Steroid Resistance of Severe Asthma - Mechanisms and Therapeutic Targets
Proceedings for Annual Meeting of The Japanese Pharmacological Society(2022)
摘要
Asthma therapy in general has improved a lot in recent years, but it is still a major problem that severe asthma, which accounts for 10 to 20%, still suffers from strong symptoms on a daily basis despite all therapeutic agents used in combination. American SARP and European ENFUMOSA started in 2000 to advance pathophysiological insights of severe asthma. Clinical usage of antibodies and inhibitors against IgE, TNF, IL-5, IL-4, IL-13, and TSLP are also accumulating. Some of these molecular-targeted drugs improve respiratory function and reduce acute exacerbations in patients with severe asthma. Until now, cytokines have been assumed to be involved in chronic inflammation, but it is also interesting to elucidate the pathways of how cytokines are involved in respiratory function and acute exacerbations. We registered approximately 100 steroid-dependent asthma patients in Japan. Although long-lasting poor control of the disease was considered the cause of severe asthma in the past, steroid dependence in one third of the cases occurred within 2-3 years after the onset. Steroid resistance seems a key process from the early stage of the disease. Steroid resistance of T cell level was induced by extracellular co-stimulation and cytokine signals. The inhibition may improve steroid sensitivity and treat steroid-resistant asthma. Therefore, we established a steroid-resistant asthma model for the first time by transferring steroid resistant T cell clones, and analyzed the steroid sensitivity recovery effect of CTLA4-Ig. In addition, a multicenter, double-blind, placebo-controlled exploratory trial was performed as a POC study investigating the efficacy of abatacept in treatment-resistant severe asthma. Elucidation of the pathophysiology and mechanism by which steroids do not work is expected to be a breakthrough for the prevention and treatment of severe asthma.
更多查看译文
关键词
Asthma,Treatment
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn