Network pharmacology analysis of Huangqi reveals quercetin as a therapeutic for allergic rhinitis via the RELA-regulated IFNG/IRF1 axis response

doi:10.21203/rs.3.rs-4122017/v1

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Research Article

Network pharmacology analysis of Huangqi reveals quercetin as a therapeutic for allergic rhinitis via the RELA-regulated IFNG/IRF1 axis response

https://doi.org/10.21203/rs.3.rs-4122017/v1

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published 12 Aug, 2024

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Despite the complexity of allergic rhinitis (AR) pathogenesis, no FDA-approved drug has been developed to achieve optimal therapeutic results. Traditional Chinese Medicine (TCM) has proven advantageous in AR therapy. The present study aimed to explore the potential bioactive components of Hedysarum Multijugum Maxim (Radix Astragali or Huangqi) in the treatment of AR by network pharmacology and experimental approaches. The bioactive components of Huangqi were identified and used for predicting potential therapeutic target genes. Genes related to AR were retrieved from GeneCard and Disgenet and merged with the targets of the bioactive components of Huangqi to obtain key target genes used for generating the "bioactive compound-target gene" pharmacological network. Ovalbumin (OVA)-induced AR mouse model was established to assess the anti-AR effect of Huangqi and its hub ingredient in AR, quercetin (QUE). We identified 13 active ingredients of Huangqi that could target 67 AR pathogenesis-related genes. In addition, QUE was detected as the bioactive component targeting the highest number of AR-related genes. The protein-protein interaction (PPI) network analysis revealed that IFNG, IRF1, JUN, RELA, and NFKBIA were important targets of QUE in AR treatment. Experimentally, we demonstrated that Huangqi and QUE counteracted AR in ovalbumin (OVA)-sensitized mice by regulating the IFNG/IRF1 signaling via NF-κB pathway in AR mice. This study sheds light on efficacious constituents, potential targets, and molecular mechanisms of Huangqi in treating AR. Such knowledge is deemed crucial in advancing the development of tailored therapeutic interventions aimed at addressing AR.

Allergic rhinitis

network pharmacology

Huangqi

quercetin

NF-κB signaling

IFNG/IRF1 signaling

Allergic rhinitis (AR) is an allergic disease of the nasal mucosa caused by various factors (Baroody et al., 2008, Peroni et al., 2012, Segboer et al., 2013, Steelant et al., 2018, Struß et al., 2020). Alongside imposing a substantial economic burden, AR alters the quality of life of patients (Dalal et al., 2008, Hellgren et al., 2010, Wang et al., 2016, Tkacz et al., 2021). To date, despite the use of drugs such as probiotics, Korean red ginseng, ear acupuncture, montelukast, pseudoephedrine, desloratadine, loratadine, fexofenadine hydrochloride, and herbal treatment such as Nigella sativa for alleviating the symptoms of different forms of AR (Bernstein et al., 1997, Meltzer et al., 2000, Simons et al., 2003, Mucha et al., 2006, Milgrom et al., 2007, Watanasomsiri et al., 2008, Nikakhlagh et al., 2011, Schaefer and Enck, 2019, Ding et al., 2021, Jung et al., 2021), no practical and effective therapeutic approach for AR has been developed so far. In-depth investigations are crucial for developing potent drugs for AR.

For centuries, Traditional Chinese Medicine (TCM) has been employed to address a range of health issues, including AR. For example, the possible therapeutic effect of acupuncture for AR treatment has been reported in numerous studies (Sun et al., 2016, Shou et al., 2020). The efficiency of herbal medicines from TCM in the treatment of AR has also been reported, suggesting the importance of developing new TCM drugs for AR (Yang et al., 2021, Qu et al., 2022).

Hedysarum Multijugum Maxim (Huangqi in Chinese) is the desiccated root of Astragalus membranaceus (Chen et al., 2020). Huangqi is known for its antioxidant properties and holds promise as a potential treatment for many human diseases, including ulcerative colitis (Zhang et al., 2022), rhinitis (Geng et al., 2021), and seasonal AR (Matkovic et al., 2010). However, further investigation is required to fully understand the therapeutic potential of Huangqi as a natural and safe alternative for treating AR. In recent years, network pharmacology and molecular docking have emerged as powerful computational methods that aid drug discovery and accelerate the identification and development of new disease treatments (Liang et al., 2019, Yao et al., 2020, Cheng et al., 2022, Cong et al., 2023, Liu et al., 2023, Zhang et al., 2023). By integrating multiple data sources, these methodologies provide a more comprehensive understanding of the potential therapeutic targets and active compounds of natural products (Liang et al., 2019, Yao et al., 2020, Cheng et al., 2022, Cong et al., 2023, Liu et al., 2023, Zhang et al., 2023) such as Huangqi.

