Integrated biomarker profiling for predicting the response of type 2 diabetes to metformin.

AIM: To explore biomarkers that can predict the response of type 2 diabetes (T2D) patients to metformin at an early stage to provide better treatment for T2D. METHODS: T2D patients with (responders) or without response (non-responders) to metformin were recruited, and their serum samples were used for metabolomic analysis to identify candidate biomarkers. Moreover, the efficacy of metformin was verified by insulin-resistant mice, and the candidate biomarkers were verified to determine the biomarkers. Five different machine learning methods were used to construct the integrated biomarker profiling (IBP) with the biomarkers to predict the response of T2D patients to metformin. RESULTS: A total of 73 responders and 63 non-responders were recruited, and 88 differential metabolites were identified in the serum samples. After being verified in mice, 19 of the 88 were considered as candidate biomarkers. Next, after metformin regulation, nine candidate biomarkers were confirmed as the biomarkers. After comparing five machine learning models, the nine biomarkers were constructed into the IBP for predicting the response of T2D patients to metformin based on the Naïve Bayes classifier, which was verified with an accuracy of 89.70%. CONCLUSIONS: The IBP composed of nine biomarkers can be used to predict the response of T2D patients to metformin, enabling clinicians to start a combined medication strategy as soon as possible if T2D patients do not respond to metformin.

[Advances in in vitro assessment models and screening methods for blood glucose-lowering medications].

Diabetes, a common metabolic condition, is recognized by the worldwide public health community as a serious chronic illness. International new drug discovery has long been dominated by the study and creation of blood glucose-lowering medications. Important phases in the development process of these medications include the in vitro assessment model and screening methods, which can dramatically lower the costs and risks of subsequent clinical trials and increase the effectiveness and efficiency of drug development. This article reviews the classic and latest cutting-edge in vitro assessment models, principles, methods, and key technologies for blood glucose-lowering medications both domestically and internationally. By objectively evaluating their advantages, disadvantages, characteristics, applicability, experimental design, and data analysis, this article aims to improve the standardization and consensus of in vitro assessment models and screening methods and serve the research and development of blood glucose-lowering medications.

[Mechanism of Huangqi Simiao Decoction in treatment of type 2 diabetes mellitus based on network pharmacology and metabonomics].

This article analyzed the mechanism of Huangqi Simiao Decoction(HSD) for the treatment of type 2 diabetes mellitus(T2DM). The component targets of HSD and the related disease targets of T2DM were screened through network pharmacology. The protein-protein interaction(PPI) network of intersecting targets and the drug-component-intersecting target network were constructed to screen the potential active ingredients and targets. Molecular docking was performed using AutoDock Vina software to verify the interaction between potential components and core targets. The serum was tested by ultra performance liquid chromatography-tandem mass spectrometry, and multivariate statistical analyses, such as principal component analysis(PCA) and partial least squares discriminant analysis(PLS-DA), were used to search for the differential metabolites and related metabolic pathways of each group by combining with the MetaboAnalyst database. The same metabolic pathways were analyzed by combining the screened differential metabolites with the intersecting targets screened by network pharmacology. Network pharmacology showed that the nine core components of HSD for the treatment of T2DM were quercetin, kaempferol, stigmasterol, baicalein, ß-sitosterol, flavodoxin, canthaxanthin, canthaxanthin, berberine, and berberine, and the five core targets included AKT1, TP53, TNF, IL6, and VEGFA. Molecular docking showed that the core components bound well to the target genes. Metabolomics showed that a total of 112 common differential metabolites were identified, of which 88 metabolites exhibited increased concentration and 24 metabolites decreased concentration after treatment with HSD. Enrichment analysis showed that HSD regulated the body metabolism of patients with T2DM, mainly related to seven metabolic pathways, such as amino acid metabolism and tricarboxylic acid cycle. The joint analysis of metabolomics and network pharmacology showed that both involved histidine metabolism, arginine and proline metabolic pathways. This study suggests that HSD has a good efficacy for T2DM. Based on the combined analysis of metabolomics and network pharmacology, it was found that the mechanism may be that the pharmacodynamic bases of quercetin, kaempferol, and stigmasterol in HSD enhance the effects on histidine metabolism, arginine and proline metabolic pathways by modulating a variety of metabolites, which provides the basis for further prevention and treatment of T2DM.

[Mechanism of Jinqi Jiangtang Tablets in treatment of pancreatic ß cell dysfunction based on network pharmacology and molecular docking technology].

