Abstract：
BACKGROUND: Icariin (ICA) inhibits inflammatory response in various diseases, but the mechanism underlying ICA treating airway inflammation in asthma needs further understood. We aimed to predict and validate the potential targets of ICA against asthma-associated airway inflammation using network pharmacology and experiments.
METHODS: The ovalbumin-induced asthma-associated airway inflammation mice model was established. The effects of ICA were evaluated by behavioral, airway hyperresponsiveness, lung pathological changes, inflammatory cell and cytokines counts. Next, the corresponding targets of ICA were mined via the SEA, CTD, HERB, PharmMapper, Symmap database and the literature. Pubmed-Gene and GeneCards databases were used to screen asthma and airway inflammation-related targets. The overlapping targets were used to build an interaction network, analyze gene ontology and enrich pathways. Subsequently, flow cytometry, quantitative real-time PCR and western blotting were employed for validation.
RESULTS: ICA alleviated the airway inflammation of asthma; 402 targets of ICA, 5136 targets of asthma and 4531 targets of airway inflammation were screened; 216 overlapping targets were matched and predicted ICA possesses the potential to modulate asthmatic airway inflammation by macrophage activation/polarization. Additionally, ICA decreased M1 but elevated M2. Potential targets that were disrupted by asthma inflammation were restored by ICA treatment.
CONCLUSIONS: ICA alleviates airway inflammation in asthma by inhibiting the M1 polarization of alveolar macrophages, which is related to metabolic reprogramming. Jun, Jak2, Syk, Tnf, Aldh2, Aldh9a1, Nos1, Nos2 and Nos3 represent potential targets of therapeutic intervention. The present study enhances understanding of the anti-airway inflammation effects of ICA, especially in asthma.
METHODS: The ovalbumin-induced asthma-associated airway inflammation mice model was established. The effects of ICA were evaluated by behavioral, airway hyperresponsiveness, lung pathological changes, inflammatory cell and cytokines counts. Next, the corresponding targets of ICA were mined via the SEA, CTD, HERB, PharmMapper, Symmap database and the literature. Pubmed-Gene and GeneCards databases were used to screen asthma and airway inflammation-related targets. The overlapping targets were used to build an interaction network, analyze gene ontology and enrich pathways. Subsequently, flow cytometry, quantitative real-time PCR and western blotting were employed for validation.
RESULTS: ICA alleviated the airway inflammation of asthma; 402 targets of ICA, 5136 targets of asthma and 4531 targets of airway inflammation were screened; 216 overlapping targets were matched and predicted ICA possesses the potential to modulate asthmatic airway inflammation by macrophage activation/polarization. Additionally, ICA decreased M1 but elevated M2. Potential targets that were disrupted by asthma inflammation were restored by ICA treatment.
CONCLUSIONS: ICA alleviates airway inflammation in asthma by inhibiting the M1 polarization of alveolar macrophages, which is related to metabolic reprogramming. Jun, Jak2, Syk, Tnf, Aldh2, Aldh9a1, Nos1, Nos2 and Nos3 represent potential targets of therapeutic intervention. The present study enhances understanding of the anti-airway inflammation effects of ICA, especially in asthma.
摘要：
背景：淫羊藿苷（ICA）抑制各种疾病的炎症反应，但ICA治疗哮喘气道炎症的潜在机制有待进一步了解。我们旨在通过网络药理学和实验来预测和验证ICA对抗哮喘相关气道炎症的潜在靶点。
方法：建立卵清蛋白诱导的哮喘相关气道炎症小鼠模型。ICA的影响是通过行为评估的，气道高反应性,肺病理变化，炎症细胞和细胞因子计数。接下来,ICA的相应目标是通过SEA开采的，CTD,HERB,PharmMapper,Symmap数据库和文献。Pubmed-Gene和GeneCards数据库用于筛选哮喘和气道炎症相关靶标。重叠的目标被用来建立一个互动网络，分析基因本体论并丰富通路。随后，流式细胞术,采用定量实时PCR和蛋白质印迹进行验证。
结果：ICA减轻了哮喘的气道炎症；ICA的402个靶标，筛选了5136个哮喘目标和4531个气道炎症目标；匹配了216个重叠目标，预测ICA具有通过巨噬细胞激活/极化调节哮喘气道炎症的潜力。此外,ICA降低M1但升高M2。通过ICA治疗，哮喘炎症破坏的潜在目标得以恢复。
结论：ICA通过抑制肺泡巨噬细胞M1极化减轻哮喘气道炎症,这与代谢重编程有关。Jun,Jak2Syk,Tnf,Aldh2、Aldh9a1、Nos1、Nos2和Nos3代表治疗干预的潜在目标。本研究增强了对ICA的抗气道炎症作用的理解，尤其是哮喘。
方法：建立卵清蛋白诱导的哮喘相关气道炎症小鼠模型。ICA的影响是通过行为评估的，气道高反应性,肺病理变化，炎症细胞和细胞因子计数。接下来,ICA的相应目标是通过SEA开采的，CTD,HERB,PharmMapper,Symmap数据库和文献。Pubmed-Gene和GeneCards数据库用于筛选哮喘和气道炎症相关靶标。重叠的目标被用来建立一个互动网络，分析基因本体论并丰富通路。随后，流式细胞术,采用定量实时PCR和蛋白质印迹进行验证。
结果：ICA减轻了哮喘的气道炎症；ICA的402个靶标，筛选了5136个哮喘目标和4531个气道炎症目标；匹配了216个重叠目标，预测ICA具有通过巨噬细胞激活/极化调节哮喘气道炎症的潜力。此外,ICA降低M1但升高M2。通过ICA治疗，哮喘炎症破坏的潜在目标得以恢复。
结论：ICA通过抑制肺泡巨噬细胞M1极化减轻哮喘气道炎症,这与代谢重编程有关。Jun,Jak2Syk,Tnf,Aldh2、Aldh9a1、Nos1、Nos2和Nos3代表治疗干预的潜在目标。本研究增强了对ICA的抗气道炎症作用的理解，尤其是哮喘。
