Investigating the Causal Effect of Brain Expression of CCL2, NFKB1, MAPK14, TNFRSF1A, CXCL10 Genes on Multiple Sclerosis: A Two-Sample Mendelian Randomization Approach

Identification of lipid metabolism-related gene markers and construction of a diagnostic model for multiple sclerosis: An integrated analysis by bioinformatics and machine learning

BACKGROUND

Multiple sclerosis (MS) is an autoimmune inflammatory disorder that causes neurological disability. Dysregulated lipid metabolism contributes to the pathogenesis of MS. This study aimed to identify lipid metabolism-related gene markers and construct a diagnostic model for MS.

METHODS

Gene expression profiles for MS were obtained from the Gene Expression Omnibus database. Differentially expressed lipid metabolism-related genes (LMRGs) were identified and performed functional enrichment analysis. Least absolute shrinkage and selection operator (LASSO), random forest (RF), and protein-protein interaction (PPI) analysis were employed to screen hub genes. The predictive power of hub genes was evaluated using receiver operating characteristic (ROC) curves. We developed an artificial neural network (ANN) model and validated its performance in three test sets. Immune cell infiltration analysis, Gene set enrichment analysis, and ceRNA network construction were performed to explore the role of lipid metabolism in the pathogenesis of MS. Drugs prediction and molecular docking were utilized to identify potential therapeutic drugs.

RESULTS

We identified 40 differentially expressed LMRGs, with significant enrichment in Arachidonic acid metabolism, Steroid hormone biosynthesis, Fatty acid elongation, and Sphingolipid metabolism. AKR1C3, NFKB1, and ABCA1 were identified as gene markers for MS, and their expression was upregulated in the MS group. The areas under the ROC curve (AUCs) for AKR1C3, NFKB1, and ABCA1 in the training set were 0.779, 0.703, and 0.726, respectively. The ANN model exhibited good discriminative ability in both the training and test sets, achieving an AUC of 0.826 on the training set and AUC values of 0.822, 0.890, and 0.833 on the test sets. Gamma.delta.T.cell, Natural.killer.T.cell, Plasmacytoid.dendritic.cell, Regulatory.T.cell, and Type.1.T.helper.cell were highly expressed in the MS group. A ceRNA network showed a complex regulatory interplay involving hub genes. Luteolin, isoflavone, and thalidomide had good binding affinities to the hub genes.

CONCLUSION

Our study emphasized the crucial role of lipid metabolism in MS, identifing AKR1C3, NFKB1, and ABCA1 as gene markers. The ANN model exhibited good performance on both the training and testing sets. These findings offer valuable insights into the molecular mechanisms underlying MS, and establish a scientific foundation for future research.

Combined Bulk and Single-Cell Transcriptomic Analysis to Reveal the Potential Influences of Intestinal Inflammatory Disease on Multiple Sclerosis

Multiple sclerosis (MS) and inflammatory bowel disease (IBD) are both autoimmune disorders caused by dysregulated immune responses. Still, there is a growing awareness of the comorbidity between MS and IBD. However, the shared pathophysiological mechanisms between these two diseases are still lacking. RNA sequencing datasets (GSE126124, GSE9686, GSE36807, GSE21942) were analyzed to identify the shared differential expressed genes (DEGs) for IBD and experimental allergic encephalomyelitis (EAE). Other datasets (GSE17048, GSE75214, and GSE16879) were downloaded for further verification and analysis. Shared pathways and regulatory networks were explored based on these DEGs. The single-cell transcriptome of central nervous system (CNS) immune cells sequenced from EAE brains and the public datasets of IBD (PRJCA003980) were analyzed for the immune characteristics of the shared DEGs. Mass cytometry by time-of-flight (CyTOF) of peripheral blood mononuclear cells (PBMCs) was performed for the systematic immune response in the EAE model. Machine learning algorithms were also used to identify the diagnostic biomarkers of MS. We identified 74 common DEGs from the selected RNA sequencing datasets, and single-cell RNA data of the intestinal tissues of IBD patients showed that 56 of 74 DEGs were highly enriched in IL1B+ macrophages. These 56 DEGs, defined as inflammation-related DEGs (IRGs), were also highly expressed in pro-inflammatory macrophages of EAE mice and MS patients. The abundance of systematic CD14+ monocytes was validated by CyTOF data. These IRGs were highly enriched in immune response, NOD-like receptor signaling pathway, IL-18 signaling pathway, and other related pathways. In addition, 'AddModuleScore_UCell' analysis further validated that these IRGs (such as IL1B, S100A8, and other inflammatory factors) are highly expressed mainly in pro-inflammatory macrophages, which play an essential role in pro-inflammatory activation in IBD and multiple sclerosis, such as IL-17 signaling pathway, NF-kappa B signaling pathway, and TNF signaling pathway. Finally, suppressors of cytokine signaling 3(SOCS3) and formyl peptide receptor 2(FPR2) were identified as potential biomarkers by machine learning. Two genes were highly expressed in pro-inflammatory macrophages of IBD and MS disease compared to control, and other datasets and experiments further revealed that SOCS3 and FPR2 were highly expressed in IBD and EAE samples. These shared IRGs, which encode inflammatory cytokines, exhibit high expression levels in inflammatory macrophages in IBD and may play a significant role in the inflammatory cytokine storm in MS patients. Two potential biomarkers, SOCS3 and FPR2, were screened out with great diagnostic value for MS and IBD.

