Targeted Metabolomic Biomarkers for Stroke Subtyping.

Area of Science:

• Biochemistry
• Neurology
• Medical Diagnostics

Background:

• Ischemic stroke is a complex condition with diverse causes, making accurate subtyping challenging.
• Current methods for classifying stroke etiologies are often inefficient and expensive.
• Metabolite-based biomarkers show potential for improving stroke classification and personalizing treatment strategies.

Purpose of the Study:

• To discover novel, targeted metabolomics-based biomarkers.
• To differentiate between large-artery atherosclerosis (LAA) and cardioembolic (CE) stroke subtypes.
• To establish a more efficient diagnostic approach for ischemic stroke.

Main Methods:

• Serum samples and clinical data were collected from 346 participants, including LAA, CE stroke patients, and healthy controls.
• Targeted metabolomic analysis was performed using liquid chromatography-tandem mass spectrometry.
• A multivariate regression model was developed to identify discriminatory metabolomic signatures.

Main Results:

• Six specific metabolites (lysine, serine, threonine, kynurenine, putrescine, lysophosphatidylcholine acyl C16:0) were identified as discriminators between LAA and CE strokes.
• These biomarkers remained significant after adjusting for clinical factors like age, sex, and stroke severity.
• The diagnostic performance of these metabolite combinations was successfully validated in an independent test set.

Conclusions:

• Significant differences in metabolite profiles exist between LAA and CE stroke subtypes.
• Targeted metabolomics offers a valuable tool for enhancing the diagnostic accuracy of ischemic stroke classification.
• Further research into the pathophysiological roles of these identified metabolites is warranted.