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Published on: September 2, 2010
Nontargeted metabolomics analysis of potential biomarkers for patients with chronic ischemic stroke in extremely cold
Li Bai1, Zhongyuan Li2, Jie Ge1
1Qiqihar Medical University, School of Public Health, Qiqihar, Heilongjiang, China.
Objective:
Chronic ischemic stroke (CIS) is a serious cardiovascular event, closely related to genetic and environmental factors in its occurrence and development. This study aims to reveal the potential impact of extreme cold environments on patients with CIS by comparing the metabolic characteristics of different populations, and to explore potential biomarkers and metabolic differences between Daur and Han CIS patients.
Methods:
A total of 32 patients with CIS and 32 matched by age, sex and race healthy controls were included in this study. Their demographic data were collected and clinical indicators were measured. The potentially differential expressed metabolites (DEMs) associated with CIS were identified using liquid chromatography-mass spectrometry (LC-MS/MS). Statistical analysis was performed using SPSS 22.0 and MetaboAnalyst 6.0.
Results:
1. There were statistically significant differences in urea nitrogen (P = 0.006), history of hypertension (P = 0.006), and history of diabetes (P = 0.046) between the patients with CIS and healthy controls. The association between a history of hypertension and CIS had an odds ratio of 4.023 (95% confidence interval 1.294-12.513). 2. Nontargeted metabolomics analysis identified 29 potential DEMs associated with CIS, which were further analyzed. A receiver operating characteristic (ROC) curve demonstrated the moderate performance (AUC = 0.750, accuracy rate = 66.5%) of these potential DEMs in identifying patients with CIS. The galactose metabolic pathway, as well as cysteine and methionine metabolism, were significantly different between the groups (P = 0.006 and P = 0.009, respectively). 3. Metabolomic analysis comparing Daur and Han patients with CIS identified 37 potential DEMs. A ROC curve for these potential DEMs was constructed (AUC = 0.942, accuracy rate = 87.4%). The metabolic pathways of cysteine and methionine metabolism, as well as arginine and proline metabolism, were significantly different between Daur and Han patients with CIS (P = 0.021 and P = 0.023, respectively).
Conclusion:
This exploratory study identified potential DEMs associated with CIS in populations from extremely cold rural regions and within the Daur ethnic subgroup. A preliminary ROC model constructed using these DEMs indicated their potential diagnostic value for CIS, though this requires further validation in large-scale, independent cohort studies.
