Association of Plasma Metabolic Biomarker Sphingosine-1-Phosphate With Cerebral Collateral Circulation in Acute Ischemic Stroke
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:...
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| Published in | Frontiers in physiology Vol. 12; p. 720672 |
|---|---|
| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Frontiers Media S.A
19.08.2021
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| Online Access | Get full text |
| ISSN | 1664-042X 1664-042X |
| DOI | 10.3389/fphys.2021.720672 |
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| 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. |
|---|---|
| AbstractList | 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. 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. 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.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. |
| Author | Wei, Minping Huang, Qin Xia, Jian Feng, Xianjing Liao, Di Liu, Zeyu Zhang, Lin Li, Xi Yu, Fang Luo, Yunfang |
| AuthorAffiliation | 1 Department of Neurology, Xiangya Hospital, Central South University , Changsha , China 3 National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University , Changsha , China 2 Clinical Research Center for Cerebrovascular Disease of Hunan Province, Central South University , Changsha , China |
| AuthorAffiliation_xml | – name: 2 Clinical Research Center for Cerebrovascular Disease of Hunan Province, Central South University , Changsha , China – name: 1 Department of Neurology, Xiangya Hospital, Central South University , Changsha , China – name: 3 National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University , Changsha , China |
| Author_xml | – sequence: 1 givenname: Fang surname: Yu fullname: Yu, Fang – sequence: 2 givenname: Xianjing surname: Feng fullname: Feng, Xianjing – sequence: 3 givenname: Xi surname: Li fullname: Li, Xi – sequence: 4 givenname: Zeyu surname: Liu fullname: Liu, Zeyu – sequence: 5 givenname: Di surname: Liao fullname: Liao, Di – sequence: 6 givenname: Yunfang surname: Luo fullname: Luo, Yunfang – sequence: 7 givenname: Minping surname: Wei fullname: Wei, Minping – sequence: 8 givenname: Qin surname: Huang fullname: Huang, Qin – sequence: 9 givenname: Lin surname: Zhang fullname: Zhang, Lin – sequence: 10 givenname: Jian surname: Xia fullname: Xia, Jian |
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| CitedBy_id | crossref_primary_10_1177_0271678X231194956 crossref_primary_10_1186_s12944_022_01762_3 crossref_primary_10_1161_JAHA_124_034170 crossref_primary_10_1002_wsbm_1553 crossref_primary_10_3389_fneur_2023_1153193 crossref_primary_10_3389_fneur_2022_1000992 crossref_primary_10_1007_s12975_021_00969_3 |
| Cites_doi | 10.1021/ac051437y 10.1016/j.bbrc.2011.08.070 10.1111/jnc.12836 10.3389/fneur.2019.01228 10.1161/STROKEAHA.120.029395 10.1016/j.neuropharm.2011.10.005 10.3390/ijms21176242 10.1007/s00018-018-2984-8 10.1161/STROKEAHA.119.027483 10.1161/STROKEAHA.110.595256 10.1161/CIRCULATIONAHA.115.016371 10.1161/STROKEAHA.110.592303 10.1007/s12975-018-0638-7 10.1038/labinvest.2010.102 10.1161/CIRCRESAHA.120.316711 10.1186/s12974-018-1323-1 10.1038/s41467-019-09550-x 10.1007/s12975-016-0477-3 10.1016/j.neuropharm.2017.08.003 10.1016/j.ejps.2017.05.003 10.1161/STROKEAHA.115.009009 10.1097/SHK.0b013e3181c02c1f 10.1002/ptr.7130. 10.6515/ACS.201809_34(5).20180405A 10.1093/intimm/dxz037 10.1074/jbc.M113.494740 10.1161/01.STR.0000086465.41263.06 10.1111/ene.13111 10.1016/j.tcb.2011.09.003 10.1002/ana.23906 10.1038/s41598-019-48609-z 10.1186/s12967-019-1962-8 10.1038/nrm.2017.107 10.1002/ana.25352 10.1016/j.jstrokecerebrovasdis.2016.12.021 10.1002/ana.22354 10.2174/0929867326666190308133732 |
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| Copyright | Copyright © 2021 Yu, Feng, Li, Liu, Liao, Luo, Wei, Huang, Zhang and Xia. Copyright © 2021 Yu, Feng, Li, Liu, Liao, Luo, Wei, Huang, Zhang and Xia. 2021 Yu, Feng, Li, Liu, Liao, Luo, Wei, Huang, Zhang and Xia |
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The contribution of metabolic profile to the cerebral collateral circulation in acute ischemic stroke (AIS) has not been fully outlined. In this... Background: The contribution of metabolic profile to the cerebral collateral circulation in acute ischemic stroke (AIS) has not been fully outlined. In this... |
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| Title | Association of Plasma Metabolic Biomarker Sphingosine-1-Phosphate With Cerebral Collateral Circulation in Acute Ischemic Stroke |
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