Discrimination of type 2 diabetes mellitus corresponding to different traditional Chinese medicine syndromes based on plasma fatty acid profiles and chemometric methods

Review on the systems biology research of Yin-deficiency-heat syndrome in traditional Chinese medicine

Traditional Chinese medicine (TCM) is a systematic medical method that has existed for more than 3,000 years. Unlike Western medicine, the disease diagnosis in TCM is carried out by inspection, auscultation, olfaction, interrogation, and palpation. The patient is then treated according to the disease and corresponding TCM syndrome. However, the development of Chinese medicine is stagnated, partially because it can be influenced by subjective factors, such as the experience and knowledge of TCM practitioners, and there is a lack of relevant biological research on TCM syndromes. Yin-deficiency-heat (YDH) syndrome in TCM is characterized by a series of pathological changes caused by the insufficiency of Yin-fluid, inability to moisturize, and the failure to suppress Yang. In recent years, systems biology research on TCM syndromes has gradually become the focus of TCM research, including syndrome differentiation and functional research using systems biology methodologies such as proteomics, transcriptomics, and metabolomics. This journal aims to publish a series of issues on the systems biology research of TCM syndromes that can provide biological indicators for the syndrome differentiation of YDH syndrome and can provide perspectives on the biological research of YDH syndrome.

The Association Between Health-Related Behaviors and Traditional Chinese Medicine Syndromes in Type 2 Diabetes Mellitus Patients

Background

Traditional Chinese medicine (TCM) has certain advantages in treating diabetes via TCM syndromes differentiation, and health-related behaviors can regulate TCM syndromes. This study aimed to identify the clusters of TCM syndromes in type 2 diabetes mellitus (T2DM) patients and to explore the association between health-related behaviors and those TCM syndromes clusters.

Methods

This was a cross-sectional study of 1761 T2DM patients from the Ningxia Province. The TCM syndromes (11 TCM syndromes in total) scale was used to collect the syndrome information. Health-related behaviors, including smoking, alcohol use, tea drinking, the intensity of physical activity, sleep quality, and sleep duration, were collected via a face-to-face interview questionnaire. Latent profile analysis was employed to identify clusters of 11 TCM syndromes. Multinomial logistic regression was employed to examine the relationships between health-related behaviors and clusters of TCM syndromes.

Results

TCM syndromes in T2DM patients were classified into three profiles using latent profile analysis: light, moderate, and heavy. Participants with poor health-related behaviors were more likely to have heavy 1.49 (95% CI: 1.12, 1.99) or moderate 1.75 (95% CI: 1.10, 2.79) profiles than those with good health-related habits. Smokers, tea drinkers, and those with poor sleep quality were more likely to have a moderate profile and heavy profile than a light profile. Compared with heavy physical activity, moderate activity 0.24 (95% CI: 0.07, 0.88) was negatively associated with a heavy profile.

Conclusion

Results showed that most participants had light or moderate levels of TCM syndromes, and those with poor health-related behaviors were more likely to have heavy or moderate profiles. In the context of precision medicine, these results have important implications for understanding the prevention and treatment of diabetes via changing lifestyles and behaviors to regulate TCM syndromes.

The therapeutic mechanism of Yuye decoction on type 2 diabetes mellitus based on network pharmacology and experimental verification

ETHNOPHARMACOLOGICAL RELEVANCE

Yuye decoction (YYD) has been widely used as a folk Chinese herbal formula in clinical treatment of type 2 diabetes mellitus(T2DM) for many years. However, its mechanism is still unclear.

AIM OF THE STUDY

The aim of this study was to explore the potential mechanism of YYD against T2DM initially by UHPLC-MS/MS combining with network pharmacology, molecular docking techniques and experimental validation.

MATERIALS AND METHODS

The main ingredients in the water extract of YYD were initially identified using UHPLC-MS/MS analysis. Combined with network pharmacology and molecular docking techniques, the YYD key compounds-core targets-key signaling pathways network was constructed and the binding activity of key components to core targets was validated. The T2DM rat model was induced by Streptozotocin combined with high glucose and high fat diets. The apoptosis cell model of mouse islet β-cell of Min6 was induced by high-glucose and palmitic acid. Histopathological and immunofluorescence satining were used to evaluate pancreatic islet β-cell function and apoptosis in rats. Min6 cell viability and apoptosis ratio were evaluated by CCK-8 and TUNEL staining. The predicted targets and pathways were validated by experiments in vitro and in vivo.

RESULTS

The 56 compounds from YYD were identified by UHPLC-MS/MS. The potential targets of the above compounds were predicted by online compound target database, among of which 362 targets were associated with T2DM. Protein-protein interaction analysis identified the main targets such as SRC, MAPK1, PIK3R1, AKT1, HRAS and HSP90AA1, which were considered as the therapeutic targets of YYD on against T2DM. Functional enrichment analysis revealed that PI3K/AKT, FoxO and apoptosis signaling pathways were significantly enriched. Molecular docking results showed that compounds of monolinolein, neomangiferin, mangiferin, pelargonidin-3-O-glucoside and acacetin from YYD had high binding activities to PIK3R1, AKT1, Sirt1 and FoxO1. Therefore, PI3K/AKT1, Sirt1/FoxO1 and apoptotic signaling pathways were considered as predicted targets for experimental validation study. Animal experiments showed that YYD reduced blood glucose levels, improved pancreatic dysfunction and pancreatic islet β-cells apoptosis in T2DM rats which contributed to the activation of AKT1 and FoxO1 and their related signaling molecules. These results were confirmed in Min6 cell model induced by high-glucose and palmitic acid.

CONCLUSIONS

In summary, this study systematically visualized the possible therapeutic effects and mechanisms of YYD on T2DM through the network pharmacology approach and experimental study. The results indicated that YYD could prevent pancreatic islet dysfunction and reverse islet of β-cells apoptosis possibly via PI3K/AKT1, Sirt1/FoxO1 signaling pathways.

Emerging Applications of Metabolomics to Assess the Efficacy of Traditional Chinese Medicines for Treating Type 2 Diabetes Mellitus

Diabetes is a common and complex disease that can exacerbate the complications related to cardiovascular disease, and this is especially true for type 2 diabetes mellitus (T2DM). In addition to the standard pharmacological therapies, T2DM has also been treated with nonconventional regimens such as traditional Chinese medicine (TCM), e.g., herbal medicines and TCM prescriptions, although the mechanisms underlying the therapeutic benefits remain unclear. In this regard, many studies have used metabolomics technology to elucidate the basis for the efficacy of TCM for T2DM. Metabolomics has recently attracted much attention with regard to drug discovery and pharmacologically relevant natural products. In this review, we summarize the application of metabolomics to the assessment of TCM efficacy for treating T2DM. Increasing evidence suggests that the metabolic profile of an individual patient may reflect a specific type of T2DM syndrome, which may provide a new perspective for disease diagnosis. In addition, TCM has proved effective for countering the metabolic disorders related to T2DM, and this may constitute the basis for TCM efficacy. Therefore, further determining how TCM contributes to the reversal of metabolic disorders, such as using network pharmacology or by assessing the contribution of host–gut microbiota interactions, will also provide researchers with new potential targets for pharmacologic-based therapies.

Based on urine metabolomics to study the mechanism of Qi-deficiency affecting type 2 diabetes rats using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

Qi-deficiency also called energy deficiency, which approximates to the term of sub-health in contemporary medical theory. Diabetes is similar to the symptoms of "xiaoke" in traditional Chinese medicine (TCM) which is linked with Qi-deficiency. However, the mechanism of Qi-deficiency on type 2 diabetes (T2D) has not been completely elucidated. In this study, a model on Qi-deficiency T2D rat was established by using diet with high fat and high sugar and small-dose STZ induction combined with exhaustive swimming, and the model was evaluated by pathological section, hematological index and serum biochemical parameters. Applying urine metabolomics based on ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to explore the underlying molecular mechanism of Qi-deficiency on T2D and 32 urinary metabolites were identified as prospective biomarkers for Qi-deficiency T2D rats. Metabolic pathway analysis indicated that synthesis and degradation of ketone bodies, starch and sucrose metabolism, phenylalanine metabolism, arachidonic acid metabolism, butanoate metabolism and TCA cycle, etc., were closely related to potential mechanisms of Qi-deficiency on T2D. The metabolomics results can provide reliable data support for complex TCM syndrome diagnosis.