Investigating the influence of oral contraceptive pill use on multiple sclerosis risk using UK Biobank data

OBJECTIVE

To investigate the association between oral contraceptive (OC) pill use and the risk of developing multiple sclerosis (MS), attempting to address the limitations present in previous studies that produced conflicting results.

DESIGN

A population-based cohort study using data from the UK Biobank.

PATIENTS

The study included 181,058 women of white ethnicity born in England between 1937 and 1970, among which 1,131 had an MS diagnosis.

INTERVENTION

Oral contraceptive use, considering the self-reported age of initiation and discontinuation. The exposures of interest include the following: ever-use, current use, duration of current use in years, and age and year at initiation.

MAIN OUTCOME MEASURES

Multiple sclerosis diagnosis (International Classification of Disease, 10th revision: G35) was used as an outcome of interest, and the associations with the exposures of interest were investigated using marginal structural models with a time-to-event approach. To adjust for confounding, we included in the models several variables, including MS polygenic risk score, education level, parity, smoking, fertility problems, obesity, and mononucleosis. We further aimed to evaluate the influence of parity using a mediation analysis.

RESULTS

The association of both ever and current OC use did not result in a statistically significant MS hazard increase (ever vs. never-users, hazard ratio [HR] = 1.30 [95% confidence interval {CI}: 0.93,1.82]; current vs. never-users, HR = 1.35 [95% CI: 0.81, 2.25]). However, we highlighted parity as an effect modifier for this association. In nulliparous women, ever and current use resulted in a significant twofold and threefold MS hazard increase (HR = 2.08 [95% CI: 1.04, 4.17] and HR = 3.15 [95% CI: 1.43, 6.9]). These associations were supported by significant MS hazard increases for a higher duration of current use and for an earlier age at initiation. We further highlighted genetic MS susceptibility as another effect modifier, as a stronger OC-MS hazard association was found in women with a low MS polygenic risk score.

CONCLUSION

Our findings highlighted how the association between OC use and MS varies on the basis of individual characteristics such as parity and genetic MS susceptibility. Importantly, current use in nulliparous women was found to be associated with a threefold increase in MS hazard. We acknowledge the need for cautious causal interpretation and further research to validate these findings across diverse populations and OC types.

Decoding the role of the CCL2/CCR2 axis in Alzheimer's disease and innovating therapeutic approaches: Keeping All options open

Alzheimer's disease (AD), as a neurodegenerative disorder, distresses the elderly in large numbers and is characterized by β-amyloid (Aβ) accumulation, elevated tau protein levels, and chronic inflammation. The brain's immune system is aided by microglia and astrocytes, which produce chemokines and cytokines. Nevertheless, dysregulated expression can cause hyperinflammation and lead to neurodegeneration. CCL2/CCR2 chemokines are implicated in neurodegenerative diseases exacerbating. Inflicting damage on nerves and central nervous system (CNS) cells is the function of this axis, which recruits and migrates immune cells, including monocytes and macrophages. It has been shown that targeting the CCL2/CCR2 axis may be a therapeutic option for inflammatory diseases. Using the current knowledge about the involvement of the CCL2/CCR2 axis in the immunopathogenesis of AD, this comprehensive review synthesizes existing information. It also explores potential therapeutic options, including modulation of the CCL2/CCR2 axis as a possible strategy in AD.

