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

Standardization, objectification, and essence research of traditional Chinese medicine syndrome: A 15-year bibliometric and content analysis from 2006 to 2020 in Web of Science database

The standardization, objectification, and essence research of traditional Chinese medicine (TCM) syndrome influence the modernization and international development of TCM syndrome. A total of 253 relevant publications collected from the Web of Science Core Collection database from 2006 to 2020 were analyzed by bibliometric and content methods. The co-occurrence analysis of countries, institutions, journals, authors, and keywords analysis were carried out by using Citespace software. The high-yield institutions and high-impact authors contributed to TCM syndrome publications were concentrated in China. Since 2012, driven by some groundbreaking publications, the number of TCM syndrome literatures has increased rapidly. According to the results of bibliometric and content analysis, research hotspots in TCM syndrome in the last 15 years can be summarized in six aspects: (a) objectification research of four TCM diagnostic methods, (b) omics technology for the essence research of TCM syndrome, (c) research on TCM syndrome evaluation scale, (d) metagenomic technology for the essence research of TCM syndrome, (e) data mining technology for TCM syndrome differentiation, and (f) systematic research on TCM syndromes of chronic hepatitis B. Emerging trends can be identified according to the most recent keywords bursts: (a) TCM syndrome diagnostic models with multiple indexes should be constructed to develop personalized medicine. (b) The connotation of TCM syndrome should be verified through "syndrome detecting from recipe used," and the screened potential markers of TCM syndrome need clinical verification. (c) The intervention and integration of multi-disciplines is expected to find a new breakthrough in the research of TCM syndrome.

Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing

Objectives

The aim of this study is to interpret a quantitative diagnosis model of traditional Chinese medicine (TCM) syndromes based on computer adaptive testing (CAT), from the perspective of both patients and clinicians.

Methods

In this cross-sectional study, patients with postprandial distress syndrome completed the CAT model of TCM syndromes and the Chinese version of the Quality of Life Questionnaire for Functional Digestive Disorders (Chin-FDDQL); the clinicians' diagnosis was concurrently recorded. The patients completed this questionnaire again after 14 ± 2 days. The kappa test and paired chi-square test were used to evaluate the consistency between the CAT model and clinical diagnosis. Minimal clinically important differences (MCID) of the Chin-FDDQL scores were used to assess clinical efficacy from the patients' perspective. Logistic regression was used to examine the association between changes in the CAT model syndrome domain scores and changes in clinical outcomes.

Results

Changes in the CAT model syndrome domain scores may affect the clinical outcomes of patients with the total scores of Chin-FDDQL (all P < 0.05). There was a correlation between changes in the CAT model syndrome domain scores and the patients' clinical outcomes. Different syndrome elements had different effects on various Chin-FDDQL domains, which was consistent with the theory of TCM.

Conclusions

This study proposes a method for the clinical interpretation of the CAT model of TCM syndromes, including evidence derived from the application. It may provide a reference for future interpretation of other CAT models.

The effect of compound kushen injection on cancer cells: Integrated identification of candidate molecular mechanisms

Traditional Chinese Medicine (TCM) preparations are often extracts of single or multiple herbs containing hundreds of compounds, and hence it has been difficult to study their mechanisms of action. Compound Kushen Injection (CKI) is a complex mixture of compounds extracted from two medicinal plants and has been used in Chinese hospitals to treat cancer for over twenty years. To demonstrate that a systematic analysis of molecular changes resulting from complex mixtures of bioactives from TCM can identify a core set of differentially expressed (DE) genes and a reproducible set of candidate pathways. We used in vitro cancer models to measure the effect of CKI on cell cycle phases and apoptosis, and correlated those phenotypes with CKI induced changes in gene expression. We treated two cancer cell lines with or without CKI and assessed the resulting phenotypes by employing cell viability and proliferation assays. Based on these results, we carried out high-throughput transcriptome data analysis to identify genes and candidate pathways perturbed by CKI. We integrated these differential gene expression results with previously reported results and carried out validation of selected differentially expressed genes. CKI induced cell-cycle arrest and apoptosis in the cancer cell lines tested. In these cells CKI also altered the expression of 363 core candidate genes associated with cell cycle, apoptosis, DNA replication/repair, and various cancer pathways. Of these, 7 are clinically relevant to cancer diagnosis or therapy, 14 are cell cycle regulators, and most of these 21 candidates are downregulated by CKI. Comparison of our core candidate genes to a database of plant medicinal compounds and their effects on gene expression identified one-to-one, one-to-many and many-to-many regulatory relationships between compounds in CKI and DE genes. By identifying genes and promising candidate pathways associated with CKI treatment based on our transcriptome-based analysis, we have shown that this approach is useful for the systematic analysis of molecular changes resulting from complex mixtures of bioactives.

