Key result
A six-metabolite random forest model distinguishes cardioembolic from large artery atherosclerotic thrombi with ~0.89 AUC.
Why the study?
The diagnosis of cerebral thrombosis origin remains challenging and unclear, necessitating new approaches to distinguish cardioembolism and large artery atherosclerosis thrombi.
Can distinct metabolites in extracted cerebral thrombi distinguish between cardioembolism and large artery atherosclerosis origins?
Observational (n=48)
Can distinct metabolites in extracted cerebral thrombi distinguish between cardioembolism and large artery atherosclerosis origins?
Metabolomic profiling of extracted cerebral thrombi can accurately distinguish between cardioembolic and large artery atherosclerotic etiologies, potentially aiding in secondary stroke prevention.
Answers are grounded in this paper and cite their sources.
Metabolite profiling of retrieved thrombi may aid etiology classification; leaves open whether it can guide secondary prevention strategies.
BACKGROUND: The diagnosis of cerebral thrombosis origin is challenging and remains unclear. This study aims to identify thrombosis due to cardioembolism (CE) and large artery atherosclerosis (LAA) from a new perspective of distinct metabolites. METHODS: Distinct metabolites between 26 CE and 22 LAA origin thrombi, which were extracted after successful mechanical thrombectomy in patients with acute ischemic stroke in the anterior circulation, were analyzed with a ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) system. Enriched metabolic pathways related to the metabolites were identified. Least absolute shrinkage selection operator regression analyses and a filtering method were used to select potential predictors. Furthermore, four machine learning classifiers, including decision tree, logistic regression, random forest (RF), and k means unsupervised classification model, were used to evaluate the predictive ability of the selected metabolites. RESULTS: UPLC-QTOF-MS analysis revealed that levels of 88 and 55 metabolites were elevated in LAA and CE thrombi, respectively. Kyoto Encyclopedia of Genes and Genomes analysis revealed a significant difference between the pathways enriched in the two types of thrombi. Six metabolites (diglyceride (DG, 18:3/24:0), DG (22:0/24:0), phytosphingosine, galabiosylceramide (18:1/24:1), triglyceride (15:0/16:1/o-18:0), and glucosylceramide (18:1/24:0)) were finally selected to build a predictive model. The predictive RF model was confirmed to be the best, with a satisfactory stability and prediction capacity (area under the curve=0.889). CONCLUSIONS: Six metabolites as potential predictors for distinguishing between cerebral thrombi of CE and LAA origin were identified. The results are useful for understanding the pathogenesis and for secondary stroke prevention.
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Li et al. (2022) conducted an observational in Acute ischemic stroke in the anterior circulation (n=48). Cardioembolism (CE) origin vs. Large artery atherosclerosis (LAA) origin was evaluated on Distinguishing between cerebral thrombi of CE and LAA origin (AUC 0.889). A random forest model using six distinct metabolites distinguished between cerebral thrombi of cardioembolic and large artery atherosclerosis origin with an area under the curve of 0.889.
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