Systems Pharmacology Approach and Experiment Evaluation Reveal Multidimensional Treatment Strategy of LiangXueJieDu Formula for Psoriasis

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

The causal relationship between serum metabolites and the risk of psoriasis: a Mendelian randomization and meta-analysis study

Objective

To explore the influence of serum metabolites on the risk of psoriasis.

Methods

In the initial stage, we applied Mendelian randomization to evaluate the association between 1,400 serum metabolites and the risk of psoriasis. Causal effects were primarily assessed through the Inverse-Variance Weighted method and Wald Ratio's odds ratios, and 95% confidence intervals. False Discovery Rate was used for multiple comparison corrections. Sensitivity analyses were conducted using Cochran's Q Test, MR-PRESSO. MR-Steiger Test was employed to check for reverse causality. In the validation stage, we sought other sources of psoriasis GWAS data to verify the initial results and used meta-analysis to combine the effect sizes to obtain robust causal relationships. In addition, we also conducted metabolic pathway enrichment analysis on known metabolites that have a causal relationship with the risk of psoriasis in both stages.

Results

In the initial stage, we identified 112 metabolites causally associated with psoriasis, including 32 metabolite ratios and 80 metabolites (69 known and 11 unknown). In the validation stage, 24 metabolites (16 known, 1 unknown, and 7 metabolite ratios) were confirmed to have a causal relationship with psoriasis onset. Meta-analysis results showed that the overall effect of combined metabolites was consistent with the main analysis in direction and robust in the causal relationship with psoriasis onset. Of the 16 known metabolites, most were attributed to lipid metabolism, with 5 as risk factors and 8 as protective factors for psoriasis. Peptidic metabolite Gamma-glutamylvaline levels had a negative causal relationship with psoriasis, while exogenous metabolite Catechol sulfate levels and amino acid 3-methylglutaconate levels had a positive causal relationship with the disease onset. The metabolites associated with psoriasis risk in the two stages are mainly enriched in the following metabolic pathways: Glutathione metabolism, Alpha Linolenic Acid and Linoleic Acid Metabolism, Biosynthesis of unsaturated fatty acids, Arachidonic acid metabolism, Glycerophospholipid metabolism.

Conclusion

Circulating metabolites may have a potential causal relationship with psoriasis risk, and targeting specific metabolites may benefit psoriasis diagnosis, disease assessment, and treatment.

Exploring the Effect of Xiao-Chai-Hu Decoction on Treating Psoriasis Based on Network Pharmacology and Experiment Validation

BACKGROUND

Psoriasis is a chronic, inflammatory and recurrent skin disease. Xiao-Chai-Hu Decoction (XCHD) has shown good effects against some inflammatory diseases and cancers. However, the pharmacological effect and mechanisms of XCHD on psoriasis are not yet clear.

OBJECTIVE

To uncover the effect and mechanisms of XCHD on psoriasis by integrating network pharmacology, molecular docking, and in vivo experiments.

METHODS

The active ingredients and corresponding targets of XCHD were screened through Traditional Chinese Medicine Systems Pharmacology Database and Analysis (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID). Differentially expressed genes (DEGs) of psoriasis were obtained from the gene expression omnibus (GEO) database. The XCHD-psoriasis intersection targets were obtained by intersecting XCHD targets, and DEGs were used to establish the "herb-active ingredient-target" network and Protein-Protein Interaction (PPI) Network. The hub targets were identified based on the PPI network by Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed next. Molecular docking was executed via AutoDockTools-1.5.6. Finally, in vivo experiments were carried out further to validate the therapeutic effects of XCHD on psoriasis.

RESULTS

58 active components and 219 targets of XCHD were screened. 4 top-active components (quercetin, baicalein, wogonin and kaempferol) and 7 hub targets (IL1B, CXCL8, CCND1, FOS, MMP9, STAT1 and CCL2) were identified. GO and KEGG pathway enrichment analyses indicated that the TNF signaling pathway, IL-17 signaling pathway and several pathways were involved. Molecular docking results indicated that hub genes had a good affinity to the corresponding key compounds. In imiquimod (IMQ)-induced psoriasis mouse models, XCHD could significantly improve psoriasis-like skin lesions, downregulate KRT17 and Ki67, and inhibit inflammation cytokines and VEGF.

CONCLUSION

XCHD showed the therapeutic effect on psoriasis by regulating keratinocyte differentiation, and suppressing inflammation and angiogenesis, which provided a theoretical basis for further experiments and clinical research.

Research progress of metabolomics in psoriasis

ABSTRACT

Psoriasis is a chronic inflammatory skin disease with significant physical and psychological burdens. The interplay between the innate and adaptive immune systems is thought to contribute to the pathogenesis; however, the details of the pathogenesis remain unclear. In addition, reliable biomarkers for diagnosis, assessment of disease activity, and monitoring of therapeutic response are limited. Metabolomics is an emerging science that can be used to identify and analyze low molecular weight molecules in biological systems. During the past decade, metabolomics has been widely used in psoriasis research, and substantial progress has been made. This review summarizes and discusses studies that applied metabolomics to psoriatic disease. These studies have identified dysregulation of amino acids, carnitines, fatty acids, lipids, and carbohydrates in psoriasis. The results from these studies have advanced our understanding of: (1) the molecular mechanisms of psoriasis pathogenesis; (2) diagnosis of psoriasis and assessment of disease activity; (3) the mechanism of treatment and how to monitor treatment response; and (4) the link between psoriasis and comorbid diseases. We discuss common research strategies and progress in the application of metabolomics to psoriasis, as well as emerging trends and future directions.

Using a System Pharmacology Method to Search for the Potential Targets and Pathways of Yinqiaosan against COVID-19

The first reported case of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei, China. Thereafter, it spread through China and worldwide in only a few months, reaching a pandemic level. It can cause severe respiratory illnesses such as pneumonia and lung failure. Since the onset of the disease, the rapid response and intervention of traditional Chinese medicine (TCM) have played a significant role in the effective control of the epidemic. Yinqiaosan (YQS) was used to treat COVID-19 pneumonia, with good curative effects. However, a systematic overview of its active compounds and the therapeutic mechanisms underlying its action has yet to be performed. The purpose of the current study is to explore the compounds and mechanism of YQS in treating COVID-19 pneumonia using system pharmacology. A system pharmacology method involving drug-likeness assessment, oral bioavailability forecasting, virtual docking, and network analysis was applied to estimate the active compounds, hub targets, and key pathways of YQS in the treatment of COVID-19 pneumonia. With this method, 117 active compounds were successfully identified in YQS, and 77 potential targets were obtained from the targets of 95 compounds and COVID-19 pneumonia. The results show that YQS may act in treating COVID-19 pneumonia and its complications (atherosclerosis and nephropathy) through Kaposi sarcoma-related herpesvirus infection and the AGE-RAGE signaling pathway in diabetic complications and pathways in cancer. We distinguished the hub molecular targets within pathways such as TNF, GAPDH, MAPK3, MAPK1, EGFR, CASP3, MAPK8, mTOR, IL-2, and MAPK14. Five of the more highly active compounds (acacetin, kaempferol, luteolin, naringenin, and quercetin) have anti-inflammatory and antioxidative properties. In summary, by introducing a systematic network pharmacology method, our research perfectly forecasts the active compounds, potential targets, and key pathways of YQS applied to COVID-19 and helps to comprehensively clarify its mechanism of action.