Exploring biological basis of Syndrome differentiation in coronary heart disease patients with two distinct Syndromes by integrated multi-omics and network pharmacology strategy

Exploiting omic-based approaches to decipher Traditional Chinese Medicine

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese Medicine (TCM), an ancient health system, faces significant research challenges due to the complexity of its active components and targets, as well as a historical lack of detailed annotation. However, recent advances in omics technologies have begun to unravel these complexities, providing a more informed and nuanced understanding of TCM's therapeutic potential in contemporary healthcare.

AIM OF THE REVIEW

This review summarizes the application of omics technologies in TCM modernization, emphasizing components analysis, quality control, biomarker discovery, target identification, and treatment optimization. In addition, future perspectives on using omics for precision TCM treatment are also discussed.

MATERIALS AND METHODS

We have explored several databases (including PubMed, ClinicalTrials, Google Scholar, and Web of Science) to review related articles, focusing on Traditional Chinese Medicine, Omics Strategy, Precision Medicine, Biomarkers, Quality Control, and Molecular Mechanisms. Paper selection criteria involved English grammar, publication date, high citations, and broad applicability, exclusion criteria included low credibility, non-English publications, and those full-text inaccessible ones.

RESULTS

TCM and the popularity of Chinese herbal medicines (CHMs) are gaining increasing attention worldwide. This is driven, in part, by a large number of technologies, especially omics strategy, which are aiding the modernization of TCM. They contribute to the quality control of CHMs, the identification of cellular targets, discovery of new drugs and, most importantly, the understanding of their mechanisms of action.

CONCLUSION

To fully integrate TCM into modern medicine, further development of robust omics strategies is essential. This vision includes personalized medicine, backed by advanced computational power and secure data infrastructure, to facilitate global acceptance and seamless integration of TCM practices.

The interactions and biological pathways among metabolomics products of patients with coronary heart disease

BACKGROUND

Through bioinformatics analysis, this study explores the interactions and biological pathways involving metabolomic products in patients diagnosed with coronary heart disease (CHD).

METHODS

A comprehensive search for relevant studies focusing on metabolomics analysis in CHD patients was conducted across databases including CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, Nature, Web of Science, Springer, and Science Direct. Metabolites reported in the literature underwent statistical analysis and summarization, with the identification of differential metabolites. The pathways associated with these metabolites were examined using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Molecular annotation of metabolites and their relationships with enzymes or transporters were elucidated through analysis with the Human Metabolome Database (HMDB). Visual representation of the properties related to these metabolites was achieved using Metabolomics Pathway Analysis (metPA).

RESULTS

A total of 13 literatures satisfying the criteria for enrollment were included. A total of 91 metabolites related to CHD were preliminarily screened, and 87 effective metabolites were obtained after the unrecognized metabolites were excluded. A total of 45 pathways were involved. Through the topology analysis (TPA) of pathways, their influence values were calculated, and 13 major metabolic pathways were selected. The pathways such as Phenylalanine, tyrosine, and tryptophan biosynthesis, Citrate cycle (TCA cycle), Glyoxylate and dicarboxylate metabolism, and Glycine, serine, and threonine metabolism primarily involved the regulation of processes and metabolites related to inflammation, oxidative stress, one-carbon metabolism, energy metabolism, lipid metabolism, immune regulation, and nitric oxide expression.

CONCLUSION

Multiple pathways, including Phenylalanine, tyrosine, and tryptophan biosynthesis, Citrate cycle (TCA cycle), Glyoxylate and dicarboxylate metabolism, and Glycine, serine, and threonine metabolism, were involved in the occurrence of CHD. The occurrence of CHD is primarily associated with the regulation of processes and metabolites related to inflammation, oxidative stress, one-carbon metabolism, energy metabolism, lipid metabolism, immune regulation, and nitric oxide expression.