Metabolic mechanisms of Fuzheng-Huayu formula against liver fibrosis in rats

ETHNOPHARMACOLOGICAL RELEVANCE

Fuzheng-Huayu formula (FZHY) is traditionally used to treat liver fibrosis in clinic. The study was conducted to investigate the metabolic mechanisms of FZHY against liver fibrosis in rats.

MATERIALS AND METHODS

Rats with CCl₄ -induced liver fibrosis were treated with FZHY and its components, including amygdalin, cordyceps polysaccharide and gypenoside, respecitively. Liver fibrosis and function were assesed by histopathological examination, Western blot and serum biochemical detection. Metabolic profiling of liver tissue, serum and urine in each group were detected by gas chromatography-mass spectrometry (GC-MS) and transcriptomic changes were tested by gene chip. RT-qPCR was used to validate levels of different expressed genes (DEGs) with statistical significance. Metabolic network together with DEGs was constructed based on KEGG database.

RESULTS

FZHY effectively improved liver fibrosis better than the mixture or single use of gypenoside, cordyceps sinensis mycelia and amygdalin. FZHY treatment widely modulated the metabolic profiles perturbed by liver fibrosis, involving several important metabolic pathways, including glycolysis/gluconeogenesis, glucose-alanine cycle, citrate cycle, galactose metabolism, tryptophan metabolism, urea cycle, etc. It also increased alanine and decreased glucose levels in liver tissue and decreased both of them in serum and urine, which were dysregulated by CCl₄ treatment. Additionally, FZHY also upregulated expression of metabolic enzymes including Hk2, Adh1 and Gpt increased, and downregulated Gs and Acss2.

CONCLUSION

FZHY improved liver fibrosis in rats via altering the metabolic pathways and regulating gene expression of involved metabolic enzymes.

Understanding Chinese Medicine Patterns of Rheumatoid Arthritis and Related Biomarkers

Background: A considerable number of Rheumatoid Arthritis (RA) patients only experience side effects from treatment, with little to no actual pain relief. The combination of disease diagnosis in biomedicine and multi-disciplinary integrative approaches such as Chinese Medicine (CM), can help to identify different functional diagnosis of RA in the context of biomarker discovery. We aimed to analyse CM patterns in RA and their biomarker profiles. Methods: Four electronic databases (web of science, CINAHL, Scopus and PubMed) were searched. The reference list of all identified reports and articles were searched for additional studies. All study designs were included and no date limits were set. Studies were considered if they were published in English and explored the possible biomarkers profiles in RA patients, classified according to the American College of Rheumatology and categorized in CM as either cold, heat/hot or deficiency patterns. Methodological quality of included studies was assessed using checklists adapted from the ©Critical Appraisal Skills Programme by two independent reviewers. A narrative synthesis was conducted, using thematic analysis. Results: A total of 10 articles were included. The studies examined 77 healthy volunteers and 1150 RA patients categorized as cold, heat/hot or deficiency pattern and related biomarkers were identified individually or concomitantly. Conclusions: CM pattern differentiation based on clinical signs and symptoms showed a diverse range of biomolecules, proteins and genes from RA patients correlated well with cold, heat/hot or deficiency phenotype-based CM patterns and could be used as diagnostic biomarkers for early detection, disease monitoring and therapeutic targets.

Differential gene expression profiles between two subtypes of ischemic stroke with blood stasis syndromes

Ischemic stroke is a cerebrovascular thrombotic disease with high morbidity and mortality. Qi deficiency blood stasis (QDBS) and Yin deficiency blood stasis (YDBS) are the two major subtypes of ischemic stroke according to the theories of traditional Chinese medicine. This study was conducted to distinguish these two syndromes at transcriptomics level and explore the underlying mechanisms. Male rats were randomly divided into three groups: sham group, QDBS/MCAO group and YDBS/MCAO group. Morphological changes were assessed after 24 h of reperfusion. Microarray analysis with circulating mRNA was then performed to identify differential gene expression profile, gene ontology and pathway enrichment analyses were carried out to predict the gene function, gene co-expression and pathway networks were constructed to identify the hub biomarkers, which were further validated by western blotting and Tunel staining analysis. Three subsets of dysregulated genes were acquired, including 445 QDBS-specific genes, 490 YDBS-specific genes and 1676 blood stasis common genes. Our work reveals for the first time that T cell receptor, MAPK and apoptosis pathway were identified as the hub pathways based on the pathway networks, while Nfκb1, Egfr and Casp3 were recognized as the hub genes by co-expression networks. This research helps contribute to a clearer understanding of the pathological characteristics of ischemic stroke with QDBS and YDBS syndrome, the proposed biomarkers might provide insight into the accurate diagnose and proper treatment for ischemic stroke with blood stasis syndrome.

