Role of beta-defensin 2 and interleukin-4 receptor as stroke outcome biomarkers.

Acute ischemic stroke is a complex disease with huge interindividual evolution variability that makes challenging the prediction of an adverse outcome. Our aim was to study the association of bloodstream signatures to early neurological outcome after stroke, by combining a subpooling of samples strategy with protein array discovery approach. Plasma samples from 36 acute stroke patients (< 4.5 h from onset) were equally pooled within outcome groups: worsening, stability, and improvement (n = 3 pools of four patients each, for each outcome group). These nine pools were screened using a 177 antibodies library, and 35 proteins were found altered regarding outcome classification (p < 0.1). Processes of inflammation, immune response, coagulation, and apoptosis were regulated by these proteins. Ten representative candidates, mainly cytokines and chemokines, were assayed for replication in individual baseline plasma samples from 80 new stroke patients: β-defensin2, MIP-3b, plasminogen activator inhibitor 1 active, β-cell-attracting chemokine 1, Exodus-2, interleukin-4 receptor (IL-4R), IL-12p40, leukemia inhibitor factor, MIP-1b, and tumor necrosis factor-related weak inducer of apoptosis. Multivariate logistic regression analysis showed β-defensin 2 (ORadj 4.87 [1.13-20.91] p = 0.033) and IL-4R (ORadj 3.52 [1.03-12.08] p = 0.045) as independent predictors of worsening at 24 h after adjustment by clinical variables. Both biomarkers improve the prediction by 19% as compared to clinical information, suggesting a potential role for risk stratification in acute thrombolyzed stroke patients. Early neurological deterioration after stroke is not easily predictable. The use of blood biomarkers might help in decision-making processes regarding this complication. By combining a sub-pooling of samples strategy with protein array discovery approach, we have found two new biomarkers: beta-defensin-2 and interleukin-4 receptor. Both biomarkers improve the prediction of poor-outcome over clinical variables in the acute phase of stroke.

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