Spatial Analysis of Neural Cell Proteomic Profiles Following Ischemic Stroke in Mice Using High-Plex Digital Spatial Profiling.

Stroke is ranked as the fifth leading cause of death and the leading cause of adult disability in the USA. The progression of neuronal damage after stroke is recognized to be a complex integration of glia, neurons, and the surrounding extracellular matrix, therefore potential treatments must target the detrimental effects created by these interactions. In this study, we examined the spatial cellular and neuroinflammatory mechanisms occurring early after ischemic stroke utilizing Nanostring Digital Spatial Profiling (DSP) technology. Male C57bl/6 mice were subjected to photothrombotic middle cerebral artery occlusion (MCAO) and sacrificed at 3 days post-ischemia. Spatial distinction of the ipsilateral hemisphere was studied according to the regions of interest: the ischemic core, peri-infarct tissues, and peri-infarct normal tissue (PiNT) in comparison to the contralateral hemisphere. We demonstrated that the ipsilateral hemisphere initiates distinct spatial regulatory proteomic profiles with DSP technology that can be identified consistently with the immunohistochemical markers, FJB, GFAP, and Iba-1. The core border profile demonstrated an induction of neuronal death, apoptosis, autophagy, immunoreactivity, and early degenerative proteins. Most notably, the core border resulted in a decrease of the neuronal proteins Map2 and NeuN; an increase in the autophagy proteins BAG3 and CTSD; an increase in the microglial and peripheral immune invasion proteins Iba1, CD45, CD11b, and CD39; and an increase in the neurodegenerative proteins BACE1, APP, amyloid ß 1-42, ApoE, and hyperphosphorylated tau protein S-199. The peri-infarct region demonstrated increased astrocytic, immunoreactivity, apoptotic, and neurodegenerative proteomic profiles, with an increase in BAG3, GFAP, and hyperphosphorylated tau protein S-199. The PiNT region displayed minimal changes compared to the contralateral cortex with only an increase in GFAP. In this study, we showed that mechanisms known to be associated with stroke, such as apoptosis and inflammation, occur in distinct spatial domains of the injured brain following ischemia. We also demonstrated the dysregulation of specific autophagic pathways that may lead to neurodegeneration in peri-infarct brain tissues. Taken together, these data suggest that identifying post-ischemic mechanisms occurring in a spatiotemporal manner may lead to more precise targets for successful therapeutic interventions to treat stroke.

Identification of novel blood biomarker panels to detect ischemic stroke in patients and their responsiveness to therapeutic intervention.

The use of blood biomarkers for stroke has been long considered an excellent method to determine the occurrence, timing, subtype, and severity of stroke. In this study, venous blood was obtained from ischemic stroke patients after stroke onset and compared with age and sex-matched controls. We used a multiplex panel of 37 inflammatory molecules, analyzed using Luminex MagPix technology, to identify the changes in plasma proteins after ischemic stroke. We identified eight key molecules that were altered within the blood of stroke patients as compared to controls. Plasma levels of interleukin 6 signal transducer (sIL-6Rß/gp130), matrix metalloproteinase-2 (MMP-2), osteopontin, sTNF-R1 and sTNF-R2 were significantly higher in stroke patients compared to controls. Interferon-ß, interleukin-28, and thymic stromal lymphopoietin (TSLP) were decreased in plasma from stroke patients. No other immunological markers were significantly different between patient groups. When stroke patients were treated with tissue plasminogen activator (t-PA), plasma levels of interferon-α2 significantly increased while interleukin-2 and pentraxin-3 decreased. The discriminatory power of the molecules was evaluated by receiver operating characteristic (ROC) analysis. According to ROC analysis, the best markers for distinguishing stroke occurrence were MMP-2 (AUC = 0.76, sensitivity 62.5%, specificity 88.5%), sTNF-R2 (AUC = 0.75, sensitivity 83.3%, specificity 65.3%) and TSLP (AUC = 0.81, sensitivity 66.7%, specificity 96.2%). Multivariate logistic regression, used to evaluate the combination of proteins, identified a biomarker panel with high specificity and sensitivity (AUC = 0.96, sensitivity 87.5%, specificity 96.2%). These results indicate a novel set of blood biomarkers that could be used in a panel to identify stroke patients and their responsiveness to therapeutic intervention.