Proteomic advance of ischemic stroke: preclinical, clinical, and intervention

Ischemic stroke (IS) is the most common type of stroke and is characterized by high rates of mortality and long-term injury. The prediction and early diagnosis of IS are therefore crucial for optimal clinical intervention. Proteomics has provided important techniques for exploring protein markers associated with IS, but there has been no systematic evaluation and review of research that has used these techniques. Here, we review the differential proteins that have been found in cell- and animal- based studies and clinical trials of IS in the past 10 years; determine the key pathological proteins that have been identified in clinical trials; summarize the target proteins affected by interventions aimed at treating IS, with a focus on traditional Chinese medicine treatments. Overall, we clarify findings and problems that have been identified in recent proteomics research on IS and provide suggestions for improvements in this area. We also suggest areas that could be explored for determining the pathogenesis and developing interventions for IS.

Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review

The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.

Network pharmacology: a bright guiding light on the way to explore the personalized precise medication of traditional Chinese medicine

Network pharmacology can ascertain the therapeutic mechanism of drugs for treating diseases at the level of biological targets and pathways. The effective mechanism study of traditional Chinese medicine (TCM) characterized by multi-component, multi-targeted, and integrative efficacy, perfectly corresponds to the application of network pharmacology. Currently, network pharmacology has been widely utilized to clarify the mechanism of the physiological activity of TCM. In this review, we comprehensively summarize the application of network pharmacology in TCM to reveal its potential of verifying the phenotype and underlying causes of diseases, realizing the personalized and accurate application of TCM. We searched the literature using "TCM network pharmacology" and "network pharmacology" as keywords from Web of Science, PubMed, Google Scholar, as well as Chinese National Knowledge Infrastructure in the last decade. The origins, development, and application of network pharmacology are closely correlated with the study of TCM which has been applied in China for thousands of years. Network pharmacology and TCM have the same core idea and promote each other. A well-defined research strategy for network pharmacology has been utilized in several aspects of TCM research, including the elucidation of the biological basis of diseases and syndromes, the prediction of TCM targets, the screening of TCM active compounds, and the decipherment of mechanisms of TCM in treating diseases. However, several factors limit its application, such as the selection of databases and algorithms, the unstable quality of the research results, and the lack of standardization. This review aims to provide references and ideas for the research of TCM and to encourage the personalized and precise use of Chinese medicine.

Improving the Data Quality of Untargeted Metabolomics through a Targeted Data-Dependent Acquisition Based on an Inclusion List of Differential and Preidentified Ions

Metabolomics based on high-resolution mass spectrometry has become a powerful technique in biomedical research. The development of various analytical tools and online libraries has promoted the identification of biomarkers. However, how to make mass spectrometry collect more data information is an important but underestimated research topic. Herein, we combined full-scan and data-dependent acquisition (DDA) modes to develop a new targeted DDA based on the inclusion list of differential and preidentified ions (dpDDA). In this workflow, the MS1 datasets for statistical analysis and metabolite preidentification were first obtained using full-scan, and then, the MS/MS datasets for metabolite identification were obtained using targeted DDA of quality control samples based on the inclusion list. Compared with the current methods (DDA, data-independent acquisition, targeted DDA with time-staggered precursor ion list, and iterative exclusion DDA), dpDDA showed better stability, higher characteristic ion coverage, higher differential metabolites' MS/MS coverage, and higher quality MS/MS spectra. Moreover, the same trend was verified in the analysis of large-scale clinical samples. More surprisingly, dpDDA can distinguish patients with different severities of coronary heart disease (CHD) based on the Canadian Cardiovascular Society angina classification, which we cannot distinguish through conventional metabolomics data collection. Finally, dpDDA was employed to differentiate CHD from healthy control, and targeted metabolomics confirmed that dpDDA could identify a more complete metabolic pathway network. At the same time, four unreported potential CHD biomarkers were identified, and the area under the receiver operating characteristic curve was greater than 0.85. These results showed that dpDDA would expand the discovery of biomarkers based on metabolomics, more comprehensively explore the key metabolites and their association with diseases, and promote the development of precision medicine.