A Network Pharmacology-Based Strategy For Predicting Active Ingredients And Potential Targets Of LiuWei DiHuang Pill In Treating Type 2 Diabetes Mellitus

Background

Traditional Chinese medicine (TCM) formulations have proven to be advantageous in clinical treatment and prevention of disease. LiuWei DiHuang Pill (LWDH Pill) is a TCM that was employed to treat type 2 diabetes mellitus (T2DM). However, a holistic network pharmacology approach to understanding the active ingredients and the therapeutic mechanisms underlying T2DM has not been pursued.

Methods

A network pharmacology approach including drug-likeness evaluation, oral bioavailability prediction, virtual docking, and network analysis has been used to predict the active ingredients and potential targets of LWDH Pill in the treatment of type 2 diabetes.

Results

The comprehensive network pharmacology approach was successfully to identify 45 active ingredients in LWDH Pill. 45 active ingredients hit by 163 potential targets related to T2DM. Ten of the more highly predictive components (such as :quercetin, Kaempferol, Stigmasterol, beta-sitosterol, Kadsurenone, Diosgenin, hancinone C, Hederagenin, Garcinone B, Isofucosterol) are involved in anti-inflammatory, anti-oxidative stress, and the reduction of beta cell damage. LWDH Pill may play a role in the treatment of T2DM and its complications (atherosclerosis and nephropathy) through the AGE-RAGE signaling pathway, TNF signaling pathway, and NF-kappa B signaling pathway.

Conclusion

Based on a systematic network pharmacology approach, our works successfully predict the active ingredients and potential targets of LWDH Pill for application to T2DM and helps to illustrate mechanism of action on a comprehensive level. This study provides identify key genes and pathway associated with the prognosis and pathogenesis of T2DM from new insights, which also demonstrates a feasible method for the research of chemical basis and pharmacology in LWDH Pill.

Research progress on Traditional Chinese Medicine syndromes of diabetes mellitus

With the improvement of people's living standard and the changes of environment, the incidence of diabetes mellitus (DM) is on the rise day by day, while clinical treatment mainly aims at lowering blood glucose, instead of fundamental prevention and treatment. What's worse, the measures of prevention and treatment of DM complications remain inadequate. Both Chinese and modern medicine have advantages and disadvantages in treating DM, therefore, it would be a worthy attempt to break through the bottleneck of DM treatment by combining the advantages of both, and explore the new measures to prevent and deal with DM from the perspective of the combination of Traditional Chinese Medicine (TCM) syndrome and modern medicine. In this paper, modern research methods and possible indicators of TCM syndromes of DM were expounded from clinical and basic research aspects, aiming to find specific biomarkers of TCM syndromes, and providing experimental supports for the diagnosis and treatment of DM and the verification of TCM theory.

Application of metabolomics for unveiling the therapeutic role of traditional Chinese medicine in metabolic diseases

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional medicine has been practiced for thousands of years in China and some Asian countries. Traditional Chinese Medicine (TCM) is characterized as multi-component and multiple targets in disease therapy, and it is a great challenge for elucidating the mechanisms of TCM.

AIM OF THE REVIEW

Comprehensively summarize the application of metabolomics in biomarker discovery, stratification of TCM syndromes, and mechanism underlying TCM therapy on metabolic diseases.

METHODS

This review systemically searched the publications with key words such as metabolomics, traditional Chinese medicine, metabolic diseases, obesity, cardiovascular disease, diabetes mellitus in "Title OR Abstract" in major databases including PubMed, the Web of Science, Google Scholar, Science Direct, CNKI from 2010 to 2019.

RESULTS

A total of 135 papers was searched and included in this review. An overview of articles indicated that metabolic characteristics may be a hallmark of different syndromes/models of metabolic diseases, which provides a new perspective for disease diagnosis and therapeutic optimization. Moreover, TCM treatment has significantly altered the metabolic perturbations associated with metabolic diseases, which may be an important mechanism for the therapeutic effect of TCM.

