM to treat patients with different diseases. Such effort shall enhance the applicability of systems biology-driven omics strategies in deciphering the mechanisms by which TCM treats different diseases and may lead to the discovery of new therapeutic directions. In addition, we proposed the possible strategies to innovate the applicable pattern of omics technologies in TCM niches, such as precision-modification metabolomics and chinmedomics methods, allowing to unveil the complexity of TCM, which must enable TCM to serve better for the population-health. Taken together, this review eventually shall highlight the core value of omics technologies in innovating TCM to combat the diseases in a new horizon.

Investigation of the metabolic difference between ST-elevated myocardial infarction and non-ST-elevated myocardial infarction via LC/Q-TOF/MS/MS

Acute coronary syndrome (ACS) is a clinical condition caused by a disturbance in myocardial blood flow. ACS can be basically divided into two forms: ST elevation myocardial infarction (STEMI) due to complete occlusion of the coronary artery and non-ST elevation myocardial infarction (NSTEMI) due to partial occlusion of the coronary artery. In this study, we aimed to monitor the metabolite profile of STEMI and NSTEMI patients and compare the results via untargeted metabolomics approach. Serum samples were collected from STEMI and NSTEMI patients, and each group consists of 20 participants. Extraction was achieved by acetonitrile, and chromatographic separation was performed by LC/Q-TOF/MS/MS accompanied with dual AJS ESI positive ion mode. METLIN, MATLAB 2017a-PLS Toolbox7.2, and Human Metabolome Database were utilized for bioinformatics evaluation of obtained findings. In our results, 203 m/z ratio was detected and 163 m/z ratio passed the significance criteria (fold analysis > 1.5 and p < 0.05). Twenty-five metabolites including BCAAs, LysoPC species, lactic acid, succinate, malonic acid, maleic acid, butyric acid, carnitine, and betaine were identified. In conclusion, new biomarker candidates were identified to differentiate the diagnosis of STEMI and NSTEMI. Identified metabolites are indicative of alterations in oxidative stress, hypoxia, TCA cycle, and amino acid metabolism.

Profiling thiol metabolites in myocardial infarction human serum by stable isotope labeling assisted liquid chromatography-mass spectrometry

Myocardial Infarction (MI) is one of the most common causes of deaths worldwide. Thiols have been reported to play a key role in physiological and pathological processes of MI. Comprehensive analysis of thiols would be conducive to fully elucidate the relation between thiols and MI. In the current study, we analyze the metabolomic differences of thiols in serum between MI patients (n = 30) and healthy controls (HCs, n = 30) by stable isotope labeling-dispersive solid phase extraction-liquid chromatography-full scan-Orbitrap-mass spectrometry analysis (IL-DSPE-LC-full scan-Orbitrap MS) method. We detected 300 potential thiols in serum of MI patients and HCs, among which, 67 thiols were positively or putatively identified. Furthermore, we found that the levels of 71 thiols in serum exhibited significant difference between MI patients and HCs. In the transsulfuration pathway, we observed that Cys and Hcys were upregulated, while GSH were downregulated. Our results provide a comprehensive understanding of thiols metabolome in human serum between MI patients and HCs.

Material basis research for Huangqi Jianzhong Tang against chronic atrophic gastritis rats through integration of urinary metabonomics and SystemsDock

ETHNOPHARMACOLOGICAL RELEVANCE

Huangqi Jianzhong Tang (HQJZ), a celebrated traditional Chinese medicine (TCM), is commonly used for treatment of chronic atrophic gastritis (CAG) in China.

AIM OF THE STUDY

We aimed to screen out the material basis of HQJZ against CAG.

MATERIALS AND METHODS

CAG rat model was constructed by alternant administrations of ammonia solution and sodium deoxycholate, and the hunger disorder method. Body weight, biochemical indexes and histopathological exam were used to evaluate the efficacy of HQJZ. ¹H NMR-based metabonomics was employed to analyze the urine metabolic features of HQJZ deviated from CAG rats. SystemsDock analysis was utilized to explore the active compounds involved into the efficacy of HQJZ against CAG based on the targeted metabolic biomarkers.

