Investigating the Role of Brain Natriuretic Peptide (BNP) and N-Terminal-proBNP in Thrombosis and Acute Ischemic Stroke Etiology

The need for biomarkers for acute ischemic stroke (AIS) to understand the mechanisms implicated in pathological clot formation is critical. The levels of the brain natriuretic peptides known as brain natriuretic peptide (BNP) and NT-proBNP have been shown to be increased in patients suffering from heart failure and other heart conditions. We measured their expression in AIS clots of cardioembolic (CE) and large artery atherosclerosis (LAA) etiology, evaluating their location inside the clots, aiming to uncover their possible role in thrombosis. We analyzed 80 thrombi from 80 AIS patients in the RESTORE registry of AIS clots, 40 of which were of CE and 40 of LAA etiology. The localization of BNP and NT-BNP, quantified using immunohistochemistry and immunofluorescence, in AIS-associated white blood cell subtypes was also investigated. We found a statistically significant positive correlation between BNP and NT-proBNP expression levels (Spearman's rho = 0.668 p < 0.0001 *). We did not observe any statistically significant difference between LAA and CE clots in BNP expression (0.66 [0.13-3.54]% vs. 0.53 [0.14-3.07]%, p = 0.923) or in NT-proBNP expression (0.29 [0.11-0.58]% vs. 0.18 [0.05-0.51]%, p = 0.119), although there was a trend of higher NT-proBNP expression in the LAA clots. It was noticeable that BNP was distributed throughout the thrombus and especially within platelet-rich regions. However, NT-proBNP colocalized with neutrophils, macrophages, and T-lymphocytes, suggesting its association with the thrombo-inflammatory process.

S100b in acute ischemic stroke clots is a biomarker for post-thrombectomy intracranial hemorrhages

Background and purpose

Post-thrombectomy intracranial hemorrhages (PTIH) are dangerous complications of acute ischemic stroke (AIS) following mechanical thrombectomy. We aimed to investigate if S100b levels in AIS clots removed by mechanical thrombectomy correlated to increased risk of PTIH.

Methods

We analyzed 122 thrombi from 80 AIS patients in the RESTORE Registry of AIS clots, selecting an equal number of patients having been pre-treated or not with rtPA (40 each group). Within each subgroup, 20 patients had developed PTIH and 20 patients showed no signs of hemorrhage. Gross photos of each clot were taken and extracted clot area (ECA) was measured using ImageJ. Immunohistochemistry for S100b was performed and Orbit Image Analysis was used for quantification. Immunofluorescence was performed to investigate co-localization between S100b and T-lymphocytes, neutrophils and macrophages. Chi-square or Kruskal-Wallis test were used for statistical analysis.

Results

PTIH was associated with higher S100b levels in clots (0.33 [0.08-0.85] vs. 0.07 [0.02-0.27] mm², H1 = 6.021, P = 0.014^*), but S100b levels were not significantly affected by acute thrombolytic treatment (P = 0.386). PTIH was also associated with patients having higher NIHSS at admission (20.0 [17.0-23.0] vs. 14.0 [10.5-19.0], H1 = 8.006, P = 0.005) and higher number of passes during thrombectomy (2 [1-4] vs. 1 [1-2.5], H1 = 5.995, P = 0.014^*). S100b co-localized with neutrophils, macrophages and with T-lymphocytes in the clots.

Conclusions

Higher S100b expression in AIS clots, higher NIHSS at admission and higher number of passes during thrombectomy are all associated with PTIH. Further investigation of S100b expression in AIS clots by neutrophils, macrophages and T-lymphocytes could provide insight into the role of S100b in thromboinflammation.

Potential Biomarkers of Acute Ischemic Stroke Etiology Revealed by Mass Spectrometry-Based Proteomic Characterization of Formalin-Fixed Paraffin-Embedded Blood Clots

Background and Aims

Besides the crucial role in the treatment of acute ischemic stroke (AIS), mechanical thrombectomy represents a unique opportunity for researchers to study the retrieved clots, with the possibility of unveiling biological patterns linked to stroke pathophysiology and etiology. We aimed to develop a shotgun proteomic approach to study and compare the proteome of formalin-fixed paraffin-embedded (FFPE) cardioembolic and large artery atherosclerotic (LAA) clots.