Quantitative Serum Proteomic Analysis of Essential Hypertension Using iTRAQ Technique

Essential hypertension (EH) is a risk factor for some severe diseases. This study aimed to screen out serum special proteins and seek interaction between them, which would provide new therapeutic targets and elucidate the comprehensive pathophysiological mechanism for EH. Patients with EH (Group A, n = 47) and healthy controls (HC) (Group B, n = 47) were recruited in this study. Serums from the two groups were analyzed with isobaric tags for relative and absolute quantitation coupled two-dimensional liquid chromatography followed by electrospray ionization-tandem mass spectrometry technique, while the candidate special proteins were verified with ELISA and western blot. A total of 404 proteins were identified, of which 30 proteins were upregulated (>1.2-fold, p < 0.05) and 81 proteins were downregulated (<0.833-fold, p < 0.05) compared with HC group. With GO, KEGG analysis, and literature retrieval, 4 proteins, cathepsin G, transforming growth factor beta-1, hyaluronidase-1, and kininogen-1, were found jointly involved in the renin-angiotensin-aldosterone system and kallikrein-kinin system. The profiles of these 4 candidate proteins were confirmed with ELISA and western blot. The concentration variation of these 4 proteins could better predict the occurrence and illustrate the pathophysiological mechanism of EH. And their discovery may help pave the way for exploring new therapies of EH.

Plasma Metabolomics Analysis Based on GC-MS in Infertile Males with Kidney-Yang Deficiency Syndrome

Introduction

Chinese medicine syndrome diagnosis is the key requisite in the treatment of male infertility with traditional Chinese medicine (TCM). Kidney-Yang deficiency syndrome (KYDS) is the critical Chinese medicine syndrome of male infertility. To explore the modernized mechanisms of KYDS in male infertility, this study aims to investigate the metabolomics of males with KYDS.

Methods

The gas chromatography-mass spectrometry method was applied to analyze the plasma samples of 67 infertile males with KYDS compared with 55 age-matched healthy controls. The chemometric methods including principal component and partial least squares-discriminate analyses were employed to identify the potential biochemical patterns. With the help of the variable importance for the projection and receiver operating characteristic curve analyses, the potential biomarkers were extracted to define the clinical utility. Simultaneously the high-quality KEGG metabolic pathways database was used to identify the related metabolic pathways.

Results

The metabolomics profiles of infertile males with KYDS including 10 potential biomarkers and six metabolic pathways were identified. They precisely distinguished infertile males with KYDS from healthy controls.

Conclusions

These potential biomarkers and pathways suggest the substantial basis of infertile males with KYDS. The metabolomics profiles highlight the modernized mechanisms of infertile males with KYDS.

The Use of Omic Technologies Applied to Traditional Chinese Medicine Research

Natural products represent one of the most important reservoirs of structural and chemical diversity for the generation of leads in the drug development process. A growing number of researchers have shown interest in the development of drugs based on Chinese herbs. In this review, the use and potential of omic technologies as powerful tools in the modernization of traditional Chinese medicine are discussed. The analytical combination from each omic approach is crucial for understanding the working mechanisms of cells, tissues, organs, and organisms as well as the mechanisms of disease. Gradually, omic approaches have been introduced in every stage of the drug development process to generate high-quality Chinese medicine-based drugs. Finally, the future picture of the use of omic technologies is a promising tool and arena for further improvement in the modernization of traditional Chinese medicine.

Current Status of Herbal Medicines in Chronic Liver Disease Therapy: The Biological Effects, Molecular Targets and Future Prospects

Chronic liver dysfunction or injury is a serious health problem worldwide. Chronic liver disease involves a wide range of liver pathologies that include fatty liver, hepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. The efficiency of current synthetic agents in treating chronic liver disease is not satisfactory and they have undesirable side effects. Thereby, numerous medicinal herbs and phytochemicals have been investigated as complementary and alternative treatments for chronic liver diseases. Since some herbal products have already been used for the management of liver diseases in some countries or regions, a systematic review on these herbal medicines for chronic liver disease is urgently needed. Herein, we conducted a review describing the potential role, pharmacological studies and molecular mechanisms of several commonly used medicinal herbs and phytochemicals for chronic liver diseases treatment. Their potential toxicity and side effects were also discussed. Several herbal formulae and their biological effects in chronic liver disease treatment as well as the underlying molecular mechanisms are also summarized in this paper. This review article is a comprehensive and systematic analysis of our current knowledge of the conventional medicinal herbs and phytochemicals in treating chronic liver diseases and on the potential pitfalls which need to be addressed in future study.

