Coordinated nasal mucosa-mediated immunity accelerates recovery from COVID-19.

ERJ open research(2024)

引用 0|浏览0
暂无评分
摘要
Introduction:Understanding the interplay of immune mediators in relation to clinical outcomes during acute infection has the potential to highlight immune networks critical to symptom recovery. The objective of the present study was to elucidate the immune networks critical to early symptom resolution following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods:In a community-based randomised clinical trial comparing inhaled budesonide against usual care in 139 participants with early onset SARS-CoV-2 (the STOIC study; clinicaltrials.gov identifier NCT04416399), significant clinical deterioration (reported need for urgent care, emergency department visit, hospitalisation: the primary outcome), self-reported symptom severity (Influenza Patient-Reported Outcome questionnaire) and immune mediator networks were assessed. Immune mediator networks were determined using pre-defined mathematical modelling of immune mediators, determined by the Meso Scale Discovery U-Plex platform, within the first 7 days of SARS-CoV-2 infection compared to 22 healthy controls. Results:Interferon- and chemokine-dominant networks were associated with high viral burden. Elevated levels of the mucosal network (chemokine (C-C motif) ligand (CCL)13, CCL17, interleukin (IL)-33, IL-5, IL-4, CCL26, IL-2, IL-12 and granulocyte-macrophage colony-stimulating factor) was associated with a mean 3.7-day quicker recovery time, with no primary outcome events, irrespective of treatment arm. This mucosal network was associated with initial nasal and throat symptoms at day 0. Conclusion:A nasal immune network is critical to accelerated recovery and improved patient outcomes in community-acquired viral infections. Overall, early prognostication and treatments aimed at inducing epithelial responses may prove clinically beneficial in enhancing early host response to virus.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要