Association of neonatal inflammatory markers and perinatal stroke subtypes.

Abstract

To examine the relationship between neonatal inflammatory cytokines and perinatal stroke using a systems biology approach analyzing serum and blood-spot cytokines from 47 patients. This was a population-based, controlled cohort study with prospective and retrospective case ascertainment. Participants were recruited through the Alberta Perinatal Stroke Project. Stroke was classified as neonatal arterial ischemic stroke (NAIS), arterial presumed perinatal ischemic stroke (APPIS), or periventricular venous infarction (PVI). Biosamples were stored blood spots (retrospective) and acute serum (prospective). Controls had comparable gestational and maternal ages. Sixty-five cytokines were measured (Luminex). Hierarchical clustering analysis was performed to create heat maps. The Fisher linear discriminant analysis was used to create projection models to determine discriminatory boundaries between stroke types and controls. A total of 197 participants were analyzed (27 with NAIS, 8 with APPIS, 12 with PVI, 150 controls). Cytokines were quantifiable with quality control measures satisfied (standards testing, decay analysis). Linear discriminant analysis had high accuracy in using cytokine profiles to separate groups. Profiles in participants with PVI and controls were similar. NAIS separation was accurate (sensitivity 77%, specificity 97%). APPIS mapping was also distinguishable from NAIS (sensitivity 86%, specificity 99%). Classification tree analysis generated similar diagnostic accuracy. Unique inflammatory biomarker signatures are associated with specific perinatal stroke diseases. Findings support an acquired pathophysiology and suggest the possibility that at-risk pregnancies might be identified to develop prevention strategies. This study provides Class III evidence that differences in acute neonatal serum cytokine profiles can discriminate between patients with specific perinatal stroke diseases and controls.