Proteomic Bronchiolitis Obliterans Syndrome Risk Monitoring in Lung Transplant Recipients
Proteomic Bronchiolitis Obliterans Syndrome Risk Monitoring in Lung Transplant Recipients
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DOI：
10.1097/tp.0b013e318224c109
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发表时间：
2011-08-27
期刊：
影响因子：
6.2
通讯作者：
von Neuhoff, Nils
中科院分区：
文献类型：
--
作者：
Wolf, Thomas;Oumeraci, Tonio;von Neuhoff, Nils
背景。闭塞性细支气管炎是肺移植受者长期生存的主要障碍，临床表现为闭塞性细支气管炎综合征（BOS）。本研究的主要目的是建立一种分子水平的筛选方法，通过用力呼气量替代标记物标准检测bos诊断前的相关蛋白质组变化。在肺移植后12至48个月的不同时间点对82例肺移植受者（48/34例有/未发生BOS）进行支气管肺泡灌洗。设计了一种基于质谱的方法来生成支气管肺泡灌洗液蛋白质组谱，筛选bos特异性改变。通过凝胶内消化、串联质谱测序和定量免疫分析，鉴定并验证了具有统计学意义的标记肽和蛋白质。在这组具有统计学意义的标志物中，有克拉拉细胞蛋白、钙粒蛋白A、人中性粒细胞肽和抗菌药物组蛋白。为了评估它们的临床相关性，我们开发了一个高度敏感和特异性的分类器模型。7种多肽监测的BOS阳性分类与BOS自由时间的显著减少密切相关。因此，在发病过程早期发现高危患者是可能的。通过基质辅助激光解吸/电离飞行时间质谱法监测支气管肺泡灌洗液中7种多肽的水平，可以使用基于随机森林决策树的分类器模型可靠地预测早期BOS。该稳健模型的高准确性及其协同潜力与已建立的基于强迫呼气量的诊断相结合，可以使其成为多中心验证后补充当前诊断方案的有效工具。
Background. Obliterative bronchiolitis poses a primary obstacle for long-term survival of lung transplant recipients and manifests clinically as bronchiolitis obliterans syndrome (BOS). Establishing a molecular level screening method to detect BOS-related proteome changes before its diagnosis by forced expiratory volume surrogate marker criteria was the main objective of this study.Methods. Bronchoalveolar lavage was performed in 82 lung transplant recipients (48/34 with/without known BOS development) at different time points between 12 and 48 months after lung transplantation. A mass spectrometry-based method was devised to generate bronchoalveolar lavage fluid proteome profiles that were screened for BOS-specific alterations. Statistically significant marker peptides and proteins were identified and validated by in-gel digestion, tandem mass spectrometric sequencing, and quantitative immunoassays.Results. Among the panel of statistically significant markers were Clara cell protein, calgranulin A, human neutrophil peptides, and the antimicrobial agent histatin. To assess their clinical relevance, a highly sensitive and specific classifier model was developed. Positive BOS classification by monitoring of seven polypeptides correlated strongly with a significant decrease in BOS-free time. Thus, it was possible to detect high-risk patients early on in the pathogenetic process.Conclusions. Monitoring the bronchoalveolar lavage fluid levels of seven polypeptides detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry allows a reliable prediction of early BOS using a Random Forest decision tree-based classifier model. The high accuracy of this robust model and its synergistic potential in combination with established forced expiratory volume-based diagnostics could make it an effective tool to supplement the current diagnostic regime after multicentric validation.