A systematic review of Mendelian randomization studies on multiple sclerosis

Mendelian randomization (MR) is a powerful approach for assessing the causal effect of putative risk factors on an outcome, using genetic variants as instrumental variables. The methodology and application developed in the framework of MR have been dramatically improved, taking advantage of the many public genome-wide association study (GWAS) data. The availability of summary-level data allowed to perform numerous MR studies especially for complex diseases, pinpointing modifiable exposures causally related to increased or decreased disease risk. Multiple sclerosis (MS) is a complex multifactorial disease whose aetiology involves both genetic and non-genetic risk factors and their interplay. Previous observational studies have revealed associations between candidate modifiable exposures and MS risk; although being prone to confounding, and reverse causation, these studies were unable to draw causal conclusions. MR analysis addresses the limitations of observational studies and allows to establish reliable and accurate causal conclusions. Here, we systematically reviewed the studies evaluating the causal effect, through MR, of genetic and non-genetic exposures on MS risk. Among 107 papers found, only 42 were eligible for final evaluation and qualitative synthesis. We found that, above all, low vitamin D levels and high adult body mass index (BMI) appear to be uncontested risk factors for increased MS risk.

Exploring molecular signatures related to the mechanism of aging in different brain regions by integrated bioinformatics

The mechanism of brain aging is not fully understood. Few studies have attempted to identify molecular changes using bioinformatics at the subregional level in the aging brain. This study aimed to identify the molecular signatures and key genes involved in aging, depending on the brain region. Differentially expressed genes (DEGs) associated with aging of the cerebral cortex (CX), hippocampus (HC), and cerebellum (CB) were identified based on five datasets from the Gene Expression Omnibus (GEO). The molecular signatures of aging were explored using functional and pathway analyses. Hub genes of each brain region were determined by protein-protein interaction network analysis, and commonly expressed DEGs (co-DEGs) were also found. Gene-microRNAs (miRNAs) and gene-disease interactions were constructed using online databases. The expression levels and regional specificity of the hub genes and co-DEGs were validated using animal experiments. In total, 32, 293, and 141 DEGs were identified in aging CX, HC, and CB, respectively. Enrichment analysis indicated molecular changes related to leukocyte invasion, abnormal neurotransmission, and impaired neurogenesis due to inflammation as the major signatures of the CX, HC, and CB. Itgax is a hub gene of cortical aging. Zfp51 and Zfp62 were identified as hub genes involved in hippocampal aging. Itgax and Cxcl10 were identified as hub genes involved in cerebellar aging. S100a8 was the only co-DEG in all three regions. In addition, a series of molecular changes associated with inflammation was observed in all three brain regions. Several miRNAs interact with hub genes and S100a8. The change in gene levels was further validated in an animal experiment. Only the upregulation of Zfp51 and Zfp62 was restricted to the HC. The molecular signatures of aging exhibit regional differences in the brain and seem to be closely related to neuroinflammation. Itgax, Zfp51, Zfp62, Cxcl10, and S100a8 may be key genes and potential targets for the prevention of brain aging.

Metabolic profiling of Lantana camara L. using UPLC-MS/MS and revealing its inflammation-related targets using network pharmacology-based and molecular docking analyses

Lantana camara L. is widely used in folk medicine for alleviation of inflammatory disorders, but studies that proved this folk use and that revealed the molecular mechanism of action in inflammation mitigation are not enough. Therefore, this study aimed to identify L. camara phytoconstituents using UPLC-MS/MS and explain their multi-level mechanism of action in inflammation alleviation using network pharmacology analysis together with molecular docking and in vitro testing. Fifty-seven phytoconstituents were identified in L. camara extract, from which the top hit compounds related to inflammation were ferulic acid, catechin gallate, myricetin and iso-ferulic acid. Whereas the most enriched inflammation related genes were PRKCA, RELA, IL2, MAPK 14 and FOS. Furthermore, the most enriched inflammation-related pathways were PI3K-Akt and MAPK signaling pathways. Molecular docking revealed that catechin gallate possessed the lowest binding energy against PRKCA, RELA and IL2, while myricetin had the most stabilized interaction against MAPK14 and FOS. In vitro cytotoxicity and anti-inflammatory testing indicated that L. camara extract is safer than piroxicam and has a strong anti-inflammatory activity comparable to it. This study is a first step in proving the folk uses of L. camara in palliating inflammatory ailments and institutes the groundwork for future clinical studies.