Our research employed network pharmacology to identify potential therapeutic targets and active compounds of Huangqi for treating AR. Our investigation revealed that quercetin (QUE), a natural flavonoid in Huangqi, exhibited promising efficacy in managing AR. These findings have significant implications for developing novel therapeutic strategies for this debilitating condition. Our research delved into the molecular mechanisms of Huangqi and QUE in AR treatment and found that Huangqi and QUE can decrease inflammation, regulate essential cytokines, and enhance the expression of crucial immune response regulators and suggest that Huangqi, especially its component QUE, holds promise as a therapeutic option for treating AR.

2.1. Retrieval of main bioactive components

The TCM system pharmacology database and analysis platform (TCMSP, https://tcmsp-e.com) was used to obtain the bioactive components of Huangqi (Hedysarum Multijugum Maxim.). The selection process of the bioactive components was based on the optimal toxicologic ADME criteria, which requires an oral bioavailability (OB) of at least 30% and a drug-like property (DL) of at least 0.18.

2.2. Potential targets of drug and disease and target classification

To obtain the full names of the targets of the Huangqi bioactive components, we used the TCMSP database. These names were then mapped with the annotation file downloaded from the UniProt database (www.uniprot.org) to retrieve the gene symbols. To find genes related to AR, we conducted a keyword search for "allergic rhinitis" in several databases, including GeneCards (http://www.genecards.org/), DrugBank (https://www.drugbank.ca/), OMIM (https://omim.org/), DisGeNET, and PharmGkb.

2.3. Compound-gene network and protein-protein interaction (PPI) network construction

To generate and visualize the bioactive component-target gene network, Cytoscape 3.8.0 (https://cytoscape.org/) was used. The STRING online tool generated the protein-protein interaction (PPI) network (https://string-db.org/). The network analysis parameters were set as follows: input type, Multiple proteins; species, "Homo sapiens"; and confidence scores ≥ 0.4. The PPI network was then downloaded and visualized in Cytoscape.

2.4. CytoNCA analysis of network topology

The topology of the PPI network was analyzed using the CytoNCA plug-in in Cytoscape. The genes were screened based on the centrality of the nodes (Centrality) and the top 50% was used as the screening standard. The topological analysis was carried out using degree centrality (degree), betweenness centrality (BC), and proximity centrality (CC) to identify the core targets and possible protein functional modules.

2.5. Functional analysis of target genes

Enrichment analysis was conducted using the TCGAbiolinks package in R to obtain the enrichment terms of target genes. The terms with a p-value lower than 0.05 were considered significant and were taken as the enriched terms.

2.6. Molecular docking

The source files and images for the key ingredient structures were obtained from TCMSP. The PDB files and images of their structures for the hub targets were acquired from the PDB website. Before docking, the original ligands and water molecules were removed, and polar hydrogens were added to the target proteins using Discovery Studio (Version 2016). The molecular docking simulation with the default parameters was performed using iGEMDOCK (Version 2.1).

2.7. Preparation of Huangqi decoction

Astragali Radix and Glycyrrhizae Radix et Rhizoma were authenticated according to the Chinese Pharmacopoeia (2015 version). The extract powder of the Huangqi decoction, expertly prepared by Jiangyin Tianjiang Pharmaceutical Co., Ltd. in Jiangsu, China, contains 6 grams of Radix astragali and 1 gram of Radix Glycyrrhizae. Thus, herein, these herbs were blended in a 6:1 ratio and then methodically extracted using boiling water. The aqueous extract was vacuum-dried (60°C) to obtain the powdered extract.

2.8. Ovalbumin-induced AR mouse model and drug treatments

We obtained male BALB/C mice aged 6–8 weeks from Shanghai SLAC laboratory animal co.Ltd. The mice were bred in an environment that was free of any specific pathogen. They were fed standardized sterile food and water, which had been sterilized by high-pressure steam and cooled to room temperature. All animal experiments were conducted in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and approved by the Ethics Committee of Shanghai Pudong New Area Guangming Hospital of Traditional Chinese Medicine.

