Intracranial VCAM1 at time of mechanical thrombectomy predicts ischemic stroke severity

Emergent large vessel occlusion (ELVO) strokes are devastating ischemic vascular events for which novel treatment options are needed. Using vascular cell adhesion molecule 1 (VCAM1) as a prototype, the objective of this study was to identify proteomic biomarkers and network signaling functions that are potential therapeutic targets for adjuvant treatment for mechanical thrombectomy.

The blood and clot thrombectomy and collaboration (BACTRAC) study is a continually enrolling tissue bank and registry from stroke patients undergoing mechanical thrombectomy. Plasma proteins from intracranial (distal to clot) and systemic arterial blood (carotid) were analyzed by Olink Proteomics for N=42 subjects. Statistical analysis of plasma proteomics used independent sample t tests, correlations, linear regression, and robust regression models to determine network signaling and predictors of clinical outcomes. Data and network analyses were performed using IBM SPSS Statistics, SAS v 9.4, and STRING V11.

Increased systemic (p<0.001) and intracranial (p=0.013) levels of VCAM1 were associated with the presence of hypertension. Intracranial VCAM1 was positively correlated to both infarct volume (p=0.032; r=0.34) and edema volume (p=0.026; r=0.35). The %∆ in NIHSS from admittance to discharge was found to be significantly correlated to both systemic (p=0.013; r = -0.409) and intracranial (p=0.011; r = -0.421) VCAM1 levels indicating elevated levels of systemic and intracranial VCAM1 are associated with reduced improvement of stroke severity based on NIHSS from admittance to discharge. STRING-generated analyses identified biologic functional descriptions as well as function-associated proteins from the predictive models of infarct and edema volume.

The current study provides novel data on systemic and intracranial VCAM1 in relation to stroke comorbidities, stroke severity, functional outcomes, and the role VCAM1 plays in complex protein-protein signaling pathways. These data will allow future studies to develop predictive biomarkers and proteomic targets for drug development to improve our ability to treat a devastating pathology.