RESULTS

The metabonomic results indicated that HQJZ could significantly improve 16 urinary perturbed metabolites in CAG rats, which were involved into the metabolism of energy and amino acids. And then 28 related proteins and genes were selected out to be the potential targets of HQJZ against CAG based on the six key metabolites closely correlating with biochemical indexes (α-ketoglutarate, valine, sarcosine, glycine, malonate and fumarate). 71 previous identified compounds were docked through systemsDock-aided molecular docking experiments. And the constructed herb-component-protein-metabolite interaction network (HCPMN) revealed the associations between the herbal formulae and CAG. At last, 51 compounds of them were screened as promising active constitutes for the inhibition of CAG, which could act on various targeted proteins.

CONCLUSIONS

he results showed that the approach integrating of metabonomics and systemsDock is a powerful tool to obtain the material basis and regulatory mechanism of TCM formula.

Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis

Coronary atherosclerosis (CAS) is the pathogenesis of coronary heart disease, which is a prevalent and chronic life-threatening disease. Initially, this disease is not always detected until a patient presents with seriously vascular occlusion. Therefore, new biomarkers for appropriate and timely diagnosis of early CAS is needed for screening to initiate therapy on time. In this study, we used an untargeted metabolomics approach to identify potential biomarkers that could enable highly sensitive and specific CAS detection. Score plots from partial least-squares discriminant analysis clearly separated early-stage CAS patients from controls. Meanwhile, the levels of 24 metabolites increased greatly and those of 18 metabolites decreased markedly in early CAS patients compared with the controls, which suggested significant metabolic dysfunction in phospholipid, sphingolipid, and fatty acid metabolism in the patients. Furthermore, binary logistic regression showed that nine metabolites could be used as a combinatorial biomarker to distinguish early-stage CAS patients from controls. The panel of nine metabolites was then tested with an independent cohort of samples, which also yielded satisfactory diagnostic accuracy (AUC = 0.890). In conclusion, our findings provide insight into the pathological mechanism of early-stage CAS and also supply a combinatorial biomarker to aid clinical diagnosis of early-stage CAS.

Global and untargeted metabolomics evidence of the protective effect of different extracts of Dipsacus asper Wall. ex C.B. Clarke on estrogen deficiency after ovariectomia in rats

ETHNOPHARMACOLOGICAL RELEVANCE

Dipsacus asper Wall. ex C.B. Clarke (DA) is an effectively traditional Chinese medicine for treating osteoporosis and bone fracture. Until now, studies on pharmacological mechanism of DA mostly centered on cell and gene level, little is known about its metabolic signatures. The aim of this study is to investigate the anti-osteoporosis effects of crude and wine-processed DA by global and untargeted metabolic profiling of rats serum, liver and kidney derived from sham, model and treated groups.

METHOD

A total of 25 female Wistar rats were divided into five groups: sham group, model group, E2, crude and wine-processed DA treated group. The treatment rats were orally administered 17β-estradiol, crude and wine-processed DA extract at a therapeutic dose once daily throughout the experimental period, while sham group and model group were orally gavaged approximately volume of saline solution. After 16 weeks, all serum, liver and kidney samples of five groups were collected and their metabolomic alterations were monitored by gas chromatography-mass spectrometry (GC-MS). The resulting dataset was analyzed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The identification of all potential biomarkers was performed using reference standard or NIST library. Moreover, clinical chemistry and biomechanical analysis were also performed to ensure the success of the osteoporosis model and to validate the anti-osteoporosis effect of crude and wine-processed DA.

RESULTS

Clear separation trend among sham, model and treatment group was observed in PCA score plot. The anti-osteoporosis effect of DA and wine-processed DA can be indicated in PLS-DA score plots. A total of 80 and 74 metabolite biomarkers were identified for DA and wine-processed DA treated groups, respectively. Pathway analysis revealed that phenylalanine, tyrosine and tryptophan biosynthesis, valine, leucine and isoleucine biosynthesis, methane metabolism, glycine, serine and threonine metabolism, galactose metabolism were the major intervened pathways. Compared with model group, levels of all biomarkers were gradually restored to normal after administration of DA and wine-processed DA.

