Abstract
Introduction
Acute ischemic stroke (AIS) accounts for the majority of all stroke, globally the second leading cause of death. Due to its rapid development after onset, its early diagnosis is crucial.
Objectives
We aim to identify potential highly reliable blood-based biomarkers for early diagnosis of AIS using quantitative plasma lipid profiling via a machine learning approach.
Methods
Lipidomics was used for quantitative plasma lipid profiling, based on ultra-performance liquid chromatography tandem mass spectrometry. Our samples were divided into a discovery and a validation set, each containing 30 AIS patients and 30 health controls (HC). Differentially expressed lipid metabolites were screened based on the criteria VIP > 1, p < 0.05, and fold change > 1.5 or < 0.67. The least absolute shrinkage and selection operator (LASSO) and random forest algorithms in machine learning were used to select differential lipid metabolites as potential biomarkers.
Results
Three key differential lipid metabolites, CarnitineC10:1, CarnitineC10:1-OH and Cer(d18:0/16:0), were identified as potential biomarkers for early diagnosis of AIS. The former two, associated with thermogenesis, were down-regulated, whereas the latter, associated with necroptosis and sphingolipd metabolism, was upregulated. Univariate and multivariate logistic regressions showed that these three lipid metabolites and the resulting diagnostic model exhibited a strong ability in discriminating between AIS patients and HCs in both the discovery and validation sets, with an area under the curve above 0.9.
Conclusions
Our work provides valuable information on the pathophysiology of AIS and constitutes an important step toward clinical application of blood-based biomarkers for diagnosing AIS.
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Data Availability
The original contributions presented in the study are included in the article. Data not provided in the article because of space limitations may be shared (anonymized) at the request of any qualified investigator for purposes of replicating procedures and results. Further inquiries can be directed to the corresponding author.
Abbreviations
- AIS:
-
Acute ischemic stroke
- AMI:
-
Acute myocardial infarction
- AUC:
-
Area under the curve
- CAR:
-
Carnitine
- Cer:
-
Ceramide
- CerP:
-
Ceramide 1-phosphate
- DA:
-
Differential abundance
- ESI:
-
Electrospray ionization
- FC:
-
Fold change
- FFA:
-
Free fatty acid
- GPI:
-
Glycosylphosphatidylinositol
- HC:
-
Healthy control
- HDL-C:
-
High-density lipoprotein cholesterol
- ICH:
-
Intracerebral haemorrhage
- KEGG:
-
Kyoto Encyclopedia of genes and genomes
- LASSO:
-
Least absolute shrinkage and selection operator
- LDL-C:
-
Low density lipoprotein cholesterol
- MS/MS:
-
Tandem mass spectrometry
- OPLS-DA:
-
Orthogonal partial least squares discriminant analysis
- PA:
-
Phosphatidic acid
- PC:
-
Phosphatidylcholine
- PCA:
-
Principal component analysis
- PE:
-
Phosphatidyl ethanolamine
- PE-O:
-
Phosphatidylethanolamine-ethers
- RF:
-
Random forest
- ROC:
-
Receiver operating characteristic
- TC:
-
Total cholesterol
- TG:
-
Triglycerides
- UPLC:
-
Ultra-performance liquid chromatography
- VIP:
-
Variable importance in projection
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Acknowledgements
We thank Qiang Wang at Yangjiang People’s Hospital for his help in sample collection.
Funding
This work was financially supported in part by the Key Projects of Natural Science Foundation of Yangjiang People’s Hospital (Grant Nos. 10, 11, and 14).
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JCL conceived the study and oversaw the project, YY, XW, and JL drafted the manuscript. YY, JL, XW, HFL, SWL, and QGX participated in sample collection, data analysis and discussions. JCL and YY proofread and polished the manuscript. All authors read and approved the final manuscript.
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All procedures followed in this study were in accordance with the ethical standards of the committee on human experimentation (Yangjiang People’s Hospital, China) and with the Helsinki Declaration of 1975, as revised in 2000(5). Written informed consent was obtained from all participants for being included in the study.
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Yu, Y., Wen, X., Lin, JG. et al. Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics. Metabolomics 19, 32 (2023). https://doi.org/10.1007/s11306-023-01990-3
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DOI: https://doi.org/10.1007/s11306-023-01990-3