Heritability Estimation of Multiple Sclerosis Related Plasma Protein Levels in Sardinian Families with Immunochip Genotyping Data

This work aimed at estimating narrow-sense heritability, defined as the proportion of the phenotypic variance explained by the sum of additive genetic effects, via Haseman–Elston regression for a subset of 56 plasma protein levels related to Multiple Sclerosis (MS). These were measured in 212 related individuals (with 69 MS cases and 143 healthy controls) obtained from 20 Sardinian families with MS history. Using pedigree information, we found seven statistically significant heritable plasma protein levels (after multiple testing correction), i.e., Gc (h2 = 0.77; 95%CI: 0.36, 1.00), Plat (h2 = 0.70; 95%CI: 0.27, 0.95), Anxa1 (h2 = 0.68; 95%CI: 0.27, 1.00), Sod1 (h2 = 0.58; 95%CI: 0.18, 0.96), Irf8 (h2 = 0.56; 95%CI: 0.19, 0.99), Ptger4 (h2 = 0.45; 95%CI: 0.10, 0.96), and Fadd (h2 = 0.41; 95%CI: 0.06, 0.84). A subsequent analysis was performed on these statistically significant heritable plasma protein levels employing Immunochip genotyping data obtained in 155 healthy controls (92 related and 63 unrelated); we found a meaningful proportion of heritable plasma protein levels’ variability explained by a small set of SNPs. Overall, the results obtained, for these seven MS-related proteins, emphasized a high additive genetic variance component explaining plasma levels’ variability.

Integration of Genetic and Immune Infiltration Insights into Data Mining of Multiple Sclerosis Pathogenesis

Background

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system. MS pathogenesis is closely related to the environment, genetic, and immune system, but the underlying interactions have not been clearly elucidated. This study aims to unveil the genetic basis and immune landscape of MS pathogenesis with bioinformatics.

Methods

Gene matrix was retrieved from the gene expression database NCBI-GEO. Then, bioinformatics was used to standardize the samples and obtain differentially expressed genes (DEGs). The protein-protein interaction network was constructed with DEGs on the STRING website. Cytohubba plug-in and MCODE plug-in were used to mine hub genes. Meanwhile, the CIBERSORTX algorithm was used to explore the characteristics of immune cell infiltration in MS brain tissues. Spearman correlation analysis was performed between genes and immune cells, and the correlation between genes and different types of brain tissues was also analyzed using the WGCNA method.

Results

A total of 90 samples from 2 datasets were included, and 882 DEGs and 10 hub genes closely related to MS were extracted. Functional enrichment analysis suggested the role of immune response in MS. Besides, CIBERSORTX algorithm results showed that MS brain tissues contained a variety of infiltrating immune cells. Correlation analysis suggested that the hub genes were highly relevant to chronic active white matter lesions. Certain hub genes played a role in the activation of immune cells such as macrophages and natural killer cells.

Conclusions

Our study shall provide guidance for the further study of the genetic basis and immune infiltration mechanism of MS.

Regulation of Neuroinflammatory Signaling by PPARγ Agonist in Mouse Model of Diabetes

Many relevant studies, as well as clinical practice, confirm that untreated diabetes predisposes the development of neuroinflammation and cognitive impairment. Having regard for the fact that PPARγ are widely distributed in the brain and PPARγ ligands may regulate the inflammatory process, the anti-inflammatory potential of the PPARγ agonist, pioglitazone, was assessed in a mouse model of neuroinflammation related with diabetes. In this regard, the biochemical and molecular indicators of neuroinflammation were determined in the hippocampus and prefrontal cortex of diabetes mice. The levels of cytokines (IL-1β, IL-6, and TNF) and the expression of genes (Tnfrsf1a and Cav1) were measured. In addition, behavioral tests such as the open field test, the hole-board test, and the novel object recognition test were conducted. A 14-day treatment with pioglitazone significantly decreased IL-6 and TNFα levels in the prefrontal cortex and led to the downregulation of Tnfrsf1a expression and the upregulation of Cav1 expression in both brain regions of diabetic mice. Pioglitazone, by targeting neuroinflammatory signaling, improved memory and exploratory activity in behavioral tests. The present study provided a potential theoretical basis and therapeutic target for the treatment of neuroinflammation associated with diabetes. Pioglitazone may provide a promising therapeutic strategy in diabetes patients with muffled of behavioral activity.

CSF sTREM2 in neurological diseases: a two-sample Mendelian randomization study

Background

Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) has been described as a biomarker for microglial activation, which were observed increased in a variety of neurological disorders.

Objective

Our objective was to explore whether genetically determined CSF sTREM2 levels are causally associated with different neurological diseases by conducting a two-sample Mendelian randomization (MR) study.

Methods

Single nucleotide polymorphisms significantly associated with CSF sTREM2 levels were selected as instrumental variables to estimate the causal effects on clinically common neurological diseases, including stroke, Alzheimer’s diseases, Parkinson’s diseases, amyotrophic lateral sclerosis, multiple sclerosis, and epilepsy and their subtypes. Summary-level statistics of both exposure and outcomes were applied in an MR framework.

Results

Genetically predicted per 1 pg/dL increase of CSF sTREM2 levels was associated with higher risk of multiple sclerosis (OR = 1.038, 95%CI = 1.014–1.064, p = 0.002). Null association was found in risk of other included neurological disorders.

Conclusions

These findings provide support for a potential causal relationship between elevated CSF sTREM2 levels and higher risk of multiple sclerosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02443-9.

The role of glial cells in multiple sclerosis disease progression

Despite the development of highly effective treatments for relapsing-remitting multiple sclerosis (MS), limited progress has been made in addressing primary progressive or secondary progressive MS, both of which lead to loss of oligodendrocytes and neurons and axons, and to irreversible accumulation of disability. Neuroinflammation is central to all forms of MS. The current effective therapies for relapsing-remitting MS target the peripheral immune system; these treatments, however, have repeatedly failed in progressive MS. Greater understanding of inflammation driven by CNS-resident cells - including astrocytes and microglia - is, therefore, required to identify novel potential therapeutic opportunities. Advances in imaging, biomarker analysis and genomics suggest that microglia and astrocytes have central roles in the progressive disease process. In this Review, we provide an overview of the involvement of astrocytes and microglia at major sites of pathology in progressive MS. We discuss current and future therapeutic approaches to directly target glial cells, either to inhibit pathogenic functions or to restore homeostatic functions lost during the course of the disease. We also discuss how bidirectional communication between astrocytes and microglia needs to be considered, as therapeutic targeting of one is likely to alter the functions of the other.

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers

Here we investigate protein levels in 69 multiple sclerosis (MS) cases and 143 healthy controls (HC) from twenty Sardinian families to search for promising biomarkers in plasma. Using antibody suspension bead array technology, the plasma levels of 56 MS-related proteins were obtained. Differences between MS cases and HC were estimated using Linear Mixed Models or Linear Quantile Mixed Models. The proportion of proteins level variability, explained by a set of 119 MS-risk SNPs as to the literature, was also quantified. Higher plasma C9 and CYP24A1 levels were found in MS cases compared to HC (p < 0.05 after Holm multiple testing correction), with protein level differences estimated as, respectively, 0.53 (95% CI: 0.25, 0.81) and 0.42 (95% CI: 0.19, 0.65) times plasma level standard deviation measured in HC. Furthermore, C9 resulted in both statistically significantly higher relapsing-remitting MS (RRMS) and secondary-progressive MS (SPMS) compared to HC, with SPMS showing the highest differences. Instead, CYP24A1 was statistically significantly higher only in RRMS as compared to HC. Respectively, 26% (95% CI: 10%, 44%) and 16% (95% CI: 9%, 39%) of CYP24A1 and C9 plasma level variability was explained by known MS-risk SNPs. Our results highlight C9 and CYP24A1 as potential biomarkers in plasma for MS and allow us to gain insight into molecular disease mechanisms.

Differentially expressed genes, lncRNAs, and competing endogenous RNAs in Kawasaki disease

BACKGROUND

Kawasaki disease (KD) is an acute and febrile systemic vasculitis of unknown etiology. This study aimed to identify the competing endogenous RNA (ceRNA) networks of lncRNAs, miRNAs, and genes in KD and explore the molecular mechanisms underlying KD.

METHODS

GSE68004 and GSE73464 datasets were downloaded from the Gene Expression Omnibus. Differentially expressed lncRNAs (DElncRNAs) and genes (DEGs) in KD were identified using the criteria of p < 0.05 and | log2 (fold change) | ≥ 1. MicroRNAs (miRNAs) related to KD were searched from databases. The lncRNA-miRNA-mRNA networks involving the DElncRNAs and DEGs were constructed.

RESULTS

A total of 769 common upregulated, 406 common downregulated DEGs, and six DElncRNAs were identified in the KD samples. The lncRNA-miRNA-mRNA network consisted of four miRNAs, three lncRNAs (including the upregulated PSORS1C3, LINC00999, and the downregulated SNHG5) and four DEGs (including the downregulated GATA3 and the upregulated SOD2, MAPK14, and PPARG). Validation in the GSE18606 dataset showed that intravenous immunoglobulin treatment significantly alleviated the deregulated profiles of the above RNAs in KD patients. Three ceRNA networks of LINC00999-hsa-miR-6780-SOD2, PSORS1C3-hsa-miR-216a-PPARG/MAPK14, and SNHG5-hsa-miR-132/hsa-miR-92-GATA3 were identified. Four genes were associated with functional categories, such as inflammatory response and vascular endothelial cell.

CONCLUSIONS

The ceRNA networks involve genes, such as SOD2, MAPK14, and PPARG, and lncRNAs, including PSORS1C3, LINC00999, and SNHG5, which might play a key role in the pathogenesis and development of KD by regulating inflammation.

Transcriptional circuitry atlas of genetic diverse unstimulated murine and human macrophages define disparity in population-wide innate immunity

Macrophages are ubiquitous custodians of tissues, which play decisive role in maintaining cellular homeostasis through regulatory immune responses. Within tissues, macrophage exhibit extremely heterogeneous population with varying functions orchestrated through regulatory response, which can be further exacerbated in diverse genetic backgrounds. Gene regulatory networks (GRNs) offer comprehensive understanding of cellular regulatory behavior by unfolding the transcription factors (TFs) and regulated target genes. RNA-Seq coupled with ATAC-Seq has revolutionized the regulome landscape influenced by gene expression modeling. Here, we employ an integrative multi-omics systems biology-based analysis and generated GRNs derived from the unstimulated bone marrow-derived macrophages of five inbred genetically defined murine strains, which are reported to be linked with most of the population-wide human genetic variants. Our probabilistic modeling of a basal hemostasis pan regulatory repertoire in diverse macrophages discovered 96 TFs targeting 6279 genes representing 468,291 interactions across five inbred murine strains. Subsequently, we identify core and distinctive GRN sub-networks in unstimulated macrophages to describe the system-wide conservation and dissimilarities, respectively across five murine strains. Our study concludes that discrepancies in unstimulated macrophage-specific regulatory networks not only drives the basal functional plasticity within genetic backgrounds, additionally aid in understanding the complexity of racial disparity among the human population during stress.

Anti-inflammatory and immunomodulatory effects of baicalin in cerebrovascular and neurological disorders

Inflammatory responses play an extraordinary role in the pathogenesis of cerebrovascular and neurological disorders. Baicalin is one of the important flavonoids, which is extracted from Scutellaria baicalensis Georgi. Recently, numerous in vivo and in vitro studies have shown that baicalin has salutary effects for anti-inflammatory and immunomodulatory and has been demonstrated to exert beneficial therapeutic properties in cerebrovascular and neurological diseases. In this review, we aim to discuss that baicalin exerts anti-inflammatory effects through multiple pathways and targets, thus affecting the production of a variety of inflammatory cytokines and neuroprotective process of neurological diseases; furthermore, the related targets of the anti-inflammatory effects of baicalin were analyzed via using the tools of network pharmacology, to provide theoretical basis and innovative ideas for the future clinical application of baicalin.