Differentiation in TCM patterns of chronic obstructive pulmonary disease by comprehensive metabolomic and lipidomic characterization

Introduction

Chronic obstructive pulmonary disease (COPD) is a complex disease involving inflammation, cell senescence, and autoimmunity. Dialectical treatment for COPD with traditional Chinese medicine (TCM) has the advantage of fewer side effects, more effective suppression of inflammation, and improved immune function. However, the biological base of TCM pattern differentiation in COPD remains unclear.

Methods

Liquid Chromatography-Quadrupole-Orbitrap mass spectrometry (LC-Q-Orbitrap MS/MS) based metabolomics and lipidomics were used to analyze the serum samples from COPD patients of three TCM patterns in Lung Qi Deficiency (n=65), Lung-Kidney Qi Deficiency (n=54), Lung-Spleen Qi Deficiency (n=52), and healthy subjects (n=41). Three cross-comparisons were performed to characterize metabolic markers for different TCM patterns of COPD vs healthy subjects.

Results

We identified 28, 8, and 16 metabolites with differential abundance between three TCM patterns of COPD vs healthy subjects, respectively, the metabolic markers included cortisol, hypoxanthine, fatty acids, alkyl-/alkenyl-substituted phosphatidylethanolamine, and phosphatidylcholine, etc. Three panels of metabolic biomarkers specific to the above three TCM patterns yielded areas under the receiver operating characteristic curve of 0.992, 0.881, and 0.928, respectively, with sensitivity of 97.1%, 88.6%, and 91.4%, respectively, and specificity of 96.4%, 81.8%, and 83.9%, respectively.

Discussion

Combining metabolomics and lipidomics can more comprehensively and accurately trace metabolic markers. As a result, the differences in metabolism were proven to underlie different TCM patterns of COPD, which provided evidence to aid our understanding of the biological basis of dialectical treatment, and can also serve as biomarkers for more accurate diagnosis.

Integrative network fusion-based multi-omics study for biomarker identification and patient classification of rheumatoid arthritis

BACKGROUND

Cold-dampness Syndrome (RA-Cold) and Hot-dampness Syndrome (RA-Hot) are two distinct groups of rheumatoid arthritis (RA) patients with different clinical symptoms based on traditional Chinese medicine (TCM) theories and clinical empirical knowledge. However, the biological basis of the two syndromes has not been fully elucidated, which may restrict the development of personalized medicine and drug discovery for RA diagnosis and therapy.

METHODS

An integrative strategy combining clinical transcriptomics, phenomics, and metabolomics data based on clinical cohorts and adjuvant-induced arthritis rat models was performed to identify novel candidate biomarkers and to investigate the biological basis of RA-Cold and RA-Hot.

RESULTS

The main clinical symptoms of RA-Cold patients are joint swelling, pain, and contracture, which may be associated with the dysregulation of T cell-mediated immunity, osteoblast differentiation, and subsequent disorders of steroid biosynthesis and phenylalanine metabolism. In contrast, the main clinical symptoms of RA-Hot patients are fever, irritability, and vertigo, which may be associated with various signals regulating angiogenesis, adrenocorticotropic hormone release, and NLRP3 inflammasome activation, leading to disorders of steroid biosynthesis, nicotinamide, and sphingolipid metabolism. IL17F, 5-HT, and IL4I1 were identified as candidate biomarkers of RA-Cold, while S1P and GLNS were identified as candidate biomarkers of RA-Hot.

CONCLUSIONS

The current study presents the most comprehensive metabonomic and transcriptomic profiling of serum, urine, synovial fluid, and synovial tissue samples obtained from RA-Cold and RA-Hot patients and experimental animal models to date. Through the integration of multi-omics data and clinical independent validation, a list of novel candidate biomarkers of RA-Cold and RA-Hot syndromes were identified, that may be useful in improving RA diagnosis and therapy.

