Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.
Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.
复制标题
基于尿液的 COVID-19 和细菌败血症引起的 ARDS 的多组学比较分析。
DOI：
10.1101/2022.08.10.22277939
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Choi,Augu
中科院分区：
文献类型：
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作者：
Batra,Richa;Uni,Rie;Akchurin,OlehM;Alvarez-Mulett,Sergio;Gómez-Escobar,LuisG;Patino,Edwin;Hoffman,KatherineL;Simmons,Will;Chetnik,Kelsey;Buyukozkan,Mustafa;Benedetti,Elisa;Suhre,Karsten;Schenck,Edward;Cho,SooJung;Choi,Augu
研究背景急性呼吸窘迫综合征（ARDS）是COVID-19的常见并发症，是危重症期间危及生命的疾病。它可能源于各种疾病病因，包括严重感染、严重损伤或吸入刺激物。由于缺乏病因特异性治疗、多系统受累和异质性、患者预后差，ARDS带来了巨大的临床挑战。ARDS组的分子比较有可能揭示ARDS发病机制的共同和不同机制。MethodsWe进行了COVID-19 ARDS患者（n = 42）和细菌败血症诱导的ARDS患者（n = 17）的尿代谢组学和蛋白质组学谱的比较分析。为此，我们使用了两种不同的方法，第一，我们比较了分子组学档案之间的ARDS组，第二，我们相关的临床表现，每组与组学profiles.ResultsThe比较两个ARDS病因确定了150个代谢产物和70个蛋白质，这两组之间的差异丰富。基于这些发现，我们通过多组学网络方法探讨了细胞粘附/细胞外基质分子、炎症和线粒体功能障碍在ARDS发病机制中的相互作用。此外，我们确定了与COVID-19 ARDS患者死亡率相关的蛋白质组学特征，其中包含几种以前与ARDS发病机制相关的临床表现中涉及的蛋白质。线粒体功能障碍在ARDS发病中的作用。蛋白质组死亡率特征应在未来的研究中进一步研究，以开发COVID-19患者结局的预测模型。
BackgroundAcute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis.MethodsWe performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). To this end, we used two different approaches, first we compared the molecular omics profiles between ARDS groups, and second, we correlated clinical manifestations within each group with the omics profiles.ResultsThe comparison of the two ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis.ConclusionIn summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.