The mice were divided into Control, AR, AR + Huangqi-Low (20 mg/kg), AR + Huangqi-High (50 mg/kg), AR + QUE, AR + helenalin, AR + helenalin + Huangqi-High (50 mg/kg), AR + helenalin + QUE. The establishment of ovalbumin-induced AR in mice was conducted in two stages, namely the basic sensitization stage and the stimulation stage. In the basic sensitization stage, we injected intraperitoneally a mixture comprising 40 µg OVA (Grade V, Sigma, St. Louis, MO, USA) and 25 µL Imject™ Alum Adjuvant (ThermoScientific, Rockford, MD, USA) three times, on days 0, 7, and 14. Next, mice received treatment once daily with low- and high-doses of Huangqi decoction extract (20 or 50 mg/kg) and QUE (100 mg/kg) by intragastric administration from day 15 to day 27. QUE with a purity of at least 95% was purchased from Sigma in St. Louis, USA. Helenalin (Cayman Chemicals) was mixed with distilled water and 0.05% polysorbate 80 and given to mice by intraperitoneal injection at a dose of 25 mg of helenalin per kg of body weight every two days. Mice in the OVA group were received saline. After being sensitized, mice were given daily treatment from day 21 to day 27. Following this, they were challenged with OVA by administering it intranasally at a concentration of 10 mg/mL (20 µL in each nasal cavity) one hour after the treatment. The mice were then put to sleep using ether and sacrificed 24 hours after the final OVA challenge.

Nasal symptoms

The number of nasal rubs and sneezes, as well as nasal secretions, were recorded for 15 minutes after the most recent OVA challenge in order to assess any early allergic reactions.

2.9. HE staining

The nasal mucosa samples from OVA-challenged mice were stained using the standard HE protocols. A 10% formalin solution-based fixation preceded paraffin embedding and dewaxing through a series of alcohols. For 5 minutes, Hematoxylin (Sigma-Aldrich, H&E, HHS16) was applied, followed by a water rinse. For 3 minutes, Eosin (Sigma-Aldrich, E4009-100ML) was applied, followed by another rinse with distilled water. Dehydration and mounting preceded microscopic observation, with a coverslip as the final touch.

2.10. Immunohistochemistry detection of RELA

The mice nasal mucosa tissue sections were processed to determine the RELA expression levels by using immunohistochemistry. Briefly, the nasal mucosa tissue was afterward paraffin-embedded followed by slicing it into 5-micron thick sections. After deparaffinizing them, the sections were rehydrated and antigen retrieval was done with a citrate buffer. After the use of hydrogen peroxide to block endogenous peroxidase activity. Next, the sections were treated with RELA antibody and incubated at temperature of 4°C for 12 hours. Subsequently, the sections were incubated with the secondary antibody tagged to peroxidase of horseradish peroxidase (HRP). Diaminobenzidine was used as a substrate to achieve a precipitation of brown crystals at the areas expressing RELA. After the counterstaining with the hematoxylin was performed, the slices were processed, stained and subsequently underwent examination under microscope and images were captured for analysis of RELA expression.

2.11. Enzyme-linked immunosorbent assay (ELISA)

Mouse ELISA kits for IL-4, IgE, IL-5, TNF-α, IL-13, and IFNG were all purchased from Invitrogen (Shanghai, China) and used to detect the levels of these proteins in the nasal lavage fluid (NALF). Briefly, following the sacrifice, the trachea was opened, and a sterile saline solution of 1 mL was gently pumped into the nasal cavities using an 18-gauge catheter. The NALF was collected from the front nostril, and then centrifuged at 10,000 rpm for 10 minutes at 4°C. The resulting supernatant was transferred to another tube and stored at a temperature of − 80°C for subsequent analysis of cytokine levels. ELISA kits were used to detect the levels of the above proteins following the manufacturer’s instructions. The absorbance was detected using a microplate reader at the wavelength of 560 nm. Standard curves were used to quantify the levels of detected proteins in the NALF samples.