CONCLUSION

The anti-osteoporosis effect of DA and wine-processed DA has been reliably confirmed by the metabolomics approach. The osteoporosis might be prevented by DA and wine-processed DA via intervening amino acid metabolism, carbohydrate metabolism and energy metabolism in vivo in rats.

A Comparative Metabolomics Approach Reveals Early Biomarkers for Metabolic Response to Acute Myocardial Infarction

Discovery of novel biomarkers is critical for early diagnosis of acute coronary syndrome (ACS). Serum metabolite profiling of ST-elevation myocardial infarction (STEMI), unstable angina (UA) and healthy controls was performed using gas chromatography mass spectrometry (GC/MS), solid-phase microextraction coupled to gas chromatography mass spectrometry (SPME-GC/MS) and nuclear magnetic resonance (¹H-NMR). Multivariate data analysis revealed a metabolic signature that could robustly discriminate STEMI patients from both healthy controls and UA patients. This panel of biomarkers consisted of 19 metabolites identified in the serum of STEMI patients. One of the most intriguing biomarkers among these metabolites is hydrogen sulfide (H₂S), an endogenous gasotransmitter with profound effect on the heart. Serum H₂S absolute levels were further investigated using a quantitative double-antibody sandwich enzyme-linked immunosorbent assay (ELISA). This highly sensitive immunoassay confirmed the elevation of serum H₂S in STEMI patients. H₂S level discriminated between UA and STEMI groups, providing an initial insight into serum-free H₂S bioavailability during ACS. In conclusion, the current study provides a detailed map illustrating the most predominant altered metabolic pathways and the biochemical linkages among the biomarker metabolites identified in STEMI patients. Metabolomics analysis may yield novel predictive biomarkers that will potentially allow for an earlier medical intervention.

Exploring the Process of Energy Generation in Pathophysiology by Targeted Metabolomics: Performance of a Simple and Quantitative Method

Abnormalities in mitochondrial metabolism and regulation of energy balance contribute to human diseases. The consequences of high fat and other nutrient intake, and the resulting acquired mitochondrial dysfunction, are essential to fully understand common disorders, including obesity, cancer, and atherosclerosis. To simultaneously and noninvasively measure and quantify indirect markers of mitochondrial function, we have developed a method based on gas chromatography coupled to quadrupole-time of flight mass spectrometry and an electron ionization interface, and validated the system using plasma from patients with peripheral artery disease, human cancer cells, and mouse tissues. This approach was used to increase sensibility in the measurement of a wide dynamic range and chemical diversity of multiple intermediate metabolites used in energy metabolism. We demonstrate that our targeted metabolomics method allows for quick and accurate identification and quantification of molecules, including the measurement of small yet significant biological changes in experimental samples. The apparently low process variability required for its performance in plasma, cell lysates, and tissues allowed a rapid identification of correlations between interconnected pathways. Our results suggest that delineating the process of energy generation by targeted metabolomics can be a valid surrogate for predicting mitochondrial dysfunction in biological samples. Importantly, when used in plasma, targeted metabolomics should be viewed as a robust and noninvasive source of biomarkers in specific pathophysiological scenarios.

Metabolomics and its application to the evaluation of the efficacy and toxicity of traditional Chinese herb medicines

Traditional Chinese herb medicines (TCHMs) have been used in the treatment of a variety of diseases for thousands of years in Asian countries. The active components of TCHMs usually exert combined synergistic therapeutic effects on multiple targets, but with less potential therapeutic effect based on routine indices than Western drugs. These complex effects make the assessment of the efficacy of TCHMs and the clarification of their underlying mechanisms very challenging, and therefore hinder their wider application and acceptance. Metabolomics is a crucial part of systems biology. It allows the quantitative measurement of large numbers of the low-molecular endogenous metabolites involved in metabolic pathways, and thus reflects the fundamental metabolism status of the body. Recently, dozens of metabolomic studies have been devoted to prove the efficacy/safety, explore the underlying mechanisms, and identify the potential biomarkers to access the action targets of TCHMs, with fruitful results. This article presents an overview of these studies, focusing on the progress made in exploring the pharmacology and toxicology of various herbal medicines.

