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Exploring plasma metabolomic changes in sepsis: a clinical matching study based on gas chromatography-mass spectrometry.
Lin, Shi-Hui; Fan, Jing; Zhu, Jing; Zhao, Yi-Si; Wang, Chuan-Jiang; Zhang, Mu; Xu, Fang.
Afiliação
  • Lin SH; Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Fan J; Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Zhu J; Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Zhao YS; Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Wang CJ; Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Zhang M; Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Xu F; Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Ann Transl Med ; 8(23): 1568, 2020 Dec.
Article em En | MEDLINE | ID: mdl-33437767
ABSTRACT

BACKGROUND:

Sepsis is a deleterious systemic inflammatory response to infection, and despite advances in treatment, the mortality rate remains high. We hypothesized that plasma metabolism could clarify sepsis in patients complicated by organ dysfunction.

METHODS:

Plasma samples from 31 patients with sepsis and 23 healthy individuals of comparable age, gender, and body mass index (BMI) were collected. Plasma metabolites were detected through gas chromatography-mass spectrometry (GC-MS), and relevant metabolic pathways were predicted using the Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway database. Student's t-test was employed for statistical analysis. In addition, to explore sepsis organ dysfunction, plasma samples of sepsis patients were further analyzed by metabolomics subgroup analysis according to organ dysfunction.

RESULTS:

A total of 222 metabolites were detected, which included 124 metabolites with statistical significance between the sepsis and control groups. Among these, we found 26 were fatty acids, including 3 branched fatty acids, 10 were saturated fatty acids, and 13 were unsaturated fatty acids that were found in sepsis plasma samples but not in the controls. In addition, 158 metabolic pathways were predicted, 74 of which were significant. Further subgroup analysis identified seven metabolites in acute kidney injury (AKI), three metabolites in acute respiratory distress syndrome (ARDS), seven metabolites in sepsis-induced myocardial dysfunction (SIMD), and four metabolites in acute hepatic ischemia (AHI) that were significantly different. The results showed that the sepsis samples exhibited extensive changes in amino acids, fatty acids, and tricarboxylic acid (TCA)-cycle products. In addition, three metabolic pathways-namely, energy metabolism, amino acid metabolism, and lipid metabolism-were downregulated in sepsis patients.

CONCLUSIONS:

The downregulated energy, amino acid, and lipid metabolism found in our study may serve as a novel clinical marker for the dysregulated internal environment, particularly involving energy metabolism, which results in sepsis.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article