Faculty, Staff and Student Publications
Language
English
Publication Date
3-5-2024
Journal
Journal of the American Heart Association
DOI
10.1161/JAHA.123.032840
PMID
38420847
PMCID
PMC10944055
PubMedCentral® Posted Date
2-29-2024
PubMedCentral® Full Text Version
Post-print
Abstract
Background: Acute ischemic stroke is a major cause of mortality and disability worldwide, with approximately 7.4% to 7.7% recurrence within the first 3 months. This study aimed to identify potential biomarkers for predicting stroke recurrence.
Methods and results: We conducted a nested case-control study using a hospital-based cohort from the Third China National Stroke Registry selecting 214 age- and sex-matched patients with ischemic stroke with hypertension and no history of diabetes or heart disease. Using data-independent acquisition for discovery and multiple reaction monitoring for quantitative validation, we identified 26 differentially expressed proteins in large-artery atherosclerosis (Causative Classification of Ischemic Stroke [CCS]1), 16 in small-artery occlusion (CCS3), and 25 in undetermined causes (CCS5) among patients with recurrent stroke. In the CCS1 and CCS3 subgroups, differentially expressed proteins were associated with platelet aggregation, neuronal death/cerebroprotection, and immune response, whereas differentially expressed proteins in the CCS5 subgroup were linked to altered metabolic functions. Validated recurrence predictors included proteins associated with neutrophil activity and vascular inflammation (TAGLN2 [transgelin 2], ITGAM [integrin subunit α M]/TAGLN2 ratio, ITGAM/MYL9 [myosin light chain 9] ratio, TAGLN2/RSU1 [Ras suppressor protein 1] ratio) in the CCS3 subgroup and proteins associated with endothelial plasticity and blood-brain barrier integrity (ITGAM/MYL9 ratio and COL1A2 [collagen type I α 2 chain]/MYL9 ratio) in the CCS3 and CCS5 subgroups, respectively.
Conclusions: These findings provide a foundation for developing a blood-based biomarker panel, using causative classifications, which may be used in routine clinical practice to predict stroke recurrence.
Keywords
Humans, Brain Ischemia, Ischemic Stroke, Case-Control Studies, Stroke, Atherosclerosis, Biomarkers, Recurrence, Risk Factors, Transcription Factors, plasma, proteomics, stroke recurrence
Published Open-Access
yes
Recommended Citation
Zhang, Chengyi; Liu, Yang; Zhu, Huimin; et al., "Potential Protein Signatures for Recurrence Prediction of Ischemic Stroke" (2024). Faculty, Staff and Student Publications. 6202.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/6202
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