LC/MS-based polar metabolite profiling reveals gender differences in serum from patients with myocardial infarction

Myocardial infarction (MI), a leading cause of death worldwide, results from prolonged myocardial ischemia with necrosis of myocytes due to a blood supply obstruction to an area of the heart. Many studies have reported gender-related differences in the clinical features of MI, but the reasons for these differences remain unclear. In this study, we applied ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS) and various statistical methods-such as multivariate, pathway, and correlation analyses-to identify gender-specific metabolic patterns in polar metabolites in serum from healthy individuals and patients with MI. Patients with diagnosed MI (n=68), and age- and body mass index-matched healthy individuals (n=68), were included in this study. The partial least-squares discriminant analysis (PLS-DA) model was generated from metabolic profiling data, and the score plots showed a significant gender-related difference in patients with MI. Many pathways were associated with amino acids and purines; amino acids, acylcarnitines, and purines differed significantly between male and female patients with MI. This approach could be utilized to observe gender-specific metabolic pattern differences between healthy controls and patients with MI.

Metabolomic signature of arterial stiffness in male patients with peripheral arterial disease

Arterial stiffness is an independent determinant of cardiovascular risk and a marker of subclinical organ damage. Metabolomics may facilitate identification of novel low-molecular cardiovascular risk factors. The aim of the present study was to compare metabolic signatures and functional-biochemical characteristics of patients with peripheral arterial disease (PAD) and clinically healthy subjects. We studied 42 men with symptomatic PAD (aged 66±7 years) and 46 healthy men (aged 66±8 years). Aortic pulse wave velocity (aPWV) was assessed by applanation tonometry using the Sphygmocor device. Metabolic profiling was performed with high-performance liquid chromatography and mass spectrometry. Serum oxidized low-density lipoprotein (oxLDL) level was measured by enzyme-linked immunosorbent assay. The aPWV as well as serum levels of lactate, free carnitine and 11 amino acids including tyrosine were higher among the patients with PAD. In contrast, serum levels of pyruvate, citrate, α-ketoglutarate, aconitate and cysteine were higher in the control group. In multiple regression models, aPWV was independently determined by log-tyrosine and log-oxLDL in the patients (R(2)=0.61; P<0.001) and by age, log-pyruvate and log-oxLDL in the controls (R(2)=0.52; P<0.001). Our study describes for the first time significant differences in metabolomic signature of patients with advanced atherosclerosis compared with clinically healthy controls. The aPWV is independently associated with serum levels of tyrosine and oxLDL in the patients with PAD and is related to pyruvate and oxLDL levels in the control group. The measurement of low-molecular metabolites, which are related to changes in vascular phenotypes, may lead to identification of novel vascular risk markers.

Ginsenoside Rg1 protects against transient focal cerebral ischemic injury and suppresses its systemic metabolic changes in cerabral injury rats

Ginsenoside Rg1 (GR), a major bioactive compound of traditional Chinese medicine, such as Panax ginseng or Radix Notoginseng, has been shown to exert neuroprotective effects against ischemic stroke. However, pharmacokinetic studies have suggested that GR could not be efficiently transported through the blood-brain barrier. The mechanism by which GR attenuates cerebral ischemic injury in vivo remains largely unknown. Therefore, this study explored potential neuro-protective effects of GR through its systemic metabolic regulating mechanism by using mass spectrometry-based metabolomic profiling. Rats with middle cerebral artery occlusion (MCAO) were treated with GR intravenously. Their metabolic profiles in serum were measured by gas chromatography coupled with mass spectrometry on 1 and 3 days after MCAO. GR exhibited a potent neuro-protective effect by significantly decreasing the neurological scores and infarct volume in the MCAO rats. Moreover, 18 differential metabolites were tentatively identified, all of which appeared to correlate well with these disease indices. Our findings suggested that GR carries a therapeutic potential in stroke possibly through a feed-back mechanism by regulating systematic metabolic mediation.

