Explore potential plasma biomarkers of acute respiratory distress syndrome (ARDS) using GC-MS metabolomics analysis
Explore potential plasma biomarkers of acute respiratory distress syndrome (ARDS) using GC-MS metabolomics analysis
复制标题
使用 GC-MS 代谢组学分析探索急性呼吸窘迫综合征 (ARDS) 的潜在血浆生物标志物
DOI：
10.1016/j.clinbiochem.2019.02.009
复制
发表时间：
2019-04-01
影响因子：
2.8
通讯作者：
Xu, Fang
中科院分区：
文献类型：
--
作者：
Lin, Shihui;Yue, Xi;Xu, Fang
目的：本研究的目的是分析代谢组学的急性呼吸窘迫综合征（ARDS）患者的代谢标志物的识别与潜在的诊断和预后value.Methods：入组的受试者包括成人患者符合柏林的定义和健康对照组匹配的基础上，年龄，性别和体重指数（BMI）。收集37例ARDS患者和28例健康对照者的血浆样品。采用气相色谱-质谱联用技术（GC-MS）检测血浆代谢产物，并利用京都基因与基因组百科全书（KEGG）数据库预测代谢途径。苯丙氨酸、天冬氨酸和氨基甲酸水平在从轻度到重度分类的所有ARDS患者组之间存在显著差异。此外，四种代谢物，鸟氨酸，辛酸，氮杂环丁烷，亚氨基二乙酸，可以作为生物标志物，潜在地预测ARDS的严重程度。我们发现92个途径，是显着不同的ARDS和对照组，包括57个途径与metabolis.Conclusions：血浆代谢组学可能会提高我们的理解ARDS生物学。与缺氧相关的特定产物可作为预测ARDS的早期生物标志物，而与动脉氧分压（PaO 2）/吸入氧百分比（FiO（2））显著相关的代谢产物可能在确定ARDS严重程度方面发挥作用。这项研究表明，代谢组学分析在危险的ARDS患者或那些早期的ARDS可能提供新的见解疾病的发病机制或预后。
Objectives: The aim of this study was to analyse the metabolomics of patients with acute respiratory distress syndrome (ARDS) for the identification of metabolic markers with potential diagnostic and prognostic value.Methods: The enrolled subjects included adult patients with ARDS that met the Berlin definition and healthy controls matched based on age, gender, and body mass index (BMI). Plasma samples were collected from 37 patients with ARDS and 28 healthy controls. The plasma metabolites were detected with gas chromatography-mass spectrometry (GC-MS), and the relevant metabolic pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.Results: A total of 222 metabolites were identified in our study, of which 128 were significantly altered in patients with ARDS compared with healthy controls. Phenylalanine, aspartic acid, and carbamic acid levels were significantly different between all groups of patients with ARDS classified from mild to severe. Furthermore, four metabolites, ornithine, caprylic acid, azetidine, and iminodiacetic acid, could serve as biomarkers to potentially predict the severity of ARDS. We discovered 92 pathways that were significantly different between ARDS and control groups, including 57 pathways linked to metabolism.Conclusions: Plasma metabolomics may improve our understanding of ARDS biology. Specific products related to hypoxia may serve as early biomarkers for ARDS prediction, while the metabolites with significant correlations with partial pressure of arterial oxygen (PaO2)/percentage of inspired oxygen (FiO(2)) may play a role in determining ARDS severity. This study suggests that metabolomic analysis in patients at risk of ARDS or those with early ARDS may provide new insight into disease pathogenesis or prognosis.