AUTHOR=Yu Fang , Feng Xianjing , Li Xi , Liu Zeyu , Liao Di , Luo Yunfang , Wei Minping , Huang Qin , Zhang Lin , Xia Jian TITLE=Association of Plasma Metabolic Biomarker Sphingosine-1-Phosphate With Cerebral Collateral Circulation in Acute Ischemic Stroke JOURNAL=Frontiers in Physiology VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.720672 DOI=10.3389/fphys.2021.720672 ISSN=1664-042X ABSTRACT=

Background: The contribution of metabolic profile to the cerebral collateral circulation in acute ischemic stroke (AIS) has not been fully outlined. In this study, we conducted a metabolomic study to assess the relationship between the metabolic biomarkers and the collateral status of AIS.

Methods: A two-stage study was conducted from September 2019 to June 2021 in our hospital. There were 96 subjects including 66 patients with AIS and 30 healthy controls in the discovery stage and 80 subjects including 53 patients with AIS and 27 healthy controls in the validation stage. Collateral circulation was assessed by the Tan score based on computed tomographic angiography (CTA). Liquid chromatography-tandem mass spectrometry was used to identify differential metabolic markers. Then, an ELISA was employed to detect the plasma levels of sphingosine-1-phosphate (S1P).

Results:There were 114 differential metabolites between patients with AIS and control groups and 37 differential metabolites between good collateral circulation (GCC) and poor collateral circulation (PCC) groups. The pathway enrichment analysis revealed that arginine biosynthesis was the only statistically significant pathway between AIS and control groups and sphingolipid metabolism was the only statistically significant pathway between GCC and PCC groups. The differential metabolites sphinganine-1-phosphate (SA1P) and S1P belong to the sphingolipid metabolism. In the discovery stage, when the GCC group was compared with the PCC group, the receiver operating characteristic (ROC) analysis showed that plasma SA1P relative levels demonstrated an area under the curve (AUC) of 0.719 (95% CI: 0.582–0.834), and S1P levels demonstrated an AUC of 0.701 (95% CI: 0.567–0.819). In addition, both plasma SA1P and S1P relative levels showed significant negative correlations with the 90-day modified Rankin Scale (mRS) score. In the validation sample, higher plasma S1P levels were independent predictors of GCC (p = 0.014), and plasma S1P levels demonstrated an AUC of 0.738 (95% CI: 0.599–0.849) to differentiate patients with GCC from patients with PCC. In addition, plasma S1P levels also showed significant negative correlations with the 90-day mRS score.

Conclusion: We first illustrated the association between plasma metabolic profiles and cerebral collateral circulation in patients with AIS. Plasma S1P levels might be a potential diagnostic biomarker for predicting collateral circulation status in patients with AIS.