CONCLUSIONS

Until now, many metabolites and differential biomarkers related to the pathogenesis of metabolic diseases and TCM therapy have been discovered through metabolomics research. Unfortunately, the biological role and mechanism of disease-related metabolites were largely unclarified so far, which warrants further investigation.

UPLC-Q/TOF-MS-Based Serum Metabolomics Reveals Hypoglycemic Effects of Rehmannia glutinosa, Coptis chinensis and Their Combination on High-Fat-Diet-Induced Diabetes in KK-Ay Mice

Diabetes is a worldwide severe health issue which causes various complications. This study aimed to evaluate the hypoglycemic effects of Rehmannia glutinosa (RG), Coptis chinensis (CC) alone and their combination on high-fat-diet-induced diabetes in mice via biochemical assays and UPLC-Q/TOF-MS-based serum metabolomic analysis. Diabetic KK-Ay mice were induced by high-fat diet and treated for eight weeks, separately with RG, CC and their combination and the positive control drug metformin. Administration of RG and CC alone, and their combination could decrease the fasting blood glucose level, ameliorate the tolerance of glucose, and recover the levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in sera of diabetic mice. Orthogonal partial least squares discriminant analysis (OPLS-DA) on serum metabolomes revealed that 79 ESI⁺ and 76 ESI⁻ metabolites were changed by diabetes mellitus (DM) compared to the normal control. Heatmaps on these diabetes-related metabolites showed that CC and RG/CC were clustered closer with the normal control, indicating that they had the better antidiabetic effects at the metabolite level. Fifteen of the differential metabolites in DM serum were annotated and their related metabolic pathways were lipid metabolism. These data suggested that RG and CC alone and in combination treatment had the antidiabetic activity in lowering glycemia and improving lipid metabolism. UPLC-Q/TOF-MS-based metabolomics shed light on the differential metabolite effects of RG and CC in DM treatment. However, it should be noted that some differential metabolites were possibly generated or not detected due to our groupwise run order, which possibly contributed to or covered the group difference in our experiment. They need to be further discriminated in the future work.

Classification of Gan Dan Shi Re Pattern and Gan Shen Yin Xu Pattern in Patients with Hepatitis B Cirrhosis Using Metabonomics

Objective

This study aimed to analyze the differential metabolites and their metabolic pathways from the serum of patients with hepatitis B cirrhosis, with two typical patterns of Gan Dan Shi Re (GDSR) and Gan Shen Yin Xu (GSYX) based on the theory of traditional Chinese medicine (TCM). It also investigated the variation in the internal material basis for the two types of patterns and provided an objective basis for classifying TCM patterns using metabolomic techniques.

Methods

The serum samples taken from 111 qualified patients (40 GDSR cases, 41 GSYX cases, and 30 Latent Pattern (LP) cases with no obvious pattern characters) and 60 healthy volunteers were tested to identify the differential substances relevant to hepatitis B cirrhosis and the two typical TCM patterns under the gas chromatography–time-of-flight mass spectrometry platform. The relevant metabolic pathways of differential substances were analyzed using multidimensional statistical analysis.

Results

After excluding the influence of LP groups, six common substances were found in GDSR and GSYX patterns, which were mainly involved in the metabolic pathways of glycine, serine, threonine, and phenylalanine. Eight specific metabolites involved in the metabolic pathways of linoleic, glycine, threonine, and serine existed in the two patterns.

Conclusions

The data points on the metabolic spectrum were found to be well distributed among the differential substances between the two typical TCM patterns of patients with hepatitis B cirrhosis using metabolomic techniques. The differential expression of these substances between GDSR and GSYX patterns provided an important objective basis for the scientific nature of TCM pattern classification at the metabolic level.

Dose-dependent target diversion of Danhong injection on the Glu-GLT-1/Gly-GlyRα dynamic balance module of cerebral ischemia

Function-oriented modular structure analysis is a great challenge in module-based pharmacological studies. A strategy to uncover target-target interaction (TTI) and dynamic balance regularity (DBR) was established to discover the structural factors influencing modular functions and explore the mechanism of Danhong injection (DHI) in treating cerebral ischemia. The dose-related metabolic features of DHI intervention were investigated using metabolomics and modular pharmacology. The findings indicated that Glu/Gly was a biomarker and Glu-GLT-1/Gly-GlyRα was the core unit regulated by DHI. Gly and Glu displayed opposite patterns and functional roles, representing intra-modular balance. GlyRα was identified as the upstream target and GLT-1 as the downstream target by inhibiting or activating GlyRα, indicating that DHI has two dose-dependent regulatory modes. GlyRα was the major target at low doses, while GLT-1 was activated as the dominant target as doses accumulated. Our study reveals that target-target interaction and dynamic balance regularity are the key factors influencing modular functions, which is a promising breakthrough for module-based pharmacological studies.

Association between genetic variants and characteristic symptoms of type 2 diabetes: A matched case-control study

OBJECTIVE

To examine the association of genetic variants with characteristic symptoms of type 2 diabetes mellitus (T2DM).

METHODS

A matched case-control study was performed to investigate the association between common variants in four genes (CDKAL1, GLIS3, GRK5, and TCF7L2) and symptoms of T2DM. Symptoms were examined with questionnaire for 710 subjects. Genomic DNA was extracted from peripheral blood mononuclear cell by salting-out procedure. Genotyping was carried out by direct sequencing of the unpurified polymerase chain reaction products.

RESULT

Most of the T2DM patients pressented characteristic symptoms, such as feeling weak in limbs (P =0.0057), hand tremor (P =0.0208), bradymasesis (P =0.0234), and polyuria (P =0.0051). Some of the T2DM patients shared characteristic symptoms, such as desire for cold drinks (P =0.0304), polyphagia (P =0.0051), and furred tongue (P =0.028). The impaired glucose regulation (IGR) cases took only one characteristic symptom of frequent micturition (P =0.0422). GLIS3 rs7034200 and GRK5 rs10886471 were significantly associated with increased T2DM risk (GLIS3 rs7034200 under dominant model: P=0.0307; GRK5 rs10886471 under recessive model: P=0.0092). However, only the rs10886471 polymorphism in GRK5 showed a significant effect on both differentiated symptoms and T2DM risk. The C-allele was involved in both dampness-heat encumbering Pi (Spleen) syndrome (P =0.047) and qi-yin deficiency syndrome (P =0.002) via increased GRK5 expression.

CONCLUSIONS

Both T2DM and IGR exhibited its corresponding characteristic symptoms. The variants of GRK5 were involved with both qi-yin deficiency syndrome and dampness-heat encumbering Pi syndrome.

Chemometrics applied to quality control and metabolomics for traditional Chinese medicines

Traditional Chinese medicines (TCMs) bring a great challenge in quality control and evaluating the efficacy because of their complexity of chemical composition. Chemometric techniques provide a good opportunity for mining more useful chemical information from TCMs. Then, the application of chemometrics in the field of TCMs is spontaneous and necessary. This review focuses on the recent various important chemometrics tools for chromatographic fingerprinting, including peak alignment information features, baseline correction and applications of chemometrics in metabolomics and modernization of TCMs, including authentication and evaluation of the quality of TCMs, evaluating the efficacy of TCMs and essence of TCM syndrome. In the conclusions, the general trends and some recommendations for improving chromatographic metabolomics data analysis are provided.

A metabolomics approach to stratify patients diagnosed with diabetes mellitus into excess or deficiency syndromes

The prevalence of type 2 diabetes continuously increases globally. The traditional Chinese medicine (TCM) can stratify the diabetic patients based on their different TCM syndromes and, thus, allow a personalized treatment. Metabolomics is able to provide metabolite biomarkers for disease subtypes. In this study, we applied a metabolomics approach using an ultraperformance liquid chromatography (UPLC) coupled with quadruple-time-of-flight (QTOF) mass spectrometry system to characterize the metabolic alterations of different TCM syndromes including excess and deficiency in patients diagnosed with diabetes mellitus (DM). We obtained a snapshot of the distinct metabolic changes of DM patients with different TCM syndromes. DM patients with excess syndrome have higher serum 2-indolecarboxylic acid, hypotaurine, pipecolic acid, and progesterone in comparison to those patients with deficiency syndrome. The excess patients have more oxidative stress as demonstrated by unique metabolite signatures than the deficiency subjects. The results provide an improved understanding of the systemic alteration of metabolites in different syndromes of DM. The identified serum metabolites may be of clinical relevance for subtyping of diabetic patients, leading to a personalized DM treatment.

