Stroke Biomarkers Research Articles

Abstract TMP9: Flair Vascular Hyperintensities as Imaging Biomarker in Pediatric Arterial Ischemic Stroke

Background: FLAIR vascular hyperintensities (FVH) are high signal intensities on MRI resulting from sluggish flow through collateral vessels in patients with acute arterial ischemic stroke (AIS). Data from adults suggest they may be a marker of penumbra. In this first investigation of FVH in children, I measured the prevalence and identified risk factors for FVH in pediatric patients with AIS. Methods: Retrospective review of patients prospectively enrolled in the CHOP Stroke Registry from 2006-2022. Patients with AIS age 29 days to 18 years with MRI within 72 hours of last known well were included. Children with pre-existing strokes, vasculopathy, prior brain surgery, radiation, or vascular compression from intracranial mass were excluded. MRIs were assessed by a blinded reviewer and adjudicated by a neuroradiologist for presence of LVO, FVH score, modASPECTS score, and AIS lesion volume. Clinical data were abstracted from chart review. Independent sample t-test compared FVH score and LVO presence. Pearson's correlation assessed the relationship between total FVH score and age, stroke size, modASPECTS, and pedNIHSS scores. Multivariable logistic regression evaluated predictors of significant FVH (score >= 3) and included time to MRI, large vessel occlusion, modASPECTS, pedNIHSS, stroke size, and age as independent variables. Results: 83 patients met inclusion criteria. Median time to MRI was 26 hours (95% CI 26-33). FVH were present in 45 patients (54%). Mean FVH score was higher in patients with LVO (5.22 ± 0.64) compared to those without (1.21 ± 0.24; p = 0.00). There was a positive correlation between total FVH score and age (p < 0.05), stroke size (p < 0.0001), modASPECTS (p < 0.0000), and pedNIHSS (p < 0.0002). In the multivariate logistic regression, only older age (OR 1.50, 95% CI 1.12-2.01, p < 0.006) and presence of LVO (OR 0.002, 95% CI 4.85x10 -5 -0.08, p<0.001) were associated with significantly increased odds of high FVH burden. Conclusions: FVH are prevalent in children with AIS, with higher burden in older children. Similar to adults, large vessel occlusion and larger infarct size are associated with higher FVH burden. Further study is needed on whether FVH could be used to identify patients who would benefit from reperfusion therapies.

Abstract WP266: Prediction of Stroke Incidence Using Machine Learning: The Suita Study

Background: This population-based study investigated the potential of machine learning algorithms to predict stroke incidence and identify important risk factors. This study aimed to evaluate the accuracy of these algorithms in constructing a stroke prediction model. Methods: Participants from the Suita study were included, and baseline measurements were used to predict stroke outcomes over a 15-year follow-up period. In total, 7,389 participants and 51 variables were investigated, including demographics, medical history, medical imaging, laboratory data, and lifestyle habits. Initially, unsupervised K-prototype clustering was used to group participants based on their stroke risk. Subsequently, five supervised models (logistic regression, random forest, support vector machine, extreme gradient boosting, and light gradient boosted machine) were applied to predict the stroke outcomes. The Shapley Additive Explanations (SHAP) method determined the most critical variables. Results: Unsupervised clustering revealed significant differences in stroke incidence among the three identified risk clusters (9.1%, 6.6%, and 3.2%). These clusters were categorized into high-, medium-, and low-risk groups. Among the supervised models, the random forest algorithm demonstrated the best performance. The top ten most important variables for predicting stroke incidence were identified using the SHAP, with age being the most influential variable. Other significant risk markers included systolic blood pressure, hypertension, estimated glomerular filtration rate, metabolic syndrome, and blood sugar level. Additionally, elbow joint thickness and fructosamine, hemoglobin, and calcium levels were found to be potential predictors of stroke risk. Notably, the variables identified by the SHAP were consistent with those obtained from the unsupervised clustering approach in the high-risk group. Conclusion: Machine learning algorithms provide accurate predictions of stroke incidence and offer valuable insights into subclinical markers without the need for prior assumptions of causality. This study presents a data-driven machine-learning framework for stroke risk prediction and biomarker identification.

Neuron-specific enolase at admission as a predictor for stroke volume, severity and outcome in ischemic stroke patients: a prognostic biomarker review

An ideal blood biomarker for stroke should provide reliable results, enable fast diagnosis, and be readily accessible for practical use. Neuron-specific enolase (NSE), an enzyme released after neuronal damage, has been studied as a marker for brain injury, including cerebral infarction. However, different methodologies and limited sample sizes have restricted the applicability of any potential findings. This work aims to determine whether NSE levels at Emergency Department (ED) admission correlate with stroke severity, infarcted brain volume, functional outcome, and/or death rates. A systematic literature review was performed using PubMed, Embase, and Scopus databases. Each reviewer independently assessed all published studies identified as potentially relevant. All relevant original observational studies (cohort, case–control, and cross-sectional studies) were included. Eleven studies (1398 patients) met the inclusion criteria. Among these, six studies reported a significant correlation between NSE levels and stroke severity, while only one found no association. Four studies indicated a positive relationship between infarcted brain volume assessed by imaging and NSE levels, in contrast to the findings of only one study. Four studies identified an association related to functional outcome and death rates, while three others did not reach statistical significance in their findings. These data highlight that NSE levels at ED admissions proved to be a promising tool for predicting the outcome of ischemic stroke patients in most studies. However, they presented high discrepancies and low robustness. Therefore, further research is necessary to establish and define the role of NSE in clinical practice.

