Expression of stromal-cell-derived factor-1 (SDF-1): a predictor of ischaemic stroke?

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Abstract

Background and purpose:

Platelet stromal-cell-derived factor-1 (SDF-1) plays a pivotal role in angiogenesis and the regeneration of ischaemic tissue through the regulation of haematopoietic progenitor cells and is upregulated at the sites of vascular injury and platelet activation. Thus, SDF-1 has recently been discussed as a predictor in ischaemic diseases such as acute myocardial infarction. However, no clinical data pertinent to the investigation of the platelet SDF-1 expression in patients with stroke are available.

Methods:

We consecutively evaluated 196 patients who were admitted to the stroke unit with symptoms suspected for stroke. Surface expression of the platelet activation markers (P-selectin and GPIb) and the expression of platelet-bound SDF-1 were determined by two-colour whole blood flow cytometry.

Results:

Patients with transient ischaemic attack (TIA) as well as with ischaemic stroke showed similar levels of SDF-1 expression on hospital admission compared with patients with non-ischaemic (NI) events and with 30 healthy controls (TIA (mean fluorescence intensity ± SD): 31.5 ± 18.2 vs. NI: 26.4 ± 15.7; P = 0.361; stroke: 28.7 ± 19.8 vs. NI; P = 0.943; control: 26.1 ± 11.3; P > 0.05 compared with all). Platelet SDF-1 expression showed a trend with the severity of stroke according to National Institute of Health Stroke Scale score (r = 0.125; P = 0.085), but significantly correlated with the peak levels of C-reactive protein (r = 0.218; P = 0.002) and with the levels of platelet activation (P-selectin: r = 0.389; P = 0.001). Multifactorial analysis of covariance revealed a significant influence on platelet SDF-1 expression by smoking (P = 0.019).

Conclusions:

Platelet SDF-1 surface expression did not show any significant difference in patients with TIA and ischaemic stroke compared with patients with NI events. Thus, single biomarker evaluation of platelet SDF-1 surface expression is not helpful to predict ischaemic stroke.

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