Mass spectrometry analysis of blood plasma lipidome as method of disease diagnostics, evuation of effectiveness and optimization of drug therapy

A new method for the analysis of blood lipid based on direct mass spectrometry of lipophilic low molecular weight fraction of blood plasma has been considered. Such technique allows quantification of hundreds of various types of lipids and this changes existing concepts on diagnostics of lipid disorders and related diseases. The versatility and quickness of the method significantly simplify its wide use. This method is applicable for diagnostics of atherosclerosis, diabetes, cancer and other diseases. Detalization of plasma lipid composition at the molecular level by means of mass spectrometry allows to assess the effectiveness of therapy and to optimize the drug treatment of cardiovascular diseases by phospholipid preparations.

Evaluation of some plants for potential dipeptidyl peptidase IV inhibitory effects in vitro

Objective: Dipeptidyl peptidase IV (DPP IV) is a serine amino (exo) peptidase which regulates various processes most notably plasma glucose homeostasis by cleaving incretin peptide hormones as glucagon-like peptide-1 (GLP-1) and glucose-dependent insulin releasing polypeptide (GIP). Realization of the inhibition of this enzyme in controlling diabetes is one of the strategies adopted in recent years. The present study was designed to investigate the DPP IV inhibitory effects of sixteen plant having antidiabetic property in aqueous extracts in correlation with their protein content.

Methods: In vitro DPP IV inhibition was evaluated by the specific inhibitory activity of plant aqueous extracts prepared without and with heat (60°C) treatment.

Results: Among the tested plants Vitis vinifera L., Artemisia dracunculus L., Prunus laurocerasus L., Rubus caesius L. and Olea europaea L. extracts showed DPP IV inhibitory activity with respect to IC50 values of 0.04-0.09 mg protein/ml. Kinetic analysis indicated that the inhibitor potency of A. dracunculus extract was stronger than the other extracts.

Conclusion: The present study is the first report on screening and preliminary characterization of DPP IV inhibitory activity in aqueous extracts of selected antidiabetic medicinal food. This study could provide a new insight into DPP IV inhibitors from plants that could be useful for treatment of Type 2 diabetes.

The application of metabolomics in traditional Chinese medicine opens up a dialogue between Chinese and Western medicine

Metabolomics provides an opportunity to develop the systematic analysis of the metabolites and has been applied to discovering biomarkers and perturbed pathways which can clarify the action mechanism of traditional Chinese medicines (TCM). TCM is a comprehensive system of medical practice that has been used to diagnose, treat and prevent illnesses more than 3000 years. Metabolomics represents a powerful approach that provides a dynamic picture of the phenotype of biosystems through the study of endogenous metabolites, and its methods resemble those of TCM. Recently, metabolomics tools have been used for facilitating interactional effects of both Western medicine and TCM. We describe a protocol for investigating how metabolomics can be used to open up 'dialogue' between Chinese and Western medicine, and facilitate lead compound discovery and development from TCM. Metabolomics will bridge the cultural gap between TCM and Western medicine and improve development of integrative medicine, and maximally benefiting the human.

Progress and perspectives of biomarker discovery in Chinese medicine research

Biomarker discovery in Chinese medicine (CM) has recently attracted a great deal of attention, owing to the promise of high-throughput technologies development and the potential of Chinese herbal medicine. Furthermore, it seems that pattern classification in CM might be serving as inspirational analogy and a practical guide, which might contribute to biomarkers discovery rather than just being used as diagnostic method. Although much work is still needed to identify markers, efforts are now being directed towards discovering biomarkers or biomarkers based network that could target herbal formulae. In this article, we review progress in biomarker discovery development, discuss current biomarker discovery in CM highlighting challenges and opportunities of pattern classification and presenting a perspective of the future integrative modeling approaches as an emerging trend in biomarker discovery.