UHPLC-LTQ-Orbitrap MS combined with spike-in method for plasma metabonomics analysis of acute myocardial ischemia rats and pretreatment effect of Danqi Tongmai tablet

Undoubtedly, metabonomics can reveal the comprehensive efficacies of traditional Chinese medicine (TCM) formulae and its complex mechanism at the molecular biological level. In this study, an attempt was made to address the pretreatment effect of a TCM formula. In this case, as a critical point, we should first know how to really reflect the various endogenous metabolites in a disease status before a TCM formula is employed in a therapeutic procedure. Here, we explored an approach that combined high resolution LTQ-Orbitrap mass spectrometry with a spike-in method to characterize endogenous metabolites in acute myocardial ischemia (AMI) rats. As a result, 19 potential biomarkers in rat plasma were identified and 10 related disturbed pathways were perturbed in the early stages of AMI development. Subsequently, the metabonomics method was applied to investigate the pretreatment effect of the TCM formula named the Danqi Tongmai tablet (DQTM). The results revealed that the DQTM pretreatment could reduce the AMI injury and partially regulate the perturbed TCA cycle and amino and nucleotide metabolism, which were presumable related to energy metabolism and myocardial cells apoptosis/necrosis. In conclusion, UHPLC-LTQ-Orbitrap MS combined with a spike-in method were successfully applied to the metabonomics analysis of DQTM, which demonstrated that not only a comprehensive metabolic profile in the early stages of AMI development was achieved, but also that the underlying holistic efficacies were assessed and it was helpful to understand the possible mechanism of pretreatment with DQTM.

Repetitive transcranial magnetic stimulation applications normalized prefrontal dysfunctions and cognitive-related metabolic profiling in aged mice

Chronic high-frequency repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain stimulation technique that has recently received increasing interests as a therapeutic procedure for neurodegenerative diseases. To identify the metabolism mechanism underlying the improving effects of rTMS, we observed that high frequency (25Hz) rTMS for 14 days could reverse the decline of the performance of the passive avoidance task in aged mice. We further investigated the metabolite profiles in the prefrontal cortex (PFC) in those mice and found that rTMS could also reverse the metabolic abnormalities of gamma-aminobutyric acid, N-acetyl aspartic, and cholesterol levels to the degree similar to the young mice. These data suggested that the rTMS could ameliorate the age-related cognitive impairment and improving the metabolic profiles in PFC, and potentially can be used to improve cognitive decline in the elderly.

Method based on GC-MS to study the influence of tricarboxylic acid cycle metabolites on cardiovascular risk factors

Metabolites involved in the tricarboxylic acid (TCA) cycle have previously been proposed as cardiovascular biomarkers. This cycle plays a key role in cell metabolism and the levels of the involved metabolites can also be affected by other physiological factors. The influence of three cardiovascular risk factors such as obesity, hypercholesterolemia, and smoking habit on serum levels of TCA-cycle metabolites has been studied in patients diagnosed with significant coronary lesion. For this purpose, a method based on GC-MS for determination of the target metabolites (viz. citric/isocitric, pyruvic, aconitic, oxaloacetic, malic, fumaric and succinic acids) in serum has been developed. The high accuracy and throughput analysis featuring the method have allowed application to a cohort of 223 patients, 172 of them with significant coronary lesion. Multifactor analysis of variance has revealed interactions between the occurrence or not of a coronary lesion and the risk factors considered in this study. These interactions were crucial to explain the levels of target TCA metabolites. Statistical evaluation by ROC curves allowed discrimination of the capability of significant metabolites with the occurrence of coronary lesions.

Determination of essential amino acids in human serum by a targeting method based on automated SPE-LC-MS/MS: discrimination between artherosclerotic patients

An automated method based on a hyphenated SPE-LC-MS/MS configuration has been optimized for the determination of essential amino acids (threonine, valine, methionine, leucine, isoleucine, lysine, tryptophan, and phenylalanine) in human serum, with the aim of discriminating between different states of coronary artery disease. Validation in terms of sensitivity (detection limits below 28.0 ng on column) and precision (repeatability expressed as relative standard deviation below 6.0%) supports the suitability of the method for application to a cohort of 122 atherosclerosis patients confirmed by a catheterization test. The cohort was composed by 80 individuals diagnosed with stable angina and 42 patients who suffered from acute myocardial infarction (AMI). Both groups of individuals are differentiated by the occurrence of ischemia in AMI patients due to the formation of thrombi. The chemometric treatment of the data obtained by multivariate analysis of variance (MANOVA) allowed comparison between both groups of diagnosed patients. Therefore, amino acids whose serum levels were affected by ischemia have been identified. The contribution of risk factors such as obesity and hypercholesterolemia as well as the individuals' gender to the concentration of essential amino acids has also been studied.

PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools

Background

Gas chromatography–mass spectrometry (GC-MS) is a technique frequently used in targeted and non-targeted measurements of metabolites. Most existing software tools for processing of raw instrument GC-MS data tightly integrate data processing methods with graphical user interface facilitating interactive data processing. While interactive processing remains critically important in GC-MS applications, high-throughput studies increasingly dictate the need for command line tools, suitable for scripting of high-throughput, customized processing pipelines.

Results

PyMS comprises a library of functions for processing of instrument GC-MS data developed in Python. PyMS currently provides a complete set of GC-MS processing functions, including reading of standard data formats (ANDI- MS/NetCDF and JCAMP-DX), noise smoothing, baseline correction, peak detection, peak deconvolution, peak integration, and peak alignment by dynamic programming. A novel common ion single quantitation algorithm allows automated, accurate quantitation of GC-MS electron impact (EI) fragmentation spectra when a large number of experiments are being analyzed. PyMS implements parallel processing for by-row and by-column data processing tasks based on Message Passing Interface (MPI), allowing processing to scale on multiple CPUs in distributed computing environments. A set of specifically designed experiments was performed in-house and used to comparatively evaluate the performance of PyMS and three widely used software packages for GC-MS data processing (AMDIS, AnalyzerPro, and XCMS).

Conclusions

PyMS is a novel software package for the processing of raw GC-MS data, particularly suitable for scripting of customized processing pipelines and for data processing in batch mode. PyMS provides limited graphical capabilities and can be used both for routine data processing and interactive/exploratory data analysis. In real-life GC-MS data processing scenarios PyMS performs as well or better than leading software packages. We demonstrate data processing scenarios simple to implement in PyMS, yet difficult to achieve with many conventional GC-MS data processing software. Automated sample processing and quantitation with PyMS can provide substantial time savings compared to more traditional interactive software systems that tightly integrate data processing with the graphical user interface.

Biomarkers in the early period of acute myocardial infarction in rat serum and protective effects of Shexiang Baoxin Pill using a metabolomic method

ETHNOPHARMACOLOGICAL RELEVANCE

To identify the biomarkers in early period of acute myocardial infarction (AMI) in rat serum and reveal the effective mechanism of a Traditional Chinese Medicine (TCM) named Shexiang Baoxin Pill (SBP).

MATERIAL AND METHOD

A metabolomic approach using reversed-phase liquid chromatography/quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) was developed.

RESULTS

Fourteen biomarkers in the early period of acute myocardial infarction (AMI) in rat serum were identified. These biomarkers include 5-methylcytosine, cystathionine ketimine, 2-oxoadipic acid, thymidine, epinephrine, homocystine, uric acid, 12(S)-hydroperoxyeicosatetraenoic acid (12s-HPETE), 11-dehydrocorticosterone, 12(S)-hydroxyeicosatetraenoic acid (12s-HETE), deoxycorticosterone, corticosterone, aldosterone and cortisol. Through pathway analysis of these biomarkers, inflammation, hypertrophy and oxidative injury were considered the most relevant pathological changes in early period of AMI.

CONCLUSION

Identification of AMI biomarkers not only supplied a systematic view of the progression of AMI in the early period but also provided the theoretical basis for the prevention or treatment of AMI. The results demonstrated that SBP pretreatment could offer protective effects for AMI through regulating the pathway of steroid hormone biosynthesis.

Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase

In this study, a tandem LC-MS (Waters Xevo TQ) MRM-based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice, including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a "fingerprint" characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum, and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples.