Serum Metabonomics Reveals Risk Factors in Different Periods of Cerebral Infarction in Humans

Studies of key metabolite variations and their biological mechanisms in cerebral infarction (CI) have increased our understanding of the pathophysiology of the disease. However, how metabolite variations in different periods of CI influence these biological processes and whether key metabolites from different periods may better predict disease progression are still unknown. We performed a systematic investigation using the metabonomics method. Various metabolites in different pathways were investigated by serum metabolic profiling of 143 patients diagnosed with CI and 59 healthy controls. Phe-Phe, carnitine C18:1, palmitic acid, cis-8,11,14-eicosatrienoic acid, palmitoleic acid, 1-linoleoyl-rac-glycerol, MAG 18:1, MAG 20:3, phosphoric acid, 5α-dihydrotestosterone, Ca, K, and GGT were the major components in the early period of CI. GCDCA, glycocholate, PC 36:5, LPC 18:2, and PA showed obvious changes in the intermediate time. In contrast, trans-vaccenic acid, linolenic acid, linoleic acid, all-cis-4,7,10,13,16-docosapentaenoic acid, arachidonic acid, DHA, FFA 18:1, FFA 18:2, FFA 18:3, FFA 20:4, FFA 22:6, PC 34:1, PC 36:3, PC 38:4, ALP, and Crea displayed changes in the later time. More importantly, we found that phenylalanine metabolism, medium-chain acylcarnitines, long-chain acylcarnitines, choline, DHEA, LPC 18:0, LPC 18:1, FFA 18:0, FFA 22:4, TG, ALB, IDBIL, and DBIL played vital roles in the development of different periods of CI. Increased phenylacetyl-L-glutamine was detected and may be a biomarker for CI. It was of great significance that we identified key metabolic pathways and risk metabolites in different periods of CI different from those previously reported. Specific data are detailed in the Conclusion section. In addition, we also explored metabolite differences of CI patients complicated with high blood glucose compared with healthy controls. Further work in this area may inform personalized treatment approaches in clinical practice for CI by experimentally elucidating the pathophysiological mechanisms.

Integrated metabolomics and network toxicology to reveal molecular mechanism of celastrol induced cardiotoxicity

Celastrol (CS), an active triterpene derived from traditional Chinese medicine Tripterygium wilfordii Hook. f, has been used to treat chronic inflammation, arthritis and other diseases. However, it has been reported that CS can trigger cardiotoxicity and the molecular mechanism of heart injury induced by CS is not clear. Considering the wide application of Tripterygium wilfordii Hook. f in clinics, it is necessary to develop an accurate and reliable method to assess the safety of CS, and to elucidate as much as possible the mechanism of cardiotoxicity induced by CS. In this study, Ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC-Q-TOF/MS)-based metabolomics revealed clues to the mechanism of CS-induced heart injury. Palmitic acid significantly increased in plasma from CS-treated rats, and this increase resulted in oxidative stress response in vivo. Excessive ROS further activate TNF signaling pathway and caspase family, which were obtained from the KEGG enrichment analysis of network toxicology strategy. Protein expression level of caspase-3, caspase-8, bax were significantly increased by western blot. Q-PCR also showed the similar results as western blot. It means that apoptosis plays a key role in the process of celastrol induced cardiotoxicity. Blocking this signal axis may be a potential way to protect myocardial tissue.

Plasma metabolic profiling analysis of Cortex Periplocae-induced cardiotoxicity based on UPLC/Q-TOF-MS

Cortex Periplocae is a well-known form of traditional medicine with its unique cardiotonic action, anti-tumor activity and immune regulation effect. However, improper use of Cortex Periplocae often leads to cardiac toxicity, which in the most severe cases can even be life-threatening. Biochemical tests and histopathological examinations are primary methods for clinical trials. However, such approaches are time-consuming, lack specificity and have low sensitivity, which can easily lead to negative results in studies. Therefore, a more scientific and systematic evaluation of Cortex Periplocae cardiotoxicity is particularly important. In this study, we established a method that combines metabonomics with trend analysis of a gavage concentration series to find cardiac toxicity biomarkers of Cortex Periplocae. We created rat cardiotoxicity models, in which the toxicity was caused by Cortex Periplocae. We collected data from rat plasma samples based on metabonomics using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS). Multiple statistical analyses, such as principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), were used to examine metabolite profile changes in plasma samples to screen potential cardiotoxicity biomarkers and metabolic pathways. Compared with the control group, after 7 days administration, the pathological sections showed cardiac toxicity. Moreover, some metabolites in the body changed significantly. Receiver operating characteristic curve (ROC) analysis showed that there are 11 metabolites related with cardiac toxicity, which play a role in “phenylalanine, tyrosine and tryptophan biosynthesis”; “phenylalanine metabolism”; “valine, leucine and isoleucine biosynthesis”; “glycerophospholipid metabolism” as well as “pantothenate and CoA biosynthesis”. These metabolites can better explain the cardiotoxicity mechanism of Cortex Periplocae and provide a scientific and systematic method to evaluate the cardiotoxicity of Cortex Periplocae.

The experimental design flow for screening the cardiotoxicity biomarkers induced by Cortex Periplocae.

Metabolic Effect of 1-Deoxynojirimycin from Mulberry Leaves on db/db Diabetic Mice Using Liquid Chromatography-Mass Spectrometry Based Metabolomics

Metabolomics was applied to the liquid chromatography-mass spectrometry urinary metabolic profile of type 2 diabetes (T2DM) mice treated with mulberry 1-deoxynojirimycin (DNJ). The serum biochemical indicators related to T2DM like blood glucose, insulin, triglyceride, total cholesterol, nitrogen, malondialdehyde, and creatinine decreased significantly in the treated group. The histopathological changes in liver cells were marked by deformations and disruptions in central area of nuclei in DM mice, whereas DNJ treatment recovered regular liver cells with normal nuclei. Most of the metabolites of T2DM were significantly different from healthy controls in the bulk data generated. The level of 16 metabolites showed that the diabetic group was closer to the healthy group as the DNJ treatment time prolonged. Moreover, DNJ inhibited the activity of glucosidase on glucose, lipid, and amino acid metabolism. Our results showed the mechanism of DNJ treatment of T2DM and could fetch deep insights into the potent metabolite markers of the applied antidiabetic interventions.

Research on the Relationships between Endogenous Biomarkers and Exogenous Toxic Substances of Acute Toxicity in Radix Aconiti

Radix Aconiti, a classic traditional Chinese medicine (TCM), has been widely used throughout China for disease treatment due to its various pharmacological activities, such as anti-inflammatory, cardiotonic, and analgesic effects. However, improper use of Radix Aconiti often generated severe acute toxicity. Currently, research on the toxic substances of Radix Aconiti is not rare. In our previous study, acute toxic biomarkers of Radix Aconiti have been found. However, few studies were available to find the relationships between these endogenous biomarkers and exogenous toxic substances. Therefore, in this study, toxic substances of Radix Aconiti have been found using UPLC-Q-TOF-MS technology. Then, we used biochemical indicators as a bridge to find the relationships between biomarkers and toxic substances of Radix Aconiti through Pearson correlation analysis and canonical correlation analysis (CCA). Finally, the CCA results showed that LysoPC(22:5) is related to 14-acetyl-talatisamine, mesaconitine, talatisamine and deoxyaconitine in varying degrees; l-acetylcarnitine is negatively correlated with deoxyaconitine and demethyl-14-acetylkaracoline; shikimic acid has a good correlation with karacoline, demethyl-14-acetylkaracoline and deoxyaconitine; and valine is correlated with talatisamine and deoxyaconitine. Research on these relationships provides an innovative way to interpret the toxic mechanism of traditional Chinese medicine, and plays a positive role in the overall study of TCM toxicity.

A Novel Method for Evaluating the Cardiotoxicity of Traditional Chinese Medicine Compatibility by Using Support Vector Machine Model Combined with Metabonomics

Traditional biochemical and histopathological tests have been used to evaluate the safety of traditional Chinese medicine (TCM) compatibility for a long time. But these methods lack high sensitivity and specificity. In the previous study, we have found ten biomarkers related to cardiotoxicity and established a support vector machine (SVM) prediction model. Results showed a good sensitivity and specificity. Therefore, in this study, we used SVM model combined with metabonomics UPLC/Q-TOF-MS technology to build a rapid and sensitivity and specificity method to predict the cardiotoxicity of TCM compatibility. This study firstly applied SVM model to the prediction of cardiotoxicity in TCM compatibility containing Aconiti Lateralis Radix Praeparata and further identified whether the cardiotoxicity increased after Aconiti Lateralis Radix Praeparata combined with other TCM. This study provides a new idea for studying the evaluation of the cardiotoxicity caused by compatibility of TCM.