Metabolomic analysis reveals potential biomarkers and serum metabolomic profiling in spontaneous intracerebral hemorrhage patients using UPLC/quadrupole time‐of‐flight MS. (3rd October 2021)

• Record Type: Journal Article
• Authors: Sun, Guozhang; Jiang, Fengling; Hu, Shaoshan; Cheng, Huakun; Qu, Lianlong; Tao, Yu; Ma, Bowen
• Is Part Of: Biomedical chromatography. Volume 36:Number 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-03
• Subjects: biomarkers -- intracerebral hemorrhage -- metabolomic profiling -- metabolomics -- UPLC/Q‐TOF; Chromatographic analysis -- Periodicals; Biology -- Periodicals; Medicine -- Periodicals; Biology -- Periodicals; Chromatography -- methods -- Periodicals; Medicine -- Periodicals; 543.089
• DOI: 10.1002/bmc.5241
• Languages: English
• ISSNs: 0269-3879

Abstract

Abstract: Spontaneous intracerebral hemorrhage (ICH) accounts for 10–20% of all strokes and contributes to higher mortalities and severe disabilities. The aims of this study were, therefore, to characterize novel biomarkers, metabolic disruptions, and mechanisms involving ICH. A total 30 ICH patients and 30 controls were enrolled in the study, and their clinical characteristics were analyzed. Nontargeted metabolomic analysis was conducted using ultra‐performance liquid chromatography quadrupole time‐of‐flight tandem mass spectrometry (UPLC/Q‐TOF). Multivariate statistical analysis and receiver operating characteristic curve analysis were used for screening and evaluating the predictive ability of biomarkers. ICH patients showed significantly higher systolic blood pressure, diastolic blood pressure, blood glucose levels, white blood cell counts, neutrophil count, percentage of neutrophils and globulin and a lower albumin/globin ratio when compared with controls. In sum, 11 important metabolites were identified, which were associated with disruption of fatty acid oxidation and sphingolipid and phospholipid metabolism, as well as increased inflammation, oxidative stress, and vascular pathologies. Further multiple logistic regression analyses of these metabolites showed that l ‐carnitine and phosphatidylcholine (20:3/22:6) have potential as biomarkers of ICH, and the area under the curve, sensitivity, specificity were 0.974, 90%, and 93%, respectively. These findings provide insights into the pathogenesis, early prevention, and diagnosis of ICH.