Metabolomics analysis of seminal plasma in infertile males with kidney-yang deficiency: a preliminary study

Traditional Chinese medicine (TCM) is an important treatment for male infertility, and its application to therapy is dependent on differentiation of TCM syndromes. This study aims to investigate the changes in metabolites and metabolic pathways in infertile males with Kidney-Yang Deficiency syndrome (KYDS) via metabolomics approaches. Seminal plasma samples were collected from 18 infertile males with KYDS and 18 fertile males. Liquid chromatography and mass spectrometry were used to characterize metabolomics profiles. Principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA), and pathway analysis were used for pattern recognition and metabolite identification. PCA and PLS-DA results differentiated the two groups of patients. Forty-one discriminating metabolites (18 in positive mode and 23 in negative mode) were identified. Seven metabolites were related to five potential metabolic pathways associated with biosynthesis and metabolism of aromatic amino acids, tricarboxylic acid cycle, and sphingolipid metabolism. The changes in metabolic pathways may play an important role in the origin of KYDS-associated male infertility. Metabolomics analysis of seminal plasma may be used to differentiate TCM syndromes of infertile males, but further research must be conducted.

Standardization and future directions in pattern identification research: International brainstorming session

An international brainstorming session on standardizing pattern identification (PI) was held at the Korea Institute of Oriental Medicine on October 1, 2013 in Daejeon, South Korea. This brainstorming session was convened to gather insights from international traditional East Asian medicine specialists regarding PI standardization. With eight presentations and discussion sessions, the meeting allowed participants to discuss research methods and diagnostic systems used in traditional medicine for PI. One speaker presented a talk titled "The diagnostic criteria for blood stasis syndrome: implications for standardization of PI". Four speakers presented on future strategies and objective measurement tools that could be used in PI research. Later, participants shared information and methodology for accurate diagnosis and PI. They also discussed the necessity for standardizing PI and methods for international collaborations in pattern research.

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.

Reliable multi-label learning via conformal predictor and random forest for syndrome differentiation of chronic fatigue in traditional Chinese medicine

OBJECTIVE

Chronic Fatigue (CF) still remains unclear about its etiology, pathophysiology, nomenclature and diagnostic criteria in the medical community. Traditional Chinese medicine (TCM) adopts a unique diagnostic method, namely 'bian zheng lun zhi' or syndrome differentiation, to diagnose the CF with a set of syndrome factors, which can be regarded as the Multi-Label Learning (MLL) problem in the machine learning literature. To obtain an effective and reliable diagnostic tool, we use Conformal Predictor (CP), Random Forest (RF) and Problem Transformation method (PT) for the syndrome differentiation of CF.

METHODS AND MATERIALS

In this work, using PT method, CP-RF is extended to handle MLL problem. CP-RF applies RF to measure the confidence level (p-value) of each label being the true label, and then selects multiple labels whose p-values are larger than the pre-defined significance level as the region prediction. In this paper, we compare the proposed CP-RF with typical CP-NBC(Naïve Bayes Classifier), CP-KNN(K-Nearest Neighbors) and ML-KNN on CF dataset, which consists of 736 cases. Specifically, 95 symptoms are used to identify CF, and four syndrome factors are employed in the syndrome differentiation, including 'spleen deficiency', 'heart deficiency', 'liver stagnation' and 'qi deficiency'.

THE RESULTS

CP-RF demonstrates an outstanding performance beyond CP-NBC, CP-KNN and ML-KNN under the general metrics of subset accuracy, hamming loss, one-error, coverage, ranking loss and average precision. Furthermore, the performance of CP-RF remains steady at the large scale of confidence levels from 80% to 100%, which indicates its robustness to the threshold determination. In addition, the confidence evaluation provided by CP is valid and well-calibrated.

CONCLUSION

CP-RF not only offers outstanding performance but also provides valid confidence evaluation for the CF syndrome differentiation. It would be well applicable to TCM practitioners and facilitate the utilities of objective, effective and reliable computer-based diagnosis tool.