2.12. RT-qPCR

Total RNA was isolated from the nasal mucosa specimens using TRIzol RNA extraction reagent as per the manufacturer’s guidelines. The purity of the extracted RNA was were checked with the NanoDrop Spectrophotometer (Thermo Fisher Scientific). Next, cDNA synthesis was achieved using SuperScript IV Reverse Transcriptase Kit (Thermo Fisher Scientific). The cDNA samples were subsequently amplified by quantitative PCR using appropriate specific primers (Table 1). The PCR reactions were carried out in Applied Biosystems QuantStudio 7 Flex Real-Time PCR System. The mRNA expression levels were normalized to GAPDH as an internal reference gene. The comparative Ct method was used to compute the relative mRNA levels of the genes of interest.

Table 1

Primers used in this study
Gene Name	Forward primer sequence (5'->3')	Reverse primer sequence (5'->3')
Il4	5'-CACTTGCAAGCTTTTGCCCT-3'	5'-AGCCAACAGCCTCCTGTATTG-3'
Il5	5'- CGTGGGGGTACTGTGGAAAT-3'	5'- AGGGTCCCTGGGGAACTTAC-3'
Il13	5'-CTTGAGCCCAGGCACTTGTA-3'	5'-TATGCTACCCGAGGGATGCT-3'
Tnf-α	5'-ACTGATGAGAGGGAGGCCAT-3'	5'-CCGTGGGTTGGACAGATGAA-3'
Ifng	5'- ATCAAGCTGCCTCCCGTATG-3'	5'- CTGTCTGCAGTGGGGAAACA-3'
Irf1	5'- AACAGGGGACCATCCTCCTT-3'	5'- GATCGACGCATGTCAATGCT-3'
Rela	5'- AGTTCTGAAAGGGGAGGGAGA-3'	5'- CACCCCTTAGTTTCACCGCA-3'

2.13. Statistical analysis

The data obtained from the experiment were analyzed with the help of GraphPad Prism 9.0 software (v9.0, La Jolla, CA, USA). For statistical analysis, one-way ANOVA followed by Turkey's test was employed. The values for all measurements were expressed as means ± standard deviation (SD). A P value of less than 0.05 was considered to indicate statistically significant results.

3.1. Identification of hub bioactive components of Huangqi and their potential target genes in AR treatment

A total of 13 unique bioactive components were screened as bioactive ingredients of Huangqi according to the ADME criteria (OB > 30%, DL > 0.18) (Additional File S1). The prediction of target genes of each bioactive components from the TCMSP database allowed the identification of 67 targets (Additional File S1). After appending and removing the sets of genes from OMIM, GeneCards, DrugBank, PharmGkb, and DisGeNET platform, a total of 1232 AR-related genes were retrieved (Additional File S2). The overlap of the AR-related genes and the target genes of Huangqi allowed the identification of 67 intersection genes as the targets of Huangqi in the treatment of AR (Fig. 1A).

3.2. Ingredient-gene interaction network of Huangqi

The bioactive components-targets network of Huangqi in AR treatment was constructed and visualized in the CytoScape software (Fig. 1B). The network parameters were as depicted in Additional File S3. The bioactive components-targets pharmacological network indicated QUE as the hub component of Huangqi in AR treatment (MOL000098, degree 62, betweenness 0.799350718, closeness 0.752380952), followed by kaempferol (MOL000422, degree 23, betweenness 0.082504775, closeness 0.436464088) that was also active in treating AR (Fig. 1B, Additional File S3). The most targeted genes were PTGS2 (degree 13, betweenness 8860.936, closeness 0.5974843), PTGS1 (Degree 11, betweenness 0.08243608, closeness 0.530201342), NOS2 (degree 8, betweenness 0.011385815, closeness 0.348017621), and PPARG (Degree 34, betweenness 0.023954991, closeness 0.49068323) (Fig. 1B, Additional File S3).

3.3. Protein-protein interaction network analysis and identification of hub targets of Huangqi in AR

The 67 targets of Huangqi components were used as input for PPI network generation in the STRING database (Fig. 2A). The PPI network was imported into Cytoscape and analyzed. The PPI network contained 66 nodes and 983 edges (Fig. 2A). The average number of neighbors was 29.788 (Fig. 2A). The network radius was 2 while its diameter was 3 (Fig. 2A). The functional enrichment analysis indicated that the protein in the PPI network were involved in the biological processes of positive regulation of cellular biosynthetic process (n = 19), positive regulation of biosynthetic process (n = 20), positive regulation of nitrogen compound metabolic process (n = 18), and positive regulation of macromolecule biosynthetic process (n = 18) (Fig. 2B). The most enriched molecular functions of Huangqi were cytokine activity (n = 10), lipid binding (n = 8), growth factor activity (n = 5), and nitric-oxide synthase activity (n = 2) while extracellular space (n = 15), extracellular region part (n = 16), plasma membrane part (n = 13), extracellular region (n = 18), and cytosol (n = 10) were the most enriched cellular components (Fig. 2B). The pathways of Glucocorticoid Receptor Signaling (n = 27), Hepatic Fibrosis / Hepatic Stellate Cell Activation (n = 20), IL − 12 Signaling and Production in Macrophages (n = 18), Fibroblasts and Endothelial Cells in Rheumatoid Arthritis (n = 21), Role of Macrophages, HMGB1 Signaling (n = 15) were the most enriched (Fig. 2B).

According to the MCODE analysis, important targets of Huangqi were 39 and included NOS2, RELA, CXCL10, BCL2L1, PPARA, VCAM1, IL10, JUN, MYC, IL1A, PTGS2, CRP, IRF1, VEGFA, MAPK14, HIF1A, CCL2, IFNG, MPO, IL2, SERPINE1, HMOX1, TNF, TGFB1, SPP1, AKT1, NFKBIA, IL6, SIRT1, NOS3, PPARG, MMP9, EGFR, IL1B, IL4, CD40LG, ICAM1, SELE, and STAT1 which formed an interaction cluster module (Fig. 2A). These hub target genes were involved in the biological processes of positive regulation of cellular biosynthetic process (n = 18), positive regulation of biosynthetic process (n = 19), and positive regulation of nitrogen compound metabolic process (n = 17) (Fig. 3). The prevalent cellular component terms were extracellular space (n = 14), extracellular region part (n = 14), extracellular region (n = 14), and non-membrane-bounded organelle (n = 10) (Fig. 3). The most enriched molecular function terms were cytokine activity (n = 10), growth factor activity (n = 5), nitric-oxide synthase activity (n = 2), and tetrahydrobiopterin binding (n = 2) (Fig. 3). The most enriched target pathways were Glucocorticoid Receptor Signaling (n = 22), Hepatic Fibrosis/Hepatic Stellate Cell Activation (n = 18), Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis (n = 18), and IL-12 Signaling and Production in Macrophages (n = 14) (Fig. 3).

3.4. Protein-protein interaction network of QUE targets in AR and their function

Because QUE was identified as the ingredient with the greatest number of targets in AR treatment, its 62 targets in AR were used for generating the PPI network (Fig. 4A). The PPI network was composed of 809 edges and 59 nodes. The network diameter was 3 with a radius of 2 and an average number of neighbors of 27.268 (Fig. 4A). Clustering with MCODE identified 34 proteins as hub targets of QUE in the treatment of AR. Successive clustering analysis from the string database indicated that the important targets of QUE were RELA, JUN, NFKBIA, IRF1, and IFNG (Fig. 4B). The 34 hub QUE targets were involved in the biological processes including positive regulation of cellular biosynthetic process (n = 15), regulation of secretion (n = 7), positive regulation of macromolecule metabolic process (n = 14), inflammatory response (n = 11), and regulation of cytokine production (n = 9) (Fig. 4C). The predominant cellular component terms were extracellular space (n = 13), extracellular region part (n = 13), extracellular region (n = 13), and platelet alpha granule lumen (n = 2) (Fig. 4C). The predominantly enriched molecular functions were cytokine activity (n = 9), growth factor activity (n = 4), interleukin-1 receptor binding (n = 2), and protein heterodimerization activity (n = 3) (Fig. 4C). The most enriched target pathways of QUE targets included Role of Osteoblasts, Osteoclasts and Chondrocytes in Rheumatoid Arthritis (n = 12), TREM1 Signaling (n = 9), IL-8 Signaling (n = 12), HMGB1 Signaling (n = 11), Glucocorticoid Receptor Signaling (n = 19), and Hepatic Fibrosis / Hepatic Stellate Cell Activation (n = 17) (Fig. 4C).

