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

How Clot Composition Influences Fibrinolysis in the Acute Phase of Stroke: A Proteomic Study of Cerebral Thrombi

BACKGROUND

The dramatic clinical improvement offered by mechanical thrombectomy raised questions about the relevance of prior intravenous thrombolysis in large-vessel occlusion strokes. Hence, studying intravenous thrombolysis susceptibility and its dependence on thrombus composition is crucial. We used an observational proteomic study of whole thrombi retrieved by mechanical thrombectomy to identify factors associated with fibrin content and fibrinolytic activity (FA).

METHODS

In 104 stroke patients, the thrombi proteome was established by mass spectrometry coupled to liquid chromatography. FA was estimated in clots both outside (FAout) by measuring D-dimer levels at the blood-thrombus interface and inside (FAin) by evaluating the ratio of fibrinogen α to its plasmin-cleaved forms using proteomics coupled with protein electrophoresis. The factors associated with fibrin content, FAin, and FAout were determined by intravenous thrombolysis-adjusted linear regression.

RESULTS

FAout (P<0.0001) and FAin (P=0.0147) were driven by recombinant tissue-type plasminogen activator (r-tPA) administration (47/104) and thrombus composition. Indeed, FAout was greater with fibrin-rich than erythrocyte-rich thrombi, presumably because of more (r)tPA substrates. Thus, FAout was increased with cardioembolic thrombi (72/104), which are rich in fibrin (P=0.0300). Opposite results were found inside the thrombus, suggesting that (r)tPA penetrability was hampered by the density of the fibrinous cap. Moreover, blood cells had a strong impact on thrombus structure and susceptibility to (r)tPA. Indeed, fibrin content was negatively associated with erythrocyte-specific proteins in the thrombus, admission hematocrit (P=0.0139), and hemoglobin level (P=0.0080), which underlines the key role of erythrocytes in thrombus composition. Also, an increased number of neutrophils impaired FAout (P=0.0225), which suggests that their aggregation around the thrombus prevented the (r)tPA attack. Only FAout was significantly associated with reduced thrombus weight (P=0.0310), increased recanalization rate (P=0.0150), good clinical outcome (P=0.0480), and reduced mortality (P=0.0080).

CONCLUSIONS

Proteomics can offer new insights into the close relationship between thrombus composition and susceptibility to fibrinolysis, paving the way for new adjuvant therapies.

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.

Proteomic advance of ischemic stroke: preclinical, clinical, and intervention

Ischemic stroke (IS) is the most common type of stroke and is characterized by high rates of mortality and long-term injury. The prediction and early diagnosis of IS are therefore crucial for optimal clinical intervention. Proteomics has provided important techniques for exploring protein markers associated with IS, but there has been no systematic evaluation and review of research that has used these techniques. Here, we review the differential proteins that have been found in cell- and animal- based studies and clinical trials of IS in the past 10 years; determine the key pathological proteins that have been identified in clinical trials; summarize the target proteins affected by interventions aimed at treating IS, with a focus on traditional Chinese medicine treatments. Overall, we clarify findings and problems that have been identified in recent proteomics research on IS and provide suggestions for improvements in this area. We also suggest areas that could be explored for determining the pathogenesis and developing interventions for IS.

CT hyperdense cerebral artery sign reflects distinct proteomic composition in acute ischemic stroke thrombus

BACKGROUND

Hyperdense cerebral artery sign (HCAS) is an imaging biomarker in acute ischemic stroke (AIS) that has been shown to be associated with various clinical outcomes and stroke etiology. While prior studies have correlated HCAS with histopathological composition of cerebral thrombus, it is unknown whether and to what extent HCAS is also associated with distinct clot protein composition.

METHODS

Thromboembolic material from 24 patients with AIS were retrieved via mechanical thrombectomy and evaluated with mass spectrometry in order to characterize their proteomic composition. Presence (+) or absence (-) of HCAS on preintervention non-contrast head CT was then determined and correlated with thrombus protein signature with abundance of individual proteins calculated as a function HCAS status.

RESULTS

24 clots with 1797 distinct proteins in total were identified. 14 patients were HCAS(+) and 10 were HCAS(-). HCAS(+) were most significantly differentially abundant in actin cytoskeletal protein (P=0.002, Z=2.82), bleomycin hydrolase (P=0.007, Z=2.44), arachidonate 12-lipoxygenase (P=0.004, Z=2.60), and lysophospholipase D (P=0.007, Z=2.44), among other proteins; HCAS(-) clots were differentially enriched in soluble N-ethylmaleimide-sensitive factor (NSF) attachment protein (P=0.0009, Z=3.11), tyrosine-protein kinase Fyn (P=0.002, Z=2.84), and several complement proteins (P<0.05, Z>1.71 for all), among numerous other proteins. Additionally, HCAS(-) thrombi were enriched in biological processes involved with plasma lipoprotein and protein-lipid remodeling/assembling, and lipoprotein metabolic processes (P<0.001), as well as cellular components including mitochondria (P<0.001).

CONCLUSIONS

HCAS is reflective of distinct proteomic composition in AIS thrombus. These findings suggest that imaging can be used to identify mechanisms of clot formation or maintenance at the protein level, and might inform future research on thrombus biology and imaging characterization.