The present study investigated the therapeutic efficacy and potential mechanism of Jinqi Jiangtang Tablets(JQJT) on pancreatic ß cell dysfunction based on network pharmacology and molecular docking technology. TCMSP platform was used to retrieve the chemical components and targets of the three Chinese herbal medicines of JQJT. The genes were converted to gene symbol by the UniProt, and its intersection with targets related to pancreatic ß cell function in GeneCards and CTD databases was obtained. The drugs, active components and common targets were imported into Cytoscape 3.8.2 to plot the drug-component-target network. The main effective components and targets were obtained by software analysis. The drug targets and targets related to pancreatic ß cell function were imported separately into the STRING platform for the construction of protein-protein interaction(PPI) networks. The two PPI networks were merged by Cytoscape 3.8.2 and the key targets were obtained by plug-in CytoNCA. The targets obtained from drug-component-target network and PPI networks were imported into DAVID for GO analysis and KEGG enrichment analysis. AutoDock was used to carry out molecular docking of main active components and core targets and Pymol was used to plot the molecular docking diagram. The results showed that there were 371 active components and 203 targets related to JQJT and 2 523 targets related to pancreatic ß cell damage, covering 136 common targets. The results revealed core targets(such as PTGS2, PTGS1, NOS2, ESR1 and RXRA) and effective key components(such as quercetin, kaempferol, luteolin, ß-carotene and ß-sitosterol). KEGG enrichment analysis indicated that apoptosis, inflammation, and other signaling pathways were mainly involved. Molecular docking results showed that the main active components could spontaneously bind to the targets. This study preliminarily revealed the mechanism of JQJT in improving pancreatic ß cell damage through multi-component, multi-target and multi-pathway, and provided a theoretical basis for JQJT in the treatment of pancreatic ß cell dysfunction.

Integrated biomarker for type 2 diabetes mellitus and impaired fasting glucose based on metabolomics analysis using ultra-high performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry.

RATIONALE: The prevalence of type 2 diabetes mellitus (T2DM) is increasing but its early diagnosis in high risk populations remains challenging using only fasting blood glucose (FBG) or hemoglobin A1c measurements. It is, therefore, important to search for an integrated biomarker for early diagnosis by determining metabolites associated with the progression of the disease. METHODS: We recruited 149 participants (51 T2DM patients, 50 individuals with impaired fasting glucose (IFG) and 48 normal glucose tolerance subjects). Their serum samples were analyzed based on a metabolomics approach using ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry (UHPLC/Q-Orbitrap HRMS). The changes in metabolites were profiled and evaluated using univariate and multivariate analyses. Furthermore, a biomarker model was established and the potential biomarkers were evaluated using binary logistic regression analysis and receiver operating characteristic analysis with AUC (area under the curve). Pathway analysis of differential metabolites was performed to reveal the important biological information. RESULTS: Thirty-eight differential metabolites were identified as significantly associated with T2DM patients and 23 differential metabolites with IFG individuals, mainly amino acids, carnitines, and phospholipids. By evaluating 17 potential biomarkers, we defined a novel integrated biomarker consisting of 2-acetolactate, 2-hydroxy-2,4-pentadienoate, L-arabinose and L-glutamine. The AUCs of the integrated biomarker with IFG and T2DM patients were 0.874 and 0.994, respectively, which showed a superior diagnostic performance. The levels of 2-acetolactate and 2-hydroxy-2,4-pentadienoate were strongly positively correlated with FBG, while L-glutamine and L-arabinose were strongly negatively associated with FBG. After pathway analysis, it was suggested that the majority of the influenced metabolic pathways associated with diabetes referred to amino acid metabolism. CONCLUSIONS: The integrated biomarker could diagnose IFG and T2DM with a superior diagnostic performance. This finding provides support for novel biomarkers in the diagnosis and treatment of diabetes.

Metabolic profile of alkaloids in Rhizoma Coptidis in rat plasma, urine and feces after oral administration using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

RATIONALE: Rhizoma Coptidis (RC) has been used to treat diabetes, pertussis, bacillary dysentery, sore throat, eczema, and aphtha for thousands of years. Alkaloids are the major components in RC, and its curative effect is achieved by oral administration. However, information on its composition in vivo is weak. METHODS: In this study, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/QTOF-MS) was used to analyze the major active components and their metabolites in rat plasma, urine and feces after oral administration of RC extract. RESULTS: A total of 96 compounds including 8 prototype compounds and 88 metabolites were identified, and hydroxylation, reduction, demethylenation, demethylation, dehydrogenation, sulfation, glucuronidation and methylation were the major metabolic pathways. CONCLUSIONS: This study analyzed metabolic processes of the major active components in RC in vivo, which provided important information for its active composition and in vivo mechanism research. Meanwhile, metabolic profile studies on representative compounds provided valuable reference materials to elucidate the full-scale metabolites of RC.

Metabolite biomarkers of type 2 diabetes mellitus and pre-diabetes: a systematic review and meta-analysis.

BACKGROUND: We aimed to explore metabolite biomarkers that could be used to identify pre-diabetes and type 2 diabetes mellitus (T2DM) using systematic review and meta-analysis. METHODS: Four databases, the Cochrane Library, EMBASE, PubMed and Scopus were selected. A random effect model and a fixed effect model were applied to the results of forest plot analyses to determine the standardized mean difference (SMD) and 95% confidence interval (95% CI) for each metabolite. The SMD for every metabolite was then converted into an odds ratio to create an metabolite biomarker profile. RESULTS: Twenty-four independent studies reported data from 14,131 healthy individuals and 3499 patients with T2DM, and 14 included studies reported 4844 healthy controls and a total of 2139 pre-diabetes patients. In the serum and plasma of patients with T2DM, compared with the healthy participants, the concentrations of valine, leucine, isoleucine, proline, tyrosine, lysine and glutamate were higher and that of glycine was lower. The concentrations of isoleucine, alanine, proline, glutamate, palmitic acid, 2-aminoadipic acid and lysine were higher and those of glycine, serine, and citrulline were lower in prediabetic patients. Metabolite biomarkers of T2DM and pre-diabetes revealed that the levels of alanine, glutamate and palmitic acid (C16:0) were significantly different in T2DM and pre-diabetes. CONCLUSIONS: Quantified multiple metabolite biomarkers may reflect the different status of pre-diabetes and T2DM, and could provide an important reference for clinical diagnosis and treatment of pre-diabetes and T2DM.

Structural characterization of Astragalus polysaccharide-D1 and its improvement of low-dose metformin effect by enriching Staphylococcus lentus.

To explore the adjuvant therapy drugs of low-dose metformin, one homogeneous polysaccharide named APS-D1 was purified from Astragalus membranaceus by DEAE-52 cellulose and Sephadex G-100 column chromatography. Its chemical structure was characterized by molecular weight distribution, monosaccharide composition, infrared spectrum, methylation analysis, and NMR. The results revealed that APS-D1 (7.36 kDa) consisted of glucose, galactose, and arabinose (97.51 %:1.56 %:0.93 %). It consisted of →4)-α-D-Glcp-(1→ residue backbone with →3)-ß-D-Galp-(1→ residue and terminal-α/ß-D-Glcp-(1→ side chains. APS-D1 could significantly improve inflammation (TNF-α, LPS, and IL-10) in vivo. Moreover, APS-D1 improved the curative effect of low-dose metformin without adverse events. APS-D1 combined with low-dose metformin regulated several gut bacteria, in which APS-D1 enriched Staphylococcus lentus to produce l-carnitine (one of 136 metabolites of S. lentus). S. lentus and l-carnitine could improve diabetes, and reduction of S. lentusl-carnitine production impaired diabetes improvement. The combination, S. lentus, and l-carnitine could promote fatty acid oxidation (CPT1) and inhibit gluconeogenesis (PCK and G6Pase). The results indicated that APS-D1 enhanced the curative effect of low-dose metformin to improve diabetes by enriching S. lentus, in which the effect of S. lentus was mediated by l-carnitine. Collectively, these findings support that low-dose metformin supplemented with APS-D1 may be a favorable therapeutic strategy for type 2 diabetes.

Uncovering the key pharmacodynamic material basis and possible molecular mechanism of Xiaoke formulation improve insulin resistant through a comprehensive investigation.