3.5. Molecular docking analysis

To confirm the interaction between QUE and its hub targets RELA, JUN, NFKBIA, IRF1, and IFNG, molecular docking was performed. The results showed that QUE had excellent binding affinity for RELA, JUN, NFKBIA, IRF1, and IFNG, and was thus potential therapeutic active ingredient of Huangqi for AR treatment (Figs. 5A and 5B). RELA-QUE showed the lowest energy value (-121), which indicated a strong and stable interaction between RELA and QUE (Fig. 5B). NFKBIA-QUE showed the greatest VDW value (9185), suggesting a strong van der Waals interactions among the ligand and the protein (Fig. 5B). RELA-QUE showed the lowest HBond value (-93), which indicated a significant hydrogen bonding (Fig. 5B). These results suggested that RELA-QUE exhibited the most favorable docking properties based on energy, hydrogen bonding, and VDW interactions, which could be valuable for further studies or drug development targeting this protein.

3.6. Huangqi and its component QUE alleviate AR via regulating RELA-regulated response of IFNG/IRF1 axis

To investigate the effect of Huangqi and its main component QUE in the treatment of AR and the potential involvement of RELA, IFNG, and IRF1 in the underlying mechanism, a mouse model of OVA-induced AR was established and subjected to the treatment with different concentrations of Huangqi, QUE and RELA inhibitor (Helenalin). HE staining was performed to analyze the histopathological changes of the nasal mucosa tissue (Fig. 6A). Compared to the control group, increased infiltration of inflammatory cells such as eosinophils and lymphocytes, hyperreactivity of nasal mucosa, and edema in the AR model group were observed (Fig. 6A). In addition, the treatment of AR mice with QUE or Huangqi significantly alleviated the AR-induced histopathological changes, and the effect of Huangqi was found to be dose-dependent (Fig. 6A). Moreover, treating RA mice with Helenalin, inhibited the extent of infiltrating inflammatory cells, mucosal hyperreactivity, edema, and cell hyperplasia (Fig. 6A). Interestingly, the combined treatment of Helenalin with Huangqi or QUE further promoted the effect of Huangqi or QUE (Fig. 6A). In addition, we found that the number of sneezing episodes (Fig. 6B), the number of rubs on the eyes (Fig. 6C), nasal secretions (Fig. 6D), and the level of IgE (Fig. 6E) were all increased in the AR group compared to the control group. Moreover, the treatments with QUE, Huangqi or Helenalin significantly decreased the number of sneezing episodes, the number of rubs, the amount of nasal secretion, and the level of IgE compared with the model group, implying relief of nasal irritability and hypersensitivity (Figs. 6B-6E). However, the effect of Huangqi or QUE on the number of sneezing episodes, the number of rubs, the amount of nasal secretion, and the level of IgE was significantly promoted by Helenalin (Figs. 6B-6E). These findings showed that Huangqi and its active component QUE have potential as treatments for AR symptoms.

The qRT-PCR assay indicated that RELA was upregulated in nasal mucosa of mice in the AR group while the IFNG and its receptor IRF1 were downregulated compared to mice in the control group (Fig. 7A). Furthermore, we observed that Huangqi dose-dependently decreased the mRNA expression of RELA but increased the mRNA expression levels of IFNG and IRF1 compared to the AR model group (Fig. 7A). Moreover, the treatment of AR mice with QUE also decreased the expression of RELA but increased the levels of IFNG and IRF1 (Fig. 7A). Similarly, the treatment of AR mice with Helenalin decreased the expression of RELA but increased the expression of IFNG and IRF1 (Fig. 7A). Further immunohistochemical analysis of RELA confirmed the effect of Huangqi, QUE and Helenalin on the protein expression of RELA (Fig. 7B).

By utilizing qRT-PCR, we also measured the levels of inflammatory cytokines in the nasal mucosa (Fig. 8A). The findings revealed an increase in mRNA expression of IL-13, IL-4, TNF-α, and IL-5 in the nasal mucosa (Fig. 8A) of mice with AR compared to the control group. Moreover, treatment with Huangqi, QUE and Helenalin resulted in a reduction in the levels of these mediators when compared to the AR model group (Fig. 8A). In addition, combination with Helenalin further promoted the effect of Huangqi and QUE (Fig. 8A). Furthermore, ELISA was used to detect the protein levels of IL-13, IL-4, TNF-α, IL-5 and IFNG in the NALF of mice. The protein levels of IL-13, IL-4, TNF-α, and IL-5 in different groups were similar to the trends observed in qRT-PCR (Fig. 8B). In addition, the protein level of IFNG in the NALF was decreased in AR but promoted by the treatment with Huangqi, QUE or Helenalin (Fig. 8B). This indicated that Huangqi or QUE may have an effect on alleviating inflammation associated with AR via regulating RELA/IFNG/IRF1 axis.