Plantamajoside alleviates hypoxia-reoxygenation injury through integrin-linked kinase/c-Src/Akt and the mitochondrial apoptosis signaling pathways in H9c2 myocardial cells

Myocardial ischemia-reperfusion injury(MIRI) is one of the common complications after myocardial infarction surgery, Oxidative stress is among the main mechanisms of myocardial ischemia-reperfusion injury. Plantamajoside (PMS), the main effective ingredient in the genus Plantain, has been reported to possess an antioxidation, anti-inflammatory and anti-apoptosis role. However, whether PMS can attenuate myocardial ischemia-reperfusion injury is not yet known. Herein, we explored the effects of PMS on hypoxia-reoxygenation (H/R) injury in H9c2 cardiomyocytes and the underling molecular mechanisms of the treatment. Network pharmacological analysis screened the top 31 key genes in the treatment of MIRI disease treated with PMS, and the result of molecular docking further illustrated the roles that the PMS play in the treatment of MIRI through its interference with integrin-linked kinase (ILK) target protein. PMS was not cytotoxic in the concentration range of 5-40 μM and increased cell survival after H/R injury in a concentration-dependent manner without affecting proliferation or growth. PMS significantly reduced the levels of lactate dehydrogenase, malonic dialdehyde, reactive oxygen species and cell apoptosis, and increased soperoxide dismutase activity compared with those of the H/R injury group. PMS promoted the protein and mRNA expression of ILK and Bcl-2, the protein expression of p-Akt, and reduced the protein and mRNA expression of Bax, Caspase-3, and Cytochrome c, the protein expression of p-c-Src. PMS has protective effects against H/R injury in H9c2 cells, and its protective mechanism may be related to reactive oxygen species clearance, activation of the ILK/c-Src/Akt pathway and inhibition of the mitochondrial apoptosis.

Different software processing affects the peak picking and metabolic pathway recognition of metabolomics data

In untargeted liquid chromatography‒mass spectrometry (LC‒MS) metabolomics studies, data preprocessing and metabolic pathway recognition are crucial for screening important pathways that are disturbed by diseases or restored by drugs. Here, we collected high-resolution mass spectrometry data of serum samples from 221 coronary heart disease (CHD) patients under two different chromatographic columns (BEH amide and C₁₈ column) and evaluated the three commonly used software programs (XCMS, Progenesis QI, MarkerView) from four aspects (including signal drift, peak number, metabolite annotation and metabolic pathway enrichment). The results showed that the data preprocessed by the three software programs have different degrees of signal drift, but the StatTarget could improve the data quality to meet the data analysis requirement after correction. In addition, XCMS surpassed other software in detection of real chromatographic peaks and Progenesis QI was the best performer in terms of the number of metabolite annotation. XCMS and Progenesis QI showed different performance in pathway enrichment. However, metabolic pathways based on the combination of XCMS and Progenesis QI had a high coincidence with Progenesis QI. In addition, we also reported that C₁₈ and amide columns were highly complementary and have great potential for cooperation in the context of metabolic pathways. In this study, the effects of different chromatographic columns and software pretreatments on metabolomics data were evaluated based on clinical large cohort samples, which will provide a reference for the metabolomics of clinical samples and guide subsequent mechanistic research.

Altered serum metabolome associated with vascular calcification developed from CKD and the critical pathways

Introduction

Vascular calcification (VC) is more likely to be detected in the chronic kidney disease (CKD) population. The mechanism of VC development from CKD is different from that for simple VC and has always been a major research area. The aim of this study was to detect alterations in the metabolome during development of VC in CKD and to identify the critical metabolic pathways and metabolites involved in its pathogenesis.

Methods

Rats in the model group were given an adenine gavage combined with a high-phosphorus diet to imitate VC in CKD. The aorta calcium content was measured and used to divide the model group into a VC group and non-vascular calcification group (non-VC group). The control group was fed a normal rat diet and given a saline gavage. Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) was used to determine the altered serum metabolome in the control, VC, and non-VC groups. The identified metabolites were mapped into the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (https://www.genome.jp/kegg/) for pathway and network analyses.

