Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine-immune network

Metabolomics study of diabetic retinopathy using gas chromatography-mass spectrometry: a comparison of stages and subtypes diagnosed by Western and Chinese medicine

Diabetic retinopathy (DR) is a serious microvascular syndrome of diabetes, and is one of the most frequent causes of blindness in the world. It has three progressive stages with complex metabolic deregulations in the holistic system of Western medicine. Chinese medicine classifies DR into two different syndrome types; integrating Western and Chinese medicine to treat DR is a validated therapeutic approach in China. In this research, the systemic metabolite change of DR was investigated from the viewpoint of both Western and Chinese medicine, using metabolomics based on gas chromatography-mass spectrometry. The data revealed both perspectives can reflect the metabolic patterns, development and differentiation of DR, and the data also had good correlation and complementarity in characterizing the process of DR. Potential biomarkers of DR based on the two perspectives indicated the alterative modes of metabolites and metabolic pathways in the disease, e.g. the disturbance in fatty acids, amino acids and glucose, etc. The results showed the usefulness and validity of combining both Western and Chinese medicine to study the subtypes of DR and the mechanisms involved.

A combination system for prediction of Chinese Materia Medica properties

Identifying and explaining the property of Chinese Materia Medica (CMM) is an important and urgent mission in recent CMM researches. In the present work, we built a combination system for predicting the cold/hot property of CMM based on chemical material basis. A novel strategy, weight center treatment, was used to solve the problem that the chemical description was unable to be applied to CMM. As the results of prediction, the accuracy of 83.3% and 81.0% for the training and the test set, respectively, indicates that this system is a useful tool to predict the property of unidentified folk herbs and foreign herbs. It will characterize these herbs with traditional Chinese medicine properties so as to design new CMM formulas for better therapeutics. Moreover, we found some interesting explanation about the property of CMM based on chemical information by using the selected descriptors. It will give new insight into the CMM property from the standpoint of chemistry.

Treatment with Aconitum Lizhong Pill down-regulates liver energy charge in rats with Spleen Yang Deficiency syndrome

AIM: To observe the effect of treatment with Aconitum Lizhong Pill on liver energy charge in rats with Spleen Yang Deficiency syndrome.

METHODS: Eighteen litters of newborn rats were used in this study. Nine littermates in each litter were randomized into nine groups. Four groups underwent thyroidectomy, and five groups did not. Thyroidectomy was carried out with ¹³¹iodine to destroy part of the thyroid on day 1 after birth. The interscapular brown adipose tissue was removed on day 42. Littermates were fed a high-fat diet from day 42, and then administered intragastrically with a decoction of medical herbs from day 70. The level of liver energy charge was quantified by HPLC on day 98. A t-test was used to evaluate the difference between the two groups.

RESULTS: Euthyroid rats: Compared with control rats, the level of liver energy charge decreased by 33.0% (P < 0.01) in model rats. The level of liver energy charge in rats consuming a high-fat diet increased by 12.3% (P < 0.01) compared with that in model rats. Compared with rats consuming a high-fat diet, the level of liver energy charge in rats treated with Huanglian-Jiedu Decoction and those with Aconitum Lizhong Pill decreased by 28.1% (P < 0.01) and 44.0% (P < 0.01), respectively. Hypothyroid rats: Compared with control rats, the level of liver energy charge increased by 40.8% (P < 0.01) in model rats. The level of liver energy charge in rats consuming a high-fat diet decreased by 23.8% (P < 0.01) compared with that in model rats. Compared with rats consuming a high-fat diet, the level of liver energy charge in rats treated with Huanglian-Jiedu Decoction and those with Aconitum Lizhong Pill increased by 9.2% (P < 0.01) and decreased by 22.8% (P < 0.01), respectively. The potency of energy charge in hypothyroid rats was lower than that in euthyroid rats (model rats: 11.7%; rats consuming a high-fat diet: 40.1%; Huanglian-Jiedu, 9.0%; Aconitum Lizhong Pill: 17.5%; all P < 0.01).

CONCLUSION: Treatment with Aconitum Lizhong Pill down-regulates liver energy charge in rats with Spleen Yang Deficiency syndrome and thereby exerts thermogenic effects.

Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae

Background

Traditional Chinese Medicine (TCM) is characterized by the wide use of herbal formulae, which are capable of systematically treating diseases determined by interactions among various herbs. However, the combination rule of TCM herbal formulae remains a mystery due to the lack of appropriate methods.

Methods

From a network perspective, we established a method called Distance-based Mutual Information Model (DMIM) to identify useful relationships among herbs in numerous herbal formulae. DMIM combines mutual information entropy and “between-herb-distance” to score herb interactions and construct herb network. To evaluate the efficacy of the DMIM-extracted herb network, we conducted in vitro assays to measure the activities of strongly connected herbs and herb pairs. Moreover, using the networked Liu-wei-di-huang (LWDH) formula as an example, we proposed a novel concept of “co-module” across herb-biomolecule-disease multilayer networks to explore the potential combination mechanism of herbal formulae.

Results

DMIM, when used for retrieving herb pairs, achieves a good balance among the herb’s frequency, independence, and distance in herbal formulae. A herb network constructed by DMIM from 3865 Collaterals-related herbal formulae can not only nicely recover traditionally-defined herb pairs and formulae, but also generate novel anti-angiogenic herb ingredients (e.g. Vitexicarpin with IC50=3.2 μM, and Timosaponin A-III with IC50=3.4 μM) as well as herb pairs with synergistic or antagonistic effects. Based on gene and phenotype information associated with both LWDH herbs and LWDH-treated diseases, we found that LWDH-treated diseases show high phenotype similarity and identified certain “co-modules” enriched in cancer pathways and neuro-endocrine-immune pathways, which may be responsible for the action of treating different diseases by the same LWDH formula.

Conclusions

DMIM is a powerful method to identify the combination rule of herbal formulae and lead to new discoveries. We also provide the first evidence that the co-module across multilayer networks may underlie the combination mechanism of herbal formulae and demonstrate the potential of network biology approaches in the studies of TCM.

Bridging the gap between traditional Chinese medicine and systems biology: the connection of Cold Syndrome and NEI network

Systems biology is a general trend of contemporary scientific development. When coupling the classical traditional Chinese medicine (TCM) Cold Syndrome and methodology of systems biology, we conformed to the genome, transcriptome, proteome, and metabolome that are supposed to run through the overall macro behavior, and explored the macro and micro framework of systems biology of TCM Syndrome. We introduced a new way to probe into the implicit stratification of Cold Syndrome, after surveying 4575 cases of Cold Syndrome patients and examining gene expression information of a typical Cold Syndrome pedigree by microarray. We underlined the genetic background of the Cold Syndrome family based on the molecular foundation to understand Syndrome, one of our earlier discoveries in which genes and chemical compounds in neuro-endocrine-immune (NEI) system are scored as Cold or Hot (or both) property. Results indicate that Cold Syndrome related genes play an essential role in energy metabolism, which are tightly correlated with the genes of neurotransmitters, hormones and cytokines in the NEI interaction network. Therefore, NEI interaction not only opens out mechanism of classical TCM theory on Syndrome but also enriches current research on complex diseases as well as systems biology.

Symptomatic comparison in efficacy on patients with benign prostatic hyperplasia treated with two therapeutic approaches

Objectives

A randomised controlled trial was performed to compare the symptomatic effects on patients with benign prostatic hyperplasia (BPH) treated by two therapeutic approaches – the Western medicine (WM) and traditional Chinese medicine (TCM).

Methods

Four primary outcome measures, namely the quality of life (QOL), maximum urine flow ratio (UFR), International Prostate Symptom Score (IPSS) and prostate volumes, as well as four urethra-related and 35 non-urethra-related symptoms, were investigated to evaluate the effects on 31 BPH patients subjected to WM (Terazosin Hydrochloride Hytrin, THH) and 30 cases to TCM (herbal Saxifrage tablet, HST). The effects of both treatments are compared by the two-sample Kolmogorov–Smirnov test. The contributions of symptoms for four assessments are analysed by the logistic regression model and the Chow test.

Results

The effect of TCM is weaker than that of WM in the assessment of the IPSS score (p < 0.05), and both treatments are similar in the prostate volumes, the maximum UFR and the QOL assessments (p > 0.05), as well as in the effective number of urethra-related or non-urethra-related symptoms before and after treatment (p > 0.05). By comparing the linear regression models, different urethra-related and non-urethra-related symptom patterns associated with TCM and WM therapies are detected for four assessments, especially for the prostate volume assessment (p < 0.01).

Conclusion

TCM (HST) is a potentially effective treatment in improving the QOL, prostate volumes and maximum UFR for patients with BPH, though it is less effective in ameliorating the IPSS score when compared with WM (THH). The non-urethra-related symptoms experienced by BPH patients might be one of the parameters to further achieve the tailored diagnosis and treatment for BPH.

An unsupervised partition method based on association delineated revised mutual information

Background

The syndrome is the basic pathological unit and the key concept in traditional Chinese medicine (TCM) and the herbal remedy is prescribed according to the syndrome a patient catches. Nevertheless, few studies are dedicated to investigate the number of syndromes and what these syndromes are. Correlative measure based on mutual information can measure arbitrary statistical dependences between discrete and continuous variables.