AR is a serious disease encountered in the human population, and its prevention and treatment options are limited. It is, therefore, important to find and validate candidate drugs for this disease. Past research indicated the potential of Huangqi in the treatment of AR. However, the therapeutic mode of action of Huangqi in AR has to be clarified. Herein, we intended to pinpoint the bioactive components of Huangqi in AR therapy by network pharmacology and examine their possible molecular mechanism. We screened 76 bioactive components in Huangqi, targeting 62 genes related to the pathogenesis of AR. Among these bioactive components, QUE was found to have the highest number of targets (41 targets) in AR treatment, showing that QUE may be used as a key drug for treating AR. Based on the 62 QUE targets, the PPI network indicated RELA, JUN, NFKBIA, IRF1, and IFNG as the key hub genes. The 34 hub targets of QUE were those participating in biological processes related to biosynthetic, immune, and inflammation processes. Experimentally, we demonstrated that Huangqi or QUE alleviate inflammation associated with AR via regulating RELA/IFNG/IRF1 axis. Our study is the first pharmacological network analysis demonstrating the molecular mechanism of Huangqi effectiveness against AR, shedding light on the mode of action of Huangqi and QUE in the treatment of AR.

The scientific study on the efficiency of TCM to treat AR has yielded positive results. Data suggests that incorporating TCM practices, such as herbal remedies and acupuncture, can significantly improve AR symptoms, including congestion and runny nose (Sun et al., 2016, Shou et al., 2020, Ding et al., 2021). The effect of TCM treatments can offer sustained relief, with symptoms subsiding for up to a year following treatment (Yang et al., 2021, Zhang et al., 2023). Of significance, TCM therapies demonstrate minimal side effects and are well-received by patients (Zhang et al., 2020). Thus, the application of TCM in alleviating AR may be a safe and effective additional therapy for individuals seeking allergy symptom relief (Zhang et al., 2020). Emerging research suggests that Huangqi may hold significant promise in managing AR symptoms. Indeed, a previous study indicated that Huangqi contains anti-allergic components (Lv et al., 2017). Another study discovered that Huangqi extract significantly alleviated nasal symptoms, including sneezing and congestion, in patients with AR (Matkovic et al., 2010). These studies indicate that Huangqi might serve as a valuable supplement to conventional AR treatments. However, despite this potential, network analysis of Huangqi in human diseases has yet to be conducted. In this study, we conducted network pharmacology to elucidate, for the first time, the mechanism of Huangqi in AR. We found that the therapeutic mechanism of Huangqi is driven by its components that target genes mainly responsible for positive regulation of cellular biosynthetic process. When an allergen triggers the immune system, it produces IgE, leading to a chain reaction of histamine release in the nasal tissues, triggering symptoms such as sneezing, itching, and congestion in AR (Justiz Vaillant et al., 2023, Kumari et al., 2023). Thus, by targeting the biosynthetic processes, Huangqi can perturb the disturbances associated with AR, resulting in efficient treatments of AR. Our research also showed that Huangqi mainly targets immune- and inflammation-related pathways such as IL − 12 Signaling and Production in Macrophages, and Role of Macrophages. Experimentally, we found that Huangqi counteracted the effect of AR on the levels of cytokines such as IL-13, IL-4, TNF-α, IL-5 and IFNG, confirming its anti-inflammatory and immune-regulating properties. This finding is supported by a previous study indicating that Huangqi-Guizhi-Wuwu decoction is effective in regulating the differentiation of CD4(+) T cell and preventing the progression of experimental autoimmune encephalomyelitis in mice (Xu et al., 2024).

QUE, a flavonoid compound, is commonly encountered in a variety of fruits and vegetables. Through consistent research findings, QUE has been shown to offer therapy and protection properties against various human conditions. In the present study, we found that QUE was the component of Huangqi with the highest number of targets as AR-related genes. Experimentally, the effect of QUE was similar to that of Huangqi on AR-associated inflammation and pathological changes. This anti-AR properties of QUE has been reported in previous studies. In fact, it was previously reported that AR can be alleviated by applying QUE, which contributes in restoring the balance of the Treg/Th17 cells and Th1/Th2 cells (Ke et al., 2023). A clinical study indicated that repeated oral intake of a quercetin-containing supplement can effectively reduce allergic reaction (Yamada et al., 2022). The PPI network established from the 62 QUE targets has revealed important hub genes, including RELA, JUN, NFKBIA, IRF1, and IFNG. RELA and JUN coordinate gene expression, whereas NFKBIA serves as a restrictive agent in the NF-κB pathway. IRF1 regulates immune responses, while IFNG participates in innate and adaptive immune responses. The targeting of these critical genes implies that QUE may influence their activity to produce therapeutic effects through associated pathways.