Electroacupuncture at Acupoints Reverses Plasma Glutamate, Lipid, and LDL/VLDL in an Acute Migraine Rat Model: A (1) H NMR-Based Metabolomic Study

Background. The objective of this study was to identify potential biomarkers of electroacupuncture (EA) on relieving acute migraine through metabolomic study. Methods. EA treatments were performed on both acupoints and nonacupoints on the nitroglycerin (NTG)-induced migraine rat model. NMR experiments and multivariate analysis were used for metabolomic analysis. Results. The number of head-scratching, the main ethology index of migraine rat model, was significantly increased (P < 0.01) after NTG injection. The plasma metabolic profile of model group was distinct from that of the control group. Glutamate was significantly increased (P < 0.01), whereas lipids were significantly decreased (P < 0.01) in model rats. After EA at acupoints, the metabolic profile of model rats was normalized, with decreased glutamate (P < 0.05) and increased lipids (P < 0.01). In contrast, EA at nonacupoints did not restore the metabolic profile, but with six metabolites significantly different from acupoints group. Interestingly, the number of head-scratching and glutamate level were significantly decreased (P < 0.05) after receiving EA at both acupoints and nonacupoints. Conclusions. EA at acupoints may relieve acute migraine by restoring the plasma metabolic profile and plasma glutamate, while EA at nonacupoints may modestly relieve acute migraine by decreasing plasma glutamate.

Clinical Applications of Omics Technologies on ZHENG Differentiation Research in Traditional Chinese Medicine

Traditional Chinese medicine (TCM) ZHENG is the basic concept of TCM theory. The effectiveness of TCM treatment depends on the accuracy of ZHENG differentiation. ZHENG differentiation, using the "four diagnostic methods," has the drawbacks of subjectivity and variability. Following development of omics technologies, which study the functional activities of human body from a system-wide perspective, it has been more and more applied in study of objectivity differentiating TCM ZHENG and understanding its biological mechanisms. This paper reviewed the literatures of clinical TCM ZHENG differentiation researches, underlying omics technologies, and indicated the increased trends of related articles with four kinds of omics technologies, including genomics, transcriptomics, proteomics and metabolomics, and the correlations between ZHENG differentiation and findings in omics studies. Moreover, the paper summarized the typical omics application in common studied diseases and TCM ZHENGs and discussed the main problems and countermeasure of ZHENG differentiation researches. The work here may provide a reference for further research of TCM ZHENG differentiation using omics technologies.

Application of metabolomics on diagnosis and treatment of patients with psoriasis in traditional Chinese medicine

Traditional Chinese medicine (TCM) is one of the oldest forms of medical system. With syndrome as the core of diagnosis and therapy in TCM, it has the advantage of collecting macroscopic information of patients for diagnosis. To understand the in vivo mechanism of TCM, a metabolomics approach was used to investigate the global biological characterization of the urine of psoriasis patients with Blood Stasis Syndrome and the therapeutic metabolomics mechanism of the Optimized Yinxieling formula. A total of 41 cases of psoriasis patients with Blood Stasis Syndrome and 19 healthy volunteers were enrolled in this study. Fasting urine samples from patients with consecutive Optimized Yinxieling intake after 0, 4, 8 and 12 weeks and from healthy volunteers were analyzed by Orthogonal Projection on Latent Structures Discriminant Analysis (OPLS-DA), which was utilized for High Performance Liquid Chromatography (HPLC) analysis and temporal metabolic changes identification. For psoriasis group, the scores of PASI of patients decreased after 12 weeks of Optimized Yinxieling treating. The metabolic variations visualized not only in the healthy group and psoriasis group, but also in the psoriasis group before and after Optimized Yinxieling treatment, demonstrated that the metabolic characteristics of the two groups were significantly different. The optimized complex structure of the target proteins from Protein Data Bank was analyzed by software package Discovery Studio. With docking score of original inhibitor and the receptor as the threshold values, two compounds from Chinese medicinal chemical database were predicted to have good interactions with the target proteins. The Metabolomics technique combining molecular docking analysis enhanced our current understanding of the metabolic response to Blood Stasis Syndrome of Psoriasis and the action mechanism of Optimized Yinxieling. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai.