Molecular characterization of pulmonary edema: a window to an injured lung

急性呼吸窘迫综合征(ARDS)是一种异质性的、危及生命的疾病，由 在大多数研究中，氧合不良和双侧肺水肿会导致40%的死亡率。每个 到目前为止，ARDS药物试验已经失败，可能是因为定义ARDS的临床标准包括大量的 低风险患者的子集。临床评分系统不能很好地预测哪些ARDS患者会长期发生ARDS 呼吸衰竭，死亡风险增加。 肺水肿液的分子图谱可以作为了解肺泡微环境的窗口， 能够识别高危患者。肺水肿直接反映了肺的病理生理学，包括肺损失 屏障的完整性、炎症和上皮损伤。不幸的是，自由流行性肺水肿 临床用途有限，因为它只能在少数患者中捕获。分子生物学特性的研究 由于两项关键的创新，现在每个ARDS患者都有可能出现肺水肿。首先，我们 发现呼吸机HME(热湿交换器)过滤器内有水肿液凝结 通常被当作垃圾丢弃的电路，与自由流动的水肿密切相关。第二，我们开发了一种无针对性的 利用质谱学表征痕量分子组成的代谢组指纹图谱方法 液体的数量。总而言之，这些创新使得有可能检验分子 水肿液的特征反映了病理生物学，并使ARDS风险分层成为可能。 为了解决HME水肿液对预后的预测潜力，300名早期ARDS患者将 在3个美国中心招募，采用程序化的HME水肿液收集。目标1是研究高HME是否 水肿液总蛋白和肺损伤特异性蛋白可预测急性呼吸窘迫综合征患者持续48小时的呼吸衰竭≥。 目的2是测试高代谢水肿液和炎性脂类是否可以预测呼吸延长 ARDS中的≥48h失败。在目标3中，套索机器学习将用于集成所有蛋白质组和 代谢性水肿表现为延长的机械通气分类器。分类器的健壮性 将通过测量它是否增加了临床ARDS严重程度评分的预后价值进行评估，确定 关键分子特征在血浆中的反映情况如何，以及在独立队列中进行复制测试。 这些研究的目标是检查一种新的和容易获得的肺部特异性样本的程度， 在ARDS病程早期获得的，反映了生物学，可以预测ARDS的结果，从而提供 为未来的临床试验丰富预后。具体目标的成功完成提供了潜力 为一个急需的分类方案，以更好地提炼、理解和治疗靶向ARDS。

Acute respiratory distress syndrome (ARDS) is a heterogeneous, life-threatening condition defined by poor oxygenation and bilateral pulmonary edema that carries a mortality rate >40% in most studies. Every ARDS drug trial to date has failed, perhaps because the clinical criteria defining ARDS include a substantial subset of low-risk patients. Clinical scoring systems poorly predict which ARDS patients will develop prolonged respiratory failure and are at increased risk of death. Molecular profiling of pulmonary edema fluid could serve as a window on the alveolar microenvironment, enabling identification of high-risk patients. Pulmonary edema directly reflects lung pathobiology including loss of barrier integrity, inflammation, and epithelial damage. Unfortunately, free-flowing pulmonary edema has limited clinical utility because it can only be captured in a minority of patients. Molecular characterization of pulmonary edema is now possible in every patient with ARDS because of two critical innovations. First, we discovered that edema fluid condensing in the HME (heat and moisture exchanger) filter of the ventilator circuit, usually discarded as trash, closely reflects free-flowing edema. Second, we developed a non-targeted metabolomic fingerprinting method using mass spectroscopy that characterizes molecular components in trace quantities of fluid. Together, these innovations make it possible to test the central hypothesis that molecular features of edema fluid reflect pathobiology and enable ARDS risk stratification. To address the prognostic enrichment potential of HME edema fluid, 300 early ARDS patients will be recruited at 3 US centers, with protocolized HME edema fluid collection. Aim 1 is to study whether high HME edema fluid total protein and lung-injury specific proteins predict prolonged respiratory failure ≥48h in ARDS. Aim 2 is to test whether hypermetabolic edema fluid and inflammatory lipids predict prolonged respiratory failure ≥48h in ARDS. In Aim 3, LASSO machine learning will be used to integrate all proteomic and metabolomic edema features into a prolonged mechanical ventilation classifier. The robustness of the classifier will be assessed by measuring whether it adds prognostic value to clinical ARDS severity scores, identifying how well key molecular features are reflected in plasma, and testing for replication in an independent cohort. The goal of these studies is to examine to what extent a novel and readily available lung-specific sample, obtained early in the course of ARDS, reflects biology and can predict ARDS outcomes, thus offering prognostic enrichment for future clinical trials. Successful completion of the Specific Aims offers the potential for a much-needed classification scheme to better refine, understand, and therapeutically-target ARDS.