ETHNOPHARMACOLOGICAL RELEVANCE: Xiaoke formulation (XKF) has been utilized in clinical practice for decades in China as a treatment option for mild to moderate type 2 diabetes. However, there is still a need for systematic research to uncover the key pharmacodynamic material basis and mechanism of XKF. AIM OF THE STUDY: Aim of to investigate the distribution and metabolism of XKF in normal and insulin resistant (IR) mice were different, and elucidate its key pharmacodynamic material basis and mechanism of action. MATERIALS AND METHODS: Ultra performance liquid chromatography/time of flight mass spectrometry technology was employed to investigate the differences in XKF absorption, distribution, and metabolism between normal and IR mice across blood, liver, feces, and urine samples. Further, network pharmacology was used to predict target proteins and their associated signaling pathways. Then, molecular docking was utilized to validate the activity of key pharmacodynamic components and targets. Finally, IR HepG2 cells were used to detect the glucose consumption under the action of key pharmacodynamic material basis. In addition, the expression of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT) and phospho-protein kinase B (p-AKT) was determined using western blotting. RESULTS: The study demonstrates significant distinctions in plasma and liver number and abundance of alkaloids, organic acids, flavonoids, iridoids and saponins between normal and IR mice when XKF was administered. Further analysis has shown that the representative components of XKF, including berberine, chlorogenic acid, calycosin, swertiamarin and astragaloside IV have significantly different metabolic pathways in plasma and liver. Prototypes and metabolites of these components were rarely detected in the urine and feces of mice. According to the network pharmacological analysis, these differential components are predicted to improve IR by targeting key factors such as SRC, JUN, HRAS, NOS3, FGF2, etc. Additionally, the signaling pathways involved in this process include PI3K-AKT pathway, GnRH signaling pathway, and T cell receptor signaling pathway. In addition, in vitro experiments indicate that berberine and its metabolites (berberine and demethyleneberine), chlorogenic acid and its metabolites (3-O-ferulic quinic acid and 5-O-ferulic quinic acid), calycosin and swertiamarin could improve IR in IR-HepG2 cells by elevating the expression of PI3K and AKT, leading to an increase in glucose consumption. CONCLUSION: The key pharmacodynamic material basis of XKF, such as berberine and its metabolites (berberrubine and demethyleneberberine), chlorogenic acid and its metabolites (3-O-feruloylquinic acid and 5-O-feruloylquinic acid), calycosin and swertiamarin influence the glucose metabolism disorder of IR-HepG2 cells by regulating the PI3K/AKT signalling pathway, leading to an improvement in IR.

Network pharmacology-based dissection of the underlying mechanisms of dyspnoea induced by zedoary turmeric oil.

Zedoary turmeric oil (ZTO) has been widely used in clinic. However, the unpleasant induced dyspnoea inevitably impedes its clinical application. Thus, it is urgent to elucidate the mechanism underlying the ZTO-induced dyspnoea. In this study, network pharmacology was firstly performed to search the clue of ZTO-induced dyspnoea. The key target genes of ZTO-induced dyspnoea were analysed using GO enrichment analysis and KEGG pathway analysis. GO analysis suggested that haem binding could be a key molecular function involved in ZTO-induced dyspnoea. Hence, the haemoglobin (Hb) was focused for its oxygen-carrying capacity with haem as its critical component binding to the oxygen. Ultraviolet-visible absorption spectrum indicated that the ZTO injection (ZTOI) perturbed the Soret band of Hb, suggesting an interaction between ZTO and Hb. GC-MS analysis revealed that ß-elemene, germacrone, curdione and furanodiene were main components of ZTOI. Molecular docking was used to illustrate the high affinity between representative sesquiterpenes and Hb, which was finally confirmed by surface plasmon resonance, suggesting their potential roles in dyspnoea by ZTO. Following a network pharmacology-driven strategy, our study revealed an intervened Hb-based mechanism underlying the ZTO-induced dyspnoea, providing a reference for elucidating mechanism underlying adverse drug reactions of herbal medicines in clinic.

Novel weight loss diet attenuates dietary-induced obesity in mice and might correlate with altered gut microbiota and metabolite profiles.

Although many dietary patterns have been studied for weight loss, various limitations still exist. Therefore, we designed a novel weight loss diet (NWLD) with carbohydrate, protein, and fat (energy) contents of 45%, 20%, and 35%, respectively. The saturated fatty acids: monounsaturated fatty acids:polyunsaturated fatty acids ratio was 1:2:1, and the insoluble: soluble dietary fiber ratio was 2:1. We aimed to observe the effect of NWLD on weight loss and understand the underlying metabolic mechanisms. Twenty-nine male C57BL/6J mice were selected. Nine mice were fed ordinary feed in a blank control group, and the rest were fed a high-fat diet (HFD) to establish obese mouse models. Twelve weeks later, obesity models were established, and 10 obese mice were switched to NWLD feeding. Six weeks after switching the diet, the serum, intestinal feces, and kidneys of mice were collected. Obesity-related indicators, gut microbial composition, and fecal metabolite profiles of all the mice were determined, and the correlations among these indicators were analyzed. Kidney function indicators were also assessed. The results showed that the NWLD attenuated HFD-induced weight gain, serum triglycerides (TG), and inflammatory factors, optimized the body composition without kidney function impairment. Amino acid metabolism pathways and metabolites might play key roles in this process. The findings of this research imply that NWLD could be an effective nutritional remedy for managing dietary-induced obesity.

