哮喘
过敏性
医学
逻辑回归
免疫学
免疫球蛋白E
内科学
抗体
作者
Gordon Smilnak,Yura Lee,Abhijnan Chattopadhyay,Annah B. Wyss,Julie D. White,Sinjini Sikdar,Jianping Jin,Andrew J. Grant,Alison A. Motsinger‐Reif,Jian‐Liang Li,Mi Kyeong Lee,Bing Yu,Stephanie J. London
出处
期刊:Allergy
[Wiley]
日期:2024-01-23
摘要
Abstract Background Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma. Methods Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non‐case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non‐case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta‐analyzed using inverse‐variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with atopy ( n = 207), asthma without atopy ( n = 554), atopy without asthma ( n = 147), compared to neither ( n = 948)). Results Meta‐analysis of 4860 proteins identified 115 significantly (FDR<0.05) associated with asthma. Multiple signaling pathways related to airway inflammation and pulmonary injury were enriched (FDR<0.05) among these proteins. A proteomic score generated using machine learning provided predictive value for asthma (AUC = 0.77, 95% CI = 0.75–0.79 in training set; AUC = 0.72, 95% CI = 0.69–0.75 in validation set). Twenty proteins are targeted by approved or investigational drugs for asthma or other conditions, suggesting potential drug repurposing. The combined asthma‐atopy phenotype showed significant associations with 20 proteins, including five not identified in the overall asthma analysis. Conclusion This first large‐scale proteomics study identified over 100 plasma proteins associated with current asthma in adults. In addition to validating previous associations, we identified many novel proteins that could inform development of diagnostic biomarkers and therapeutic targets in asthma management.
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