Plasma Metabolic Profile Determination in Young ST-segment Elevation Myocardial Infarction Patients with Ischemia and Reperfusion: Ultra-performance Liquid Chromatography and Mass Spectrometry for Pathway Analysis.
- Author:
Lei HUANG
;
Tong LI
1
;
Ying-Wu LIU
;
Lei ZHANG
;
Zhi-Huan DONG
;
Shu-Ye LIU
;
Ying-Tang GAO
Author Information
- Publication Type:Journal Article
- MeSH: Adolescent; Adult; Aged; Aged, 80 and over; Area Under Curve; Chromatography, High Pressure Liquid; methods; Humans; Least-Squares Analysis; Mass Spectrometry; methods; Myocardial Ischemia; metabolism; Myocardial Reperfusion; ST Elevation Myocardial Infarction; metabolism; Sphingolipids; metabolism
- From: Chinese Medical Journal 2016;129(9):1078-1086
- CountryChina
- Language:English
-
Abstract:
BACKGROUNDThis study was to establish a disease differentiation model for ST-segment elevation myocardial infarction (STEMI) youth patients experiencing ischemia and reperfusion via ultra-performance liquid chromatography and mass spectrometry (UPLC/MS) platform, which searches for closely related characteristic metabolites and metabolic pathways to evaluate their predictive value in the prognosis after discharge.
METHODSForty-seven consecutive STEMI patients (23 patients under 45 years of age, referred to here as "youth," and 24 "elderly" patients) and 48 healthy control group members (24 youth, 24 elderly) were registered prospectively. The youth patients were required to provide a second blood draw during a follow-up visit one year after morbidity (n = 22, one lost). Characteristic metabolites and relative metabolic pathways were screened via UPLC/MS platform base on the Kyoto encyclopedia of genes and genomes (KEGG) and Human Metabolome Database. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive value of characteristic metabolites in the prognosis after discharge.
RESULTSWe successfully established an orthogonal partial least squares discriminated analysis model (R2X = 71.2%, R2Y = 79.6%, and Q2 = 55.9%) and screened out 24 ions; the sphingolipid metabolism pathway showed the most drastic change. The ROC curve analysis showed that ceramide [Cer(d18:0/16:0), Cer(t18:0/12:0)] and sphinganine in the sphingolipid pathway have high sensitivity and specificity on the prognosis related to major adverse cardiovascular events after youth patients were discharged. The area under curve (AUC) was 0.671, 0.750, and 0.711, respectively. A follow-up validation one year after morbidity showed corresponding AUC of 0.778, 0.833, and 0.806.
CONCLUSIONSBy analyzing the plasma metabolism of myocardial infarction patients, we successfully established a model that can distinguish two different factors simultaneously: pathological conditions and age. Sphingolipid metabolism is the top most altered pathway in young STEMI patients and as such may represent a valuable prognostic factor and potential therapeutic target.