Metabolomics based plasma biomarkers for diagnosis of oral squamous cell carcinoma and oral erosive lichen planus.

Backgrounds: To identify diagnostic biomarkers for differentiating oral squamous cell carcinoma (OSCC) from oral erosive lichen planus (OELP) and investigate potential biomarkers associated with malignant transformation. Methods: In this study, 72 patients with OSCC, 75 patients with OELP subjects were recruited. Their plasma samples were analyzed by ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry, (UHPLC/Q-Orbitrap HRMS). Principal component analysis, orthogonal partial least square discrimination analysis, t-test analysis and false discovery rate were used to identify different metabolites in patients with OSCC and OELP. The metabolic pathway analysis was performed by MetaboAnalyst. To further screen and identify the biomarkers of OSCC and establish a diagnostic panel, binary logistic regression analysis and receiver operating characteristic analysis were used. The data were then combined with blood samples from healthy individuals for mass spectrometry analysis to obtain biomarkers related to malignant transformation. Results: A total of 20 kinds of endogenous metabolites were identified from plasma samples of OSCC patients and OELP patients. Metabolic pathway analysis showed that the biomarkers associated with OSCC were closely related to cholic acid metabolism and amino acid metabolism. Finally, a diagnostic panel composed of decanoylcarnitine, cysteine and cholic acid was established. This diagnostic panel had good diagnostic efficiency with the AUC=0.998. Other metabolites including uridine, taurine, glutamate, citric acid and LysoPC(18:1) were identified to be general biomarkers for malignant transformation of OELP. Conclusion: Biomarkers based on plasma metabolomics are of great significance for the prediction of malignant transformation of OELP and early diagnosis of OSCC.

Polystyrene microplastic exposure induces insulin resistance in mice via dysbacteriosis and pro-inflammation.

Microplastics (MPs) as emerging contaminants have become a global environmental problem. However, studies on the effects of MPs on metabolic diseases remain limited. Here, we evaluated the effects of polystyrene (PS), one of the most prominent types of MPs, on insulin sensitivity in mice fed with normal chow diet (NCD) or high-fat diet (HFD), and explained the underlying mechanisms. Mice fed with NCD or HFD both showed insulin resistance (IR) after PS exposure accompanied by increased plasma lipopolysaccharide and pro-inflammatory cytokines such as tumor necrosis factor-α and interleukin-1ß. Exposure to PS also resulted in a significant decrease in the richness and diversity of gut microbiota, particularly an increase in the relative abundance of Gram-negative bacteria such as Prevotellaceae and Enterobacteriaceae. Additionally, PS with a small particle size (5 µm) accumulated in the liver, kidneys and blood vessels of mice. Further analyses showed inhibition of the insulin signaling pathway in the liver of PS exposed mice, such as inhibition of IRS1 and decreased expression of PI3K. Hence, the mechanism of PS exposure to induce IR in mice might be mediated through regulating gut microbiota and PS accumulation in tissues, stimulating inflammation and inhibiting the insulin signaling pathway. In conclusion, PS might be a potential environmental contaminant that causes metabolic diseases associated with IR.

Lipophagy: A New Perspective of Natural Products in Type 2 Diabetes Mellitus Treatment.

Autophagy has been reported to involve in the pathogenesis of type 2 diabetes mellitus (T2DM), which protects the insulin target tissues and pancreatic ß-cells. However, autophagy is inhibited when the cells are lipid overload. That, in turn, increases the accumulation of fat. Lipotoxicity caused by excessive lipid accumulation contributes to pathogenesis of T2DM. Therefore, it is undeniable to break the vicious circles between lipid excess and autophagy deficiency. Lipophagy, a selective form of autophagy, is characterized by selective breakdown of lipid droplets (LDs). The nutritional status of cells contributes to the way of autophagy (selective or non-selective), while selective autophagy helps to accurately remove excess substances. It seems that lipophagy could be an effective means to decrease abnormal lipid accumulation that leads to insulin resistance and ß-cell impairment by removing ectopic LDs. Based on this process, many natural compounds have been reported to decrease lipid accumulation in tissues through autophagy-lysosomal pathway, which gradually highlights the significance of lipophagy. In this review, we focus on the mechanisms that lipophagy improves T2DM and natural products that are applied to induce lipophagy. It is also suggested that natural herbs with rich contents of natural products inducing lipophagy would be potential candidates for alleviating T2DM.