Results

We presented a revised version of mutual information to discriminate positive and negative association. The entropy partition method self-organizedly discovers the effective patterns in patient data and rat data. The super-additivity of cluster by mutual information is proved and N-class association concept is introduced in our model to reduce computational complexity. Validation of the algorithm is performed by using the patient data and its diagnostic data. The partition results of patient data indicate that the algorithm achieves a high sensitivity with 96.48% and each classified pattern is of clinical significance. The partition results of rat data show the inherent relationship between vascular endothelial function related parameters and neuro-endocrine-immune (NEI) network related parameters.

Conclusion

Therefore, we conclude that the algorithm provides an excellent solution to patients and rats data problem in the context of traditional Chinese medicine.

TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

Background

Traditional Chinese Medicine (TCM), a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature.

Methods

TCM, gene, disease, biological pathway and protein-protein interaction information were collected from public databases. For association discovery, the TCM names, gene names, disease names, TCM ingredients and effects were used to annotate the literature corpus obtained from PubMed. The concept to mine entity associations was based on hypothesis testing and collocation analysis. The annotated corpus was processed with natural language processing tools and rule-based approaches were applied to the sentences for extracting the relations between TCM effecters and effects.

Results

We developed a database, TCMGeneDIT, to provide association information about TCMs, genes, diseases, TCM effects and TCM ingredients mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information are also available for exploring the regulations of genes associated with TCM curative effects. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in understanding the possible therapeutic mechanisms of TCMs via gene regulations and deducing synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. The database is now available at .

Conclusion

TCMGeneDIT is a unique database that offers diverse association information on TCMs. This database integrates TCMs with biomedical studies that would facilitate clinical research and elucidate the possible therapeutic mechanisms of TCMs and gene regulations.

Network-based global inference of human disease genes

Deciphering the genetic basis of human diseases is an important goal of biomedical research. On the basis of the assumption that phenotypically similar diseases are caused by functionally related genes, we propose a computational framework that integrates human protein–protein interactions, disease phenotype similarities, and known gene–phenotype associations to capture the complex relationships between phenotypes and genotypes. We develop a tool named CIPHER to predict and prioritize disease genes, and we show that the global concordance between the human protein network and the phenotype network reliably predicts disease genes. Our method is applicable to genetically uncharacterized phenotypes, effective in the genome-wide scan of disease genes, and also extendable to explore gene cooperativity in complex diseases. The predicted genetic landscape of over 1000 human phenotypes, which reveals the global modular organization of phenotype–genotype relationships. The genome-wide prioritization of candidate genes for over 5000 human phenotypes, including those with under-characterized disease loci or even those lacking known association, is publicly released to facilitate future discovery of disease genes.

Integrative mining of traditional Chinese medicine literature and MEDLINE for functional gene networks

OBJECTIVE

The amount of biomedical data in different disciplines is growing at an exponential rate. Integrating these significant knowledge sources to generate novel hypotheses for systems biology research is difficult. Traditional Chinese medicine (TCM) is a completely different discipline, and is a complementary knowledge system to modern biomedical science. This paper uses a significant TCM bibliographic literature database in China, together with MEDLINE, to help discover novel gene functional knowledge.

MATERIALS AND METHODS

We present an integrative mining approach to uncover the functional gene relationships from MEDLINE and TCM bibliographic literature. This paper introduces TCM literature (about 50,000 records) as one knowledge source for constructing literature-based gene networks. We use the TCM diagnosis, TCM syndrome, to automatically congregate the related genes. The syndrome-gene relationships are discovered based on the syndrome-disease relationships extracted from TCM literature and the disease-gene relationships in MEDLINE. Based on the bubble-bootstrapping and relation weight computing methods, we have developed a prototype system called MeDisco/3S, which has name entity and relation extraction, and online analytical processing (OLAP) capabilities, to perform the integrative mining process.

RESULTS

We have got about 200,000 syndrome-gene relations, which could help generate syndrome-based gene networks, and help analyze the functional knowledge of genes from syndrome perspective. We take the gene network of Kidney-Yang Deficiency syndrome (KYD syndrome) and the functional analysis of some genes, such as CRH (corticotropin releasing hormone), PTH (parathyroid hormone), PRL (prolactin), BRCA1 (breast cancer 1, early onset) and BRCA2 (breast cancer 2, early onset), to demonstrate the preliminary results. The underlying hypothesis is that the related genes of the same syndrome will have some biological functional relationships, and will constitute a functional network.

CONCLUSION

This paper presents an approach to integrate TCM literature and modern biomedical data to discover novel gene networks and functional knowledge of genes. The preliminary results show that the novel gene functional knowledge and gene networks, which are worthy of further investigation, could be generated by integrating the two complementary biomedical data sources. It will be a promising research field through integrative mining of TCM and modern life science literature.