Abstract WP275: Longitudinal Biomarker Analysis in Patients With Ischemic Stroke: Exploratory Targeted and Omics Assessments From a Phase 2a Clinical Trial

Introduction: Elezanumab (EZB), a monoclonal antibody specific to repulsive guidance molecule A (RGMa), is under investigation to treat acute ischemic stroke. Biomarker evidence in ischemic stroke and for the RGMa pathway is limited. Methods: This blinded, in-study analysis from a 52-week phase 2a, multicenter, randomized (1:1; EZB:placebo) clinical trial (NCT04309474) included patients aged 30-90 years with an acute ischemic stroke (onset ≤ 24 hours before baseline), and a NIHSS score of 7-21. Blinded analyses did not distinguish between treatment arms. Healthy adult controls were procured outside this trial. Blood samples were taken post-stroke across 52 weeks, or 1 time (baseline) for healthy adults. Plasma concentrations of neurodegenerative markers neurofilament light chain protein (NfL) and glial fibrillary acidic protein (GFAP) were measured (validated Simoa Human Neurology 4-Plex A assay; Quanterix). Protein, mRNA, and miRNA were assessed with omics approaches. Results: This preliminary analysis included 34 patients with stroke (mean [SD] age 67.1 [12.3] years, 58.8% male) and 31 healthy adults (61.8 [8.0] years, 71.0% male). The mean (SD) baseline NIHSS total score was 10.9 (4.3). NfL and GFAP concentrations were elevated on day 1 in patients with stroke vs healthy adults (healthy adults are included for reference only). Mean concentrations of NfL were 48.7 pg/mL vs 13.9 pg/mL, respectively; mean concentrations of GFAP were 746.0 pg/mL vs 137.2 pg/mL, respectively. In patients with stroke, agnostic to treatment, peak NfL and GFAP elevations occurred at day 28 and days 2-4, respectively; NfL and GFAP concentrations were lower at week 52 than day 1. Conclusions: Preliminary blinded analysis of plasma markers of neurodegeneration confirm increased NfL and GFAP levels during acute stroke, which diminish over time with different temporal patterns. Final unblinded results will provide a robust natural time course of specific biomarkers of neurodegeneration including GAP43. Forthcoming analyses evaluate broad panels of proteins, mRNA, and miRNA markers. Identifying relevant post stroke biomarkers with directed and exploratory omics may allow development of validated assays to assess efficacy and support decision making in clinical trials.

Methods in Stroke Prevention in the Wisconsin Native American Population

Native American individuals are more frequently affected by cerebrovascular diseases including stroke and vascular cognitive decline. The aim of this study was to determine stroke risk factors that are most prevalent in Wisconsin Native Americans and to examine how education at the community and individual level as well as intensive health wellness coaching may influence modification of stroke risk factors. Additionally, we will investigate the role novel stroke biomarkers may play in stroke risk in this population. This paper details the aims and methods employed in the “Stroke Prevention in the Wisconsin Native American Population” (clinicaltrials.gov identifier: NCT04382963) study including participant health assessments, clinical ultrasound exam of the carotid arteries, cognitive testing battery, and structure and execution of the coaching program.

A task-driven cerebral angiographic imaging based on CT perfusion.

Current clinical computed tomography arteriography (cCTA) and clinical computed tomography venography (cCTV) images often display restricted cerebrovascular profiles, incomplete brain tissue segmentation, and incomplete artery-vein segmentation. Especially for vessels associated with diseases, capturing their complete profiles proves challenging. In this work, we developed a Task-driven Cerebral Angiographic Imaging (TDCAI) technique using computed tomography perfusion (CTP) images of stroke patients. A evaluation on intracranial hemorrhagic stroke (IHS) and acute ischemic stroke (AIS) cases was performed with CT perfusion imaging. The TDCAI technique processed the CTP images, resulting in supplementary diagnostic images, including CTA, CTV, centerline images of the vessels-of-interest [internal carotid artery (ICA) for AIS patients, Labbé vein for IHS patients], and straightened images of the vessels-of-interest. We conducted a comparison between the obtained CTA/CTV images and the cCTA/cCTV images in terms of overall image quality and visibility of the vessels-of-interest. By constructing a virtual vascular phantom, we extracted its centerline and compared it with the actual centerline to calculate maximum and average deviations. This allowed us to evaluate both the accuracy of the centerline extraction algorithm and its capability to resist the influence of side branches. We