Mollet I, Mendonça M, Salavisa M, Meira B, Fernandes M, Serrazina F, Cabral G, Ventura R, Sobral‐Pinho A, Beck HC, Vieira HLA, Viana‐Baptista M, Matthiesen R. Proteomics to Identify New Blood Biomarkers for Diagnosing Patients With Acute Stroke

Background Blood biomarkers are a potential tool for early stroke diagnosis. We aimed to perform a pilot and exploratory study on untargeted blood biomarkers in patients with suspected stroke by using mass spectrometry analysis. Methods and Results This was a prospective observational study of consecutive patients with suspected stroke admitted within 6 hours of last being seen well. Blood samples were collected at admission. Patients were divided into 3 groups: ischemic stroke (IS), intracerebral hemorrhage (ICH), and stroke mimics. Quantitative analysis from mass spectrometry data was performed using a supervised approach. Biomarker-based prediction models were developed to differentiate IS from ICH and ICH+stroke mimics. Models were built aiming to minimize misidentification of patients with ICH as having IS. We included 90 patients, one-third within each subgroup. The median age was 71 years (interquartile range, 57-81 years), and 49 participants (54.4%) were women. In quantitative analysis, C3 (complement component 3), ICAM-2 (intercellular adhesion molecule 2), PLGLA (plasminogen like A), STXBP5 (syntaxin-binding protein 5), and IGHV3-64 (immunoglobulin heavy variable 3-64) were the 5 most significantly dysregulated proteins for both comparisons. Biomarker-based models showed 88% sensitivity and 89% negative predictive value for differentiating IS from ICH, and 75% sensitivity and 95% negative predictive value for differentiating IS from ICH+stroke mimics. ICAM-2, STXBP5, PLGLA, C3, and IGHV3-64 displayed the highest importance score in our models, being the most informative for identifying patients with stroke. Conclusions In this proof-of-concept and exploratory study, our biomarker-based prediction models, including ICAM-2, STXBP5, PLGLA, C3, and IGHV3-64, showed 75% to 88% sensitivity for identifying patients with IS, while aiming to minimize misclassification of ICH. Although our methodology provided an internal validation, these results still need validation in other cohorts and with different measurement techniques.

The thrombus proteome in stroke reveals a key role of the innate immune system and new insights associated with its etiology, severity, and prognosis

BACKGROUND

Nowadays little is known about the molecular profile of the occluding thrombus of patients with ischemic stroke.

OBJECTIVES

To analyze the proteomic profile of thrombi in patients who experienced an ischemic stroke in order to gain insights into disease pathogenesis.

METHODS

Thrombi from an exploratory cohort of patients who experienced a stroke were obtained by thrombectomy and analyzed by sequential window acquisition of all theoretical spectra-mass spectrometry. Unsupervised k-means clustering analysis was performed to stratify patients who experienced a stroke. The proteomic profile was associated with both the neurological function (National Institute of Health Stroke Scale [NIHSS]) and the cerebral involvement (Alberta Stroke Program Early CT Score [ASPECTS]) prior to thrombectomy and the clinical status of patients at 3 months using the modified Rankin Scale. In an independent cohort of 210 patients who experienced a stroke, the potential role of neutrophils in stroke severity was interrogated.

RESULTS

Proteomic analysis identified 580 proteins in thrombi, which were stratified into 4 groups: hemostasis, proteasome and neurological diseases, structural proteins, and innate immune system and neutrophils. The thrombus proteome identified 3 clusters of patients with distinctive severity, prognosis, and etiology of the stroke. A protein signature clearly distinguished atherothrombotic and cardioembolic strokes. Several proteins were significantly correlated with the severity of the stroke (NIHSS and ASPECTS). Functional proteomic analysis highlighted the prominent role of neutrophils in stroke severity. This was in line with the association of neutrophil activation markers and count with NIHSS, ASPECTS, and the modified Rankin Scale score 90 days after the event.

CONCLUSION

The use of sequential window acquisition of all theoretical spectra-mass spectrometry in thrombi from patients who experienced an ischemic stroke has provided new insights into pathways and players involved in its etiology, severity, and prognosis. The prominent role of the innate immune system identified might pave the way for the development of new biomarkers and therapeutic approaches in this disease.

Gene expression profiles of ischemic stroke clots retrieved by mechanical thrombectomy are associated with disease etiology

BACKGROUND

Determining stroke etiology is crucial for secondary prevention, but intensive workups fail to classify ~30% of strokes that are cryptogenic.

OBJECTIVE

To examine the hypothesis that the transcriptomic profiles of clots retrieved during mechanical thrombectomy are unique to strokes of different subtypes.

METHODS

We isolated RNA from the clots of 73 patients undergoing mechanical thrombectomy. Samples of sufficient quality were subjected to 100-cycle, paired-end RNAseq, and transcriptomes with less than 10 million unique reads were excluded from analysis. Significant differentially expressed genes (DEGs) between subtypes (defined by the Trial of Org 10 172 in Acute Stroke Treatment) were identified by expression analysis in edgeR. Gene ontology enrichment analysis was used to study the biologic differences between stroke etiologies.