The NF-κB pathway is crucial for immune homeostasis. The RELA subunit of NF-κB is responsible for the transcriptional activation of pro-inflammatory genes, and its activity is tightly controlled by various mechanisms to prevent excessive inflammation and ensure proper immune responses. RELA has been reported to be significantly involved in AR. For instance, it was reported that miR-302e hinders allergic inflammation via inhibiting NF-kB activation by targeting RELA (Xiao et al., 2018). Moreover, fucoxanthin was reported to alleviate Ovalbumin-Induced AR via RELA and STAT3 Signaling (Li et al., 2019). In the present study, docking results indicated a strong interaction between QUE and RELA. Our study revealed that treatment with Huangqi, QUE and RELA inhibitor helenalin resulted in a considerable decrease in AR symptoms in mice that were exposed to OVA. These treatments also inhibited the expression of proinflammatory cytokines in the nasal mucosa and activated the IFNG/IRF1 axis. The results point towards Huangqi, QUE and RELA inhibition as a potentially effective anti-inflammatory intervention for AR.

Conclusion

Through the use of network pharmacology, we have successfully identified 13 core components and 67 potential targets of Huangqi, which have proven effective in treating AR. The results of molecular docking analysis have revealed that QUE, the primary component of Huangqi used in AR treatment, shows exceptional binding ability to key targets. In vivo experiments have further demonstrated that Huangqi may mitigate the pathological damage associated with AR, while also regulating the production of pro-inflammatory factors and immune response by suppressing the activation of the NF-kB and IFNG/IRF1 pathway. Our study presents a promising new drug for AR, and serves as a comprehensive reference for the mechanistic study of Huangqi and QUE in treating this condition.

Acknowledgments

We are grateful to Pudong New Area Science and Technology Development Fund Special Project for Civil Livelihood Research for the financial support of this study.

Author contributions statement

YD contributed to the study conception and design. LS performed data collection. HZ and YZ performed data analysis. YD wrote the frst draft of the paper. XH commented on the frst draft and read and approved the fnal manuscript. The authors declare that no paper mill was used and that all data were generated in-house.The authors declare that all data were generated in-house and that no paper mill was used

Funding

This study was supported by Pudong New Area Science and Technology Development Fund Special Project for Civil Livelihood Research (PKJ2022-Y29).

Data availability

All original data of this study are attached as a supplementary fle.

Consent for publication Not applicable because publicly available

information is used as data source.

Competing interests The authors declare no competing interests.

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Network pharmacology analysis of Huangqi reveals quercetin as a therapeutic for allergic rhinitis via the RELA-regulated IFNG/IRF1 axis response

Status:

Journal Publication

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Abstract

Figures

1. Introduction

2. Materials and methods

2.1. Retrieval of main bioactive components

2.2. Potential targets of drug and disease and target classification

2.3. Compound-gene network and protein-protein interaction (PPI) network construction

2.4. CytoNCA analysis of network topology

2.5. Functional analysis of target genes

2.6. Molecular docking

2.7. Preparation of Huangqi decoction

2.8. Ovalbumin-induced AR mouse model and drug treatments

2.9. HE staining

2.10. Immunohistochemistry detection of RELA

2.11. Enzyme-linked immunosorbent assay (ELISA)

2.12. RT-qPCR

2.13. Statistical analysis

3. Results

3.1. Identification of hub bioactive components of Huangqi and their potential target genes in AR treatment

3.2. Ingredient-gene interaction network of Huangqi

3.3. Protein-protein interaction network analysis and identification of hub targets of Huangqi in AR

3.4. Protein-protein interaction network of QUE targets in AR and their function

3.5. Molecular docking analysis

3.6. Huangqi and its component QUE alleviate AR via regulating RELA-regulated response of IFNG/IRF1 axis

4. Discussion

Declarations

References

Additional Declarations

Supplementary Files

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