Methods

We used 16 cardioembolic and 15 LAA FFPE thrombi from 31 AIS patients. The thrombus proteome was analyzed by label-free quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS). MaxQuant v1.5.2.8 and Perseus v.1.6.15.0 were used for bioinformatics analysis. Protein classes were identified using the PANTHER database and the STRING database was used to predict protein interactions.

Results

We identified 1,581 protein groups as part of the AIS thrombus proteome. Fourteen significantly differentially abundant proteins across the two etiologies were identified. Four proteins involved in the ubiquitin-proteasome pathway, blood coagulation or plasminogen activating cascade were identified as significantly abundant in LAA clots. Ten proteins involved in the ubiquitin proteasome-pathway, cytoskeletal remodeling of platelets, platelet adhesion or blood coagulation were identified as significantly abundant in cardioembolic clots.

Conclusion

Our results outlined a set of 14 proteins for a proof-of-principle characterization of cardioembolic and LAA FFPE clots, advancing the proteome profile of AIS human thrombi and understanding the pathophysiology of ischemic stroke.

Proteomic Characterization of the Dynamics of Ischemic Stroke in Mice

Novel therapies and biomarkers are needed for the treatment of acute ischemic stroke (AIS). This study aimed to provide comprehensive insights into the dynamic proteome changes and underlying molecular mechanisms post-ischemic stroke. TMT-coupled proteomic analysis was conducted on mouse brain cortex tissue from five time points up to 4 weeks poststroke in the distal hypoxic-middle cerebral artery occlusion (DH-MCAO) model. We found that nearly half of the detected proteome was altered following stroke, but only ∼8.6% of the changes were at relatively large scales. Clustering on the changed proteome defined four distinct expression patterns characterized by temporal and quantitative changes in innate and adaptive immune response pathways and cytoskeletal and neuronal remodeling. Further analysis on a subset of 309 “top hits”, which temporally responded to stroke with relatively large and sustained changes, revealed that they were mostly secreted proteins, highly correlated to different cortical cytokines, and thereby potential pharmacodynamic biomarker candidates for inflammation-targeting therapies. Closer examination of the top enriched neurophysiologic pathways identified 57 proteins potentially associated with poststroke recovery. Altogether, our study generated a rich dataset with candidate proteins worthy of further validation as biomarkers and/or therapeutic targets for stroke. The proteomics data are available in the PRIDE Archive with identifier PXD025077.

[The possibility of using neuron-specific enolase as a biomarker in the acute period of stroke]

The article presents a review of the literature on neuron-specific enolase (NSE) as a biomarker of stroke. It is shown that NSE does not allow differentiation of the ischemic and hemorrhagic process in stroke, but is suitable for determining the extent of brain tissue destruction both in the first hours of stroke and in the dynamics. The HSE analysis can be useful for monitoring the course of the disease, control of the dynamics of the pathological process, including when the size of the lesion increases, for evaluating the effectiveness of therapy and as a prognostic biomarker.

Validation of a proteomic biomarker panel to diagnose minor-stroke and transient ischaemic attack: phase 2 of SpecTRA, a large scale translational study

OBJECTIVE

To validate our previously developed 16 plasma-protein biomarker panel to differentiate between transient ischaemic attack (TIA) and non-cerebrovascular emergency department (ED) patients.

METHOD

Two consecutive cohorts of ED patients prospectively enrolled at two urban medical centers into the second phase of SpecTRA study (training, cohort 2A, n = 575; test, cohort 2B, n = 528). Plasma samples were analyzed using liquid chromatography/multiple reaction monitoring-mass spectrometry. Logistic regression models which fit cohort 2A were validated on cohort 2B.

RESULTS

Three of the panel proteins failed quality control and were removed from the panel. During validation, panel models did not outperform a simple motor/speech (M/S) deficit variable. Post-hoc analyses suggested the measured behaviour of L-selectin and coagulation factor V contributed to poor model performance. Removal of these proteins increased the external performance of a model containing the panel and the M/S variable.

CONCLUSIONS

Univariate analyses suggest insulin-like growth factor-binding protein 3 and serum paraoxonase/lactonase 3 are reliable and reproducible biomarkers for TIA status. Logistic regression models indicated L-selectin, apolipoprotein B-100, coagulation factor IX, and thrombospondin-1 to be significant multivariate predictors of TIA. We discuss multivariate feature subset analyses as an exploratory technique to better understand a panel's full predictive potential.

Verification of a proteomic biomarker panel to diagnose minor stroke and transient ischaemic attack: phase 1 of SpecTRA, a large scale translational study

OBJECTIVE

To derive a plasma biomarker protein panel from a list of 141 candidate proteins which can differentiate transient ischaemic attack (TIA)/minor stroke from non-cerebrovascular (mimic) conditions in emergency department (ED) settings.

DESIGN

Prospective clinical study (#NCT03050099) with up to three timed blood draws no more than 36 h following symptom onset. Plasma samples analysed by multiple reaction monitoring-mass spectrometry (MRM-MS).

PARTICIPANTS

Totally 545 participants suspected of TIA enrolled in the EDs of two urban medical centres.

OUTCOMES

90-day, neurologist-adjudicated diagnosis of TIA informed by clinical and radiological investigations.

RESULTS

The final protein panel consists of 16 proteins whose patterns show differential abundance between TIA and mimic patients. Nine of the proteins were significant univariate predictors of TIA [odds ratio (95% confidence interval)]: L-selectin [0.726 (0.596-0.883)]; Insulin-like growth factor-binding protein 3 [0.727 (0.594-0.889)]; Coagulation factor X [0.740 (0.603-0.908)]; Serum paraoxonase/lactonase 3 [0.763 (0.630-0.924)]; Thrombospondin-1 [1.313 (1.081-1.595)]; Hyaluronan-binding protein 2 [0.776 (0.637-0.945)]; Heparin cofactor 2 [0.775 (0.634-0.947)]; Apolipoprotein B-100 [1.249 (1.037-1.503)]; and von Willebrand factor [1.256 (1.034-1.527)]. The scientific plausibility of the panel proteins is discussed.

CONCLUSIONS

Our panel has the potential to assist ED physicians in distinguishing TIA from mimic patients.

Improvement in stroke risk prediction: role of C-reactive protein and lipoprotein-associated phospholipase A2 in the women's health initiative

BACKGROUND

Classification of risk of ischemic stroke is important for medical care and public health reasons. Whether addition of biomarkers adds to predictive power of the Framingham Stroke Risk or other traditional risk factors has not been studied in older women.

METHODS

The Hormones and Biomarkers Predicting Stroke Study is a case-control study of blood biomarkers assayed in 972 ischemic stroke cases and 972 controls, nested in the Women's Health Initiative Observational Study of 93, 676 postmenopausal women followed for an average of eight-years. We evaluated additive predictive value of two commercially available biomarkers: C-reactive protein and lipoprotein-associated phospholipase A2 to determine if they added to risk prediction by the Framingham Stroke Risk Score or by traditional risk factors, which included lipids and other variables not included in the Framingham Stroke Risk Score. As measures of additive predictive value, we used the C-statistic, net reclassification improvement, category-less net reclassification improvement, and integrated discrimination improvement index.

RESULTS

Addition of C-reactive protein to Framingham risk models or additional traditional risk factors overall modestly improved prediction of ischemic stroke and resulted in overall net reclassification improvement of 6·3%, (case net reclassification improvement=3·9%, control net reclassification improvement=2·4%). In particular, high-sensitivity C-reactive protein was useful in prediction of cardioembolic strokes (net reclassification improvement=12·0%; 95% confidence interval 4·3-19·6%) and in strokes occurring in less than three-years (net reclassification improvement=7·9%, 95% confidence interval 0·8-14·9%). Lipoprotein-associated phospholipase A2 was useful in risk prediction of large artery strokes (net reclassification improvement=19·8%, 95% confidence interval 7·4-32·1%) and in early strokes (net reclassification improvement=5·8%, 95% confidence interval 0·4-11·2%).

CONCLUSIONS

C-reactive protein and lipoprotein-associated phospholipase A2 can improve prediction of certain subtypes of ischemic stroke in older women, over the Framingham stroke risk model and traditional risk factors, and may help to guide surveillance and treatment of women at risk.