RESULTS

In all, 38 clot transcriptomes were analyzed; 6 from large artery atherosclerosis (LAA), 21 from cardioembolism (CE), 5 from strokes of other determined origin, and 6 from cryptogenic strokes. Among all comparisons, there were 816 unique DEGs, 174 of which were shared by at least two comparisons, and 20 of which were shared by all three. Gene ontology analysis showed that CE clots reflected high levels of inflammation, LAA clots had greater oxidoreduction and T-cell processes, and clots of other determined origin were enriched for aberrant platelet and hemoglobin-related processes. Principal component analysis indicated separation between these subtypes and showed cryptogenic samples clustered among several different groups.

CONCLUSIONS

Expression profiles of stroke clots were identified between stroke etiologies and reflected different biologic responses. Cryptogenic thrombi may be related to multiple etiologies.

Thrombus composition and thrombolysis resistance in stroke

A State of the Art lecture titled "Thrombus Composition and Thrombolysis Resistance in Stroke" was presented at the ISTH Congress in 2022. Intravenous thrombolysis (IVT) remains the only pharmacologic option to re-establish cerebral perfusion at the acute phase of ischemic stroke. IVT is based on the administration of recombinant tissue plasminogen activator with the objective of dissolving fibrin, the major fibrillar protein component of thrombi. Almost 30 years on from its introduction, although the clinical benefits of IVT have been clearly demonstrated, IVT still suffers from a relatively low efficacy, with a rate of successful early recanalization below 50% overall. Analyses of thrombectomy-recovered acute ischemic stroke (AIS) thrombi have shown that apart from occlusion site, thrombus length, and collateral status, AIS thrombus structure and composition are also important modulators of IVT efficacy. In this article, after a brief presentation of IVT principle and current knowledge on IVT resistance, we review recent findings on how compaction and structural alterations of fibrin together with nonfibrin thrombus components such as neutrophil extracellular traps and von Willebrand factor interfere with IVT in AIS. We further discuss how these new insights could soon result in the development of original adjuvant therapies for improved IVT in AIS. Finally, we summarize relevant new data presented during the 2022 ISTH Congress.

Advancing Stroke Research on Cerebral Thrombi with Omic Technologies

Cerebrovascular diseases represent a leading cause of disability, morbidity, and death worldwide. In the last decade, the advances in endovascular procedures have not only improved acute ischemic stroke care but also conceded a thorough analysis of patients' thrombi. Although early anatomopathological and immunohistochemical analyses have provided valuable insights into thrombus composition and its correlation with radiological features, response to reperfusion therapies, and stroke etiology, these results have been inconclusive so far. Recent studies applied single- or multi-omic approaches-such as proteomics, metabolomics, transcriptomics, or a combination of these-to investigate clot composition and stroke mechanisms, showing high predictive power. Particularly, one pilot studies showed that combined deep phenotyping of stroke thrombi may be superior to classic clinical predictors in defining stroke mechanisms. Small sample sizes, varying methodologies, and lack of adjustments for potential confounders still represent roadblocks to generalizing these findings. However, these techniques hold the potential to better investigate stroke-related thrombogenesis and select secondary prevention strategies, and to prompt the discovery of novel biomarkers and therapeutic targets. In this review, we summarize the most recent findings, overview current strengths and limitations, and present future perspectives in the field.

Thrombosis origin identification of cardioembolism and large artery atherosclerosis by distinct metabolites

BACKGROUND

The diagnosis of cerebral thrombosis origin is challenging and remains unclear. This study aims to identify thrombosis due to cardioembolism (CE) and large artery atherosclerosis (LAA) from a new perspective of distinct metabolites.

METHODS

Distinct metabolites between 26 CE and 22 LAA origin thrombi, which were extracted after successful mechanical thrombectomy in patients with acute ischemic stroke in the anterior circulation, were analyzed with a ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) system. Enriched metabolic pathways related to the metabolites were identified. Least absolute shrinkage selection operator regression analyses and a filtering method were used to select potential predictors. Furthermore, four machine learning classifiers, including decision tree, logistic regression, random forest (RF), and k means unsupervised classification model, were used to evaluate the predictive ability of the selected metabolites.

RESULTS

UPLC-QTOF-MS analysis revealed that levels of 88 and 55 metabolites were elevated in LAA and CE thrombi, respectively. Kyoto Encyclopedia of Genes and Genomes analysis revealed a significant difference between the pathways enriched in the two types of thrombi. Six metabolites (diglyceride (DG, 18:3/24:0), DG (22:0/24:0), phytosphingosine, galabiosylceramide (18:1/24:1), triglyceride (15:0/16:1/o-18:0), and glucosylceramide (18:1/24:0)) were finally selected to build a predictive model. The predictive RF model was confirmed to be the best, with a satisfactory stability and prediction capacity (area under the curve=0.889).

CONCLUSIONS

Six metabolites as potential predictors for distinguishing between cerebral thrombi of CE and LAA origin were identified. The results are useful for understanding the pathogenesis and for secondary stroke prevention.