Result

There were 14 metabolites that changed significantly in the VC group, with three metabolic pathways playing critical roles in the pathogenesis of VC in CKD: steroid hormone biosynthesis; valine, leucine and isoleucine biosynthesis; and pantothenate and CoA biosynthesis.

Conclusion

Our results indicated changes in the expression of steroid sulfatase and estrogen sulfotransferase, and down-regulation of the in situ synthesis of estrogens in the VC group. In conclusion, the serum metabolome alters significantly during the pathogenesis of VC in CKD. The key pathways, metabolites, and enzymes we identified are worth further study and may become a promising therapeutic target for the treatment of VC in CKD.

Efficacy and safety of anti-obesity herbal medicine focused on pattern identification: A systematic review and meta-analysis

BACKGROUND

Herbal medicine based on pattern identification (PI) is used widely in Traditional Chinese Medicine. Proper herbal medicine based on PI has been suggested for effective weight reduction and decreasing the adverse events. This systematic review examined the effectiveness and safety of herbal medicine, focusing on PI in treating obesity.

METHODS

Eight electric databases were used for searching randomized controlled trials (RCT) (to August 31, 2021). RCTs which prescribed herbal medicine to obese patients based on PI were included. Body weight (BW) and body mass index (BMI) were the primary outcomes. The risk of bias was assessed using Cochrane risk of bias tool, and the meta-analysis was conducted. Grading the evidence was conducted by using GRADEpro.

RESULTS

Sixteen RCTs (1052 patients) were included: 2 studies compared herbal medicine to placebo (128 patients); 2 studies compared them to western medication (161 patients); 12 studies compared them with usual care (763 patients). The meta-analysis showed that the herbal formulas reduced the BW and BMI without significant Adverse events compared to the control group (BW: mean difference  = -4.10, 95% confidence interval: -5.14 to -3.06, I2 = 2% and BMI: mean difference = -1.53, 95% confidence interval: -1.88 to -1.19, I2 = 25%). Moderate-quality evidence on the primary outcomes was found.

CONCLUSIONS

Herbal medicine - has good clinical efficacy and safety in treating obesity. This study has limitations that some literatures with high risk of bias in blinding or without using a standardized diagnosis of PI were included. However, the current evidence suggests the possibility of precision medicine using PI.

Exploring the "gene-protein-metabolite" network of coronary heart disease with phlegm and blood stasis syndrome by integrated multi-omics strategy

