Objective:To examine the relationship between neonatal inflammatory cytokines and perinatal stroke, using a systems biology approach analyzing serum and bloodspot cytokines from 47 patients.Methods:This was a population-based, controlled cohort study with prospective and retrospective case ascertainment. Participants were recruited through the Alberta Perinatal Stroke Project (APSP). Stroke was classified as neonatal arterial ischemic stroke (NAIS), arterial presumed perinatal ischemic stroke (APPIS), or periventricular infarction (PVI). Biosamples were stored bloodspots (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. Fisher’s linear discriminant analysis was used to create projection models to determine discriminatory boundaries between stroke types and controls.Results:A total of 197 participants were analyzed (27 NAIS, 8 APPIS, 12 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 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.Interpretation: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.Classification of Evidence: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.

The understanding of molecular biology in neurocritical care (NCC) is expanding rapidly and recognizing the important contribution of neuroinflammation, specifically changes in immunometabolism, towards pathological disease processes encountered across all illnesses in the NCC. Additionally, the importance of individualized inflammatory responses has been emphasized, acknowledging that not all individuals have the same mechanisms contributing towards their presentation. By understanding cellular processes that drive disease, we can make better personalized therapy decisions to improve patient outcomes. While the understanding of these cellular processes is evolving, the ability to measure such cellular responses at bedside to make acute care decisions is lacking. In this overview, we review cellular mechanisms involved in pathological neuroinflammation with a focus on immunometabolic dysfunction and review non-invasive bedside tools that have the potential to measure indirect and direct markers of shifts in cellular metabolism related to neuroinflammation. These tools include near-infrared spectroscopy, transcranial doppler, elastography, electroencephalography, magnetic resonance imaging and spectroscopy, and cytokine analysis. Additionally, we review the importance of genetic testing in providing information about unique metabolic profiles to guide individualized interpretation of bedside data. Together in tandem, these modalities have the potential to provide real time information and guide more informed treatment decisions.