预测未控制型哮喘未来急性加重：基于大规模临床蛋白质组学的探索/验证方法
2025/04/06
摘要
背景：哮喘急性加重显著增加疾病负担。部分患者易反复发作，但其潜在机制尚未明确。本研究旨在开发与未来急性加重相关的痰液蛋白质标志谱。
方法：从AMAZES研究的对照组（安慰剂组）中选取22例基线痰液样本，采用优化高通量质谱法进行分析。
结果：以对数倍变化≥1.5且p值≤0.05为阈值，单变量分析发现，未来48周内是否发生急性加重的患者之间存在533种差异表达的痰液蛋白质。通过稀疏偏最小二乘法（sPLS-DA）构建的260种蛋白质多变量标志谱，可部分预测急性加重风险，受试者工作特征曲线下面积（AUC）为0.95，错误率为0.41。进一步选取20种关键蛋白，在123例新增样本中进行验证与定量。最终确认9种蛋白质与未来急性加重风险相关，验证模型的AUC为0.77，错误率0.40。通路分析显示，急性加重相关机制涉及炎症反应、免疫细胞募集及增殖。
结论：本研究首次揭示了与哮喘未来急性加重相关的痰液蛋白质组学标志及通路，将为未控制型持续性哮喘的生物标志物发现及新治疗靶点开发提供重要依据。
Predicting future exacerbations in uncontrolled asthma: a discovery/validation approach using large-scale clinical proteomics
Jurak LM, Yang IA, Simpson JL, Gibson PG, Hill MM, Upham JW
Abstract
BACKGROUND:Exacerbations contribute significantly to the burden of asthma. Some individuals are predisposed to recurring exacerbations however, the underlying mechanisms are not well understood. To generate a sputum protein signature associated with future exacerbations.
METHODS:22 baseline sputum samples from the control (placebo control) arm of the AMAZES study were analysed using an optimised high-throughput mass spectrometry method
RESULTS:Using a log-fold change of ≥ 1.5 and a p-value of 0.05 as cut-offs, univariate analysis identified 533 differentially abundant sputum proteins in participants with and without future exacerbations over the ensuring 48 weeks. A multivariate signature of 260 proteins for predicting future exacerbations was developed using sparse partial least squares data analysis, that was partially able to predict those who would likely experience an exacerbation with an area under the receiver-operating curve of 0.95 and an error rate of 0.41. Next, the 20 most influential proteins were selected for validation and quantification in sputum from an additional 123 participants. Upon validation, 9 proteins were found to be linked to future exacerbation risk. The final model could predict future exacerbations with an area under the receiver-operating curve of 0.77 with an error rate of 0.40. Pathway analysis revealed major themes associated with exacerbations including inflammation, recruitment, and proliferation of immune cells.
CONCLUSION:This study has identified for the first time a sputum proteomic signature and pathways associated with future exacerbations, which will facilitate the discovery of new biomarkers and novel therapeutic targets in uncontrolled persistent asthma.
背景：哮喘急性加重显著增加疾病负担。部分患者易反复发作，但其潜在机制尚未明确。本研究旨在开发与未来急性加重相关的痰液蛋白质标志谱。
方法：从AMAZES研究的对照组（安慰剂组）中选取22例基线痰液样本，采用优化高通量质谱法进行分析。
结果：以对数倍变化≥1.5且p值≤0.05为阈值，单变量分析发现，未来48周内是否发生急性加重的患者之间存在533种差异表达的痰液蛋白质。通过稀疏偏最小二乘法（sPLS-DA）构建的260种蛋白质多变量标志谱，可部分预测急性加重风险，受试者工作特征曲线下面积（AUC）为0.95，错误率为0.41。进一步选取20种关键蛋白，在123例新增样本中进行验证与定量。最终确认9种蛋白质与未来急性加重风险相关，验证模型的AUC为0.77，错误率0.40。通路分析显示，急性加重相关机制涉及炎症反应、免疫细胞募集及增殖。
结论：本研究首次揭示了与哮喘未来急性加重相关的痰液蛋白质组学标志及通路，将为未控制型持续性哮喘的生物标志物发现及新治疗靶点开发提供重要依据。
（中日友好医院呼吸与危重症医学科 沈焜路 摘译 林江涛 审校）
（J Allergy Clin Immunol. 2025 Mar 4; DOI: 10.1016/j.jaci.2025.02.028）
Predicting future exacerbations in uncontrolled asthma: a discovery/validation approach using large-scale clinical proteomics
Jurak LM, Yang IA, Simpson JL, Gibson PG, Hill MM, Upham JW
Abstract
BACKGROUND:Exacerbations contribute significantly to the burden of asthma. Some individuals are predisposed to recurring exacerbations however, the underlying mechanisms are not well understood. To generate a sputum protein signature associated with future exacerbations.
METHODS:22 baseline sputum samples from the control (placebo control) arm of the AMAZES study were analysed using an optimised high-throughput mass spectrometry method
RESULTS:Using a log-fold change of ≥ 1.5 and a p-value of 0.05 as cut-offs, univariate analysis identified 533 differentially abundant sputum proteins in participants with and without future exacerbations over the ensuring 48 weeks. A multivariate signature of 260 proteins for predicting future exacerbations was developed using sparse partial least squares data analysis, that was partially able to predict those who would likely experience an exacerbation with an area under the receiver-operating curve of 0.95 and an error rate of 0.41. Next, the 20 most influential proteins were selected for validation and quantification in sputum from an additional 123 participants. Upon validation, 9 proteins were found to be linked to future exacerbation risk. The final model could predict future exacerbations with an area under the receiver-operating curve of 0.77 with an error rate of 0.40. Pathway analysis revealed major themes associated with exacerbations including inflammation, recruitment, and proliferation of immune cells.
CONCLUSION:This study has identified for the first time a sputum proteomic signature and pathways associated with future exacerbations, which will facilitate the discovery of new biomarkers and novel therapeutic targets in uncontrolled persistent asthma.
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通过图形和流形分析探索过敏致敏和哮喘的时间相互作用
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1岁前呼吸道与非呼吸道症状对学龄期哮喘的预测价值