Background: According to the theory of traditional Chinese medicine, phlegm and blood stasis (PBS) is the pathological basis for coronary heart disease (CHD). This study aimed to explore the biological basis of PBS syndrome in CHD. Methods: Using a strategy that integrated RNA-seq, DIA-based proteomics, and untargeted metabolomics on 90 clinic samples, we constructed a "gene-protein-metabolite" network for CHD-PBS syndrome. We expanded the sample size and validated the differential genes and metabolites in the network through enzyme-linked immunosorbent assay. Results: Our findings revealed that the "gene-protein-metabolite" network of CHD-PBS syndrome included 33 mRNAs, four proteins, and 25 metabolites. JNK1, FOS, CCL2, CXCL8, PTGS2, and CSF1 were all poorly expressed in the PBS group during the sequencing stage, whereas arachidonic acid (AA) was highly expressed. During the validation stage, JNK1, AP-1, CCL2, and CXCL8 were poorly expressed, whereas PTGS2, CSF1, and AA were highly expressed. The area under the receiver operating curve was as follows: CSF1 [0.9635, 95%CI (0.9295, 0.9976)] >JNK1 [0.9361, 95% CI (0.8749, 0.9972)] >CXCL8 [0.8953, 95% CI (0.8222, 0.9684)] > CCL2 [0.8458, 95% CI (0.7676, 0.9241)] >AP-1 [0.7884, 95%CI (0.6869, 0.8899)]. The logistic regression model composed of CSF1 and JNK1 showed the greatest diagnostic value and significance for PBS syndrome. Conclusion: PBS syndrome is characterized by low levels of FOS, AP-1, CCL2, CXCL8, and JNK1 and elevated levels of PTGS2 and CSF1, implying that the AA metabolism is abnormal and that the JNK/AP-1 pathway is inhibited. PBS syndromes, as a subtype of CHD, may have unique molecular changes. Background. Globally, coronary heart disease (CHD) is the leading cause of death, and this would likely continue until 2030 (Mirzaei et al., 2009, 95, 740-746). According to the disease course, CHD can be classified as chronic stable CHD (or chronic coronary syndrome) and acute coronary syndrome (ACS) (Katus et al., 2017; Knuuti, 2019). Although stable CHD is not as lethal as ACS, it has a varied incidence range and patients with CHD have prolonged angina. Some symptoms of stable angina are alleviated with pharmacological therapy, but it cannot eliminate recurrent angina (Rousan et al., 2017). The clinical outcomes were not significantly improved in patients who underwent revascularization compared with those who received optimal pharmacological therapy (Shaw et al., 2008; Antman and Braunwald, 2020). A bottleneck appears to exist in CHD treatment, and traditional Chinese medicine (TCM) can act as a favorable complement. Because of its individualized treatment approach, TCM is widely practiced in eastern civilizations (Teng et al., 2016). TCM has become a principal complement in western countries (Wieland et al., 2013). Like "disease" is used in western medicine, "syndrome" is used in TCM to comprehend anomalous human conditions on the basis of patients' symptoms, tongue, and pulse (Li et al., 2012). On the basis of disease-syndrome diagnose, a TCM doctor can subclassify CHD patients into various categories, such as phlegm and blood stasis (PBS) syndrome, cold congealing and Qi stagnation syndrome, and Qi stagnation and blood stasis syndrome. PBS syndrome has recently emerged as a hot research topic in the TCM field. Objective diagnosis, expert consultations, and efficacy evaluation scales have been developed for PBS syndrome (Ren et al., 2020; Liu et al., 2021; Zheng et al., 2022). The concept of "omics" originates from the genome. It refers to the vocabulary generated by biological molecules at different levels to describe high-sequence molecular biological data resources (Dai and Shen, 2022). RNA, protein, and metabolites decipher the essence of complex etiologies, and the integration of transcriptomics, proteomics, and metabolomics are becoming a promising research mode (Pan et al., 2022). Multi-omics studies have revealed the biological characteristics of APOE transgenic mice, bronchopulmonary dysplasia, and plant tolerant to heavy metals (Singh et al., 2016; Lal et al., 2018; Mohler et al., 2020). Over the past few years, many academic achievements related to CHD-PBS syndrome have been accrued in the single-omic area. For example, Zhou identified the differential metabolites between PBS syndrome and Qi and Yin deficiency syndrome by using the urine samples of 1072 volunteers. Some of the specific metabolites of PBS syndrome are pyroglutamic acid, glutaric acid, glucose, mannitol, and xanthine (Zhou et al., 2019). Li's metabolomic study suggested that valine, leucine, isoleucine, and glycerol phospholipid metabolism could represent PBS syndrome (Zheng et al., 2022). Although some progress has been made in the understanding of PBS syndrome in CHD through the studies conducted, some issues still exist, such as a single-omics level, a lack of in-depth research, an inability to verify each other's research results, and a lack of validation of research conclusions. Overall, a systematic description of the biological foundation of PBS syndrome is lacking. Thus, the present study utilizes system biology methodologies and constructs a multi-omics network by integrating differential genes, proteins, and metabolites to systematically and comprehensively reveal the biological basis of CHD-PBS syndrome. The current study explored 1) the characteristics of the transcriptome, proteome, and metabolome for CHD-PBS syndrome; 2) the "gene-protein-metabolite" network based on differential genes (DGs), differential proteins (DPs), and differential metabolites (DMs); 3) the key biological process and metabolic pathway most related to PBS syndrome; and 4) quantitative results and the diagnostic potential of biomarkers for PSB syndrome. Materials and methods. Multi-omics sequencing, bioinformatics analysis, and clinical validation research strategy. We collected the blood samples from healthy subjects as well as CHD patients with PBS and non-phlegm and blood stasis (NPBS) syndrome to compare the differences between them by subjecting the samples to the transcriptome, proteome, and metabolomics analyses. Bioinformatics analysis identified differential molecules as well as related biological processes and pathways. Next, the "gene-protein-metabolite" network was constructed using the MetaboAnalyst database, String database, and Cytoscape software. We selected molecules with strong centrality and biological association as potential PBS syndrome biomarkers and recruited more volunteers for further validation by enzyme-linked immunosorbent assay (ELISA). Finally, the ROC curve was utilized to assess the level and diagnostic efficacy of various molecules (Figure 1).

Multi-omics approaches for in-depth understanding of therapeutic mechanism for Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) is extensively utilized in clinical practice due to its therapeutic and preventative treatments for various diseases. With the development of high-throughput sequencing and systems biology, TCM research was transformed from traditional experiment-based approaches to a combination of experiment-based and omics-based approaches. Numerous academics have explored the therapeutic mechanism of TCM formula by omics approaches, shifting TCM research from the "one-target, one-drug" to "multi-targets, multi-components" paradigm, which has greatly boosted the digitalization and internationalization of TCM. In this review, we concentrated on multi-omics approaches in principles and applications to gain a better understanding of TCM formulas against various diseases from several aspects. We first summarized frequently used TCM quality assessment methods, and suggested that incorporating both chemical and biological ingredients analytical methods could lead to a more comprehensive assessment of TCM. Secondly, we emphasized the significance of multi-omics approaches in deciphering the therapeutic mechanism of TCM formulas. Thirdly, we focused on TCM network analysis, which plays a vital role in TCM-diseases interaction, and serves for new drug discovery. Finally, as an essential source for storing multi-omics data, we evaluated and compared several TCM databases in terms of completeness and reliability. In summary, multi-omics approaches have infiltrated many aspects of TCM research. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired or will be gained in the future.

Appraisal of treatment outcomes in integrative medicine using metabonomics: Taking non-alcoholic fatty liver disease with spleen deficiency syndrome as an example

OBJECTIVE

Appraisal of treatment outcomes in integrative medicine is a challenge due to a gap between the concepts of Western medicine (WM) disease and traditional Chinese medicine (TCM) syndrome. This study presents an approach for the appraisal of integrative medicine that is based on targeted metabolomics. We use non-alcoholic fatty liver disease with spleen deficiency syndrome as a test case.

METHODS

A patient-reported outcome (PRO) scale was developed based on literature review, Delphi consensus survey, and reliability and validity test, to quantitatively evaluate spleen deficiency syndrome. Then, a metabonomic foundation for the treatment of non-alcoholic fatty liver disease with spleen deficiency syndrome was identified via a longitudinal interventional trial and targeted metabolomics. Finally, an integrated appraisal model was established by identifying metabolites that responded in the treatment of WM disease and TCM syndrome as positive outcomes and using other aspects of the metabonomic foundation as independent variables.

RESULTS

Ten symptoms and signs were included in the spleen deficiency PRO scale. The internal reliability, content validity, discriminative validity and structural validity of the scale were all qualified. Based on treatment responses to treatments for WM disease (homeostasis model assessment of insulin resistance) or TCM syndrome (spleen deficiency PRO scale score) from a previous randomized controlled trial, two cohorts comprised of 30 participants each were established for targeted metabolomics detection. Twenty-five metabolites were found to be involved in successful treatment outcomes to both WM and TCM, following quantitative comparison and multivariate analysis. Finally, the model of the integrated appraisal system was exploratively established using binary logistic regression; it included 9 core metabolites and had the prediction probability of 83.3%.

CONCLUSION

This study presented a new and comprehensive research route for integrative appraisal of treatment outcomes for WM disease and TCM syndrome. Critical research techniques used in this research included the development of a TCM syndrome assessment tool, a longitudinal interventional trial with verified TCM treatment, identification of homogeneous metabolites, and statistical modeling.

Multi-omics approaches for deciphering the complexity of traditional Chinese medicine syndromes in stroke: A systematic review

Background: Deciphering the biological basis of traditional Chinese medicine (TCM) syndromes in complex diseases is challenging. Rapid advances in multi-omics approaches provide new opportunities to unveil the biological basis of TCM syndromes. We intend to summarize the latest significant progress and highlight the crucial value of applying multi-omics approaches to reveal TCM syndromes of stroke in a new horizon. Methods: We systematically searched PubMed, EMBASE, Web of Science Core Collection (WOSCC), Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), Wanfang database and China Biology Medicine Database (SinoMed) for relevant studies from their inception to 31 March 2022, and conducted a comprehensive systematic review (PROSPERO registration number: CRD42021285922). Results: A total of 43 relevant studies were included in the final systematic review, genomics, transcriptomics, proteomics, and metabolomics were all involved. Some gene polymorphisms, differential lncRNAs, mRNAs, miRNAs, proteins, and metabolites may be associated with TCM syndromes of stroke. In addition, some studies conducted a preliminary exploration on the different diseases with the same TCM syndrome. The results showed that thioredoxin-dependent peroxidase reductase may be the specific marker protein of Liver-yang transforming into wind syndrome, and the network formed by mir-146b-5p, -199a-5p, and 23 targeted mRNAs may be the biomarker of Blood-stasis syndrome. Conclusion: Multi-omics technologies have served as powerful tools to investigate the complexity of TCM syndromes and may hold the promise of promoting the modernization of TCM as well as personalized medicine of TCM in stroke.

Network pharmacology provides a systematic approach to understanding the treatment of ischemic heart diseases with traditional Chinese medicine

BACKGROUND

The field of network pharmacology showed significant development. The concept of network pharmacology has many similarities to the philosophy of traditional Chinese medicine (TCM), making it suitable to understand the action mechanisms of TCM in treating complex diseases, such as ischemic heart diseases (IHDs).

PURPOSE

This review summarizes the representative applications of network pharmacology in deciphering the mechanism underlying the treatment of IHDs with TCM.

METHODS

In this report, we used "ischemic heart disease" OR "coronary heart disease" OR "coronary artery disease" OR "myocardial ischemia" AND ("network pharmacology" OR "systematic pharmacology") as keywords to search for publications from PubMed, the Web of Science, and Google Scholar databases and then analyzed the representative research reports that summarized and validated the active components and targets network of TCM in improving IHDs to show the advantages and deficiencies of network pharmacology applied in TCM research.

RESULTS

The network pharmacology research indicated that HGF, PGF, MMP3, INSR, PI3K, MAPK1, SRC, VEGF, VEGFR-1, NO, eNOS, NO3, IL-6, TNF-α, and more are the main targets of TCM. Apigenin, 25S-macrostemonoside P, ginsenosides Re, Rb3, Rg3, SheXiang XinTongNing, colchicine, dried ginger-aconite decoction, Suxiao Xintong dropping pills, Ginseng-Danshen drug pair and Shenlian and more are the active ingredients, extracts, and formulations of TCM to ameliorate IHDs. These active compounds, extract, and formulations of TCM treat IHDs by delaying ventricular remodeling, reducing myocardial fibrosis, decreasing reactive oxygen species, regulating myocardial energy metabolism, ameliorating inflammation, mitigating apoptosis, and many other aspects.

CONCLUSIONS

The network pharmacology supplies a novel research exemplification for understanding the treatment of IHDs with TCM. However, the application of network pharmacology in TCM studies is still at a superficial level. By rational combining artificial intelligence technology and network pharmacology, molecular biology, metabolomics, and other advanced theories and technologies, and systematically studying the metabolic process and the network among products, targets, and pathways of TCM from the clinical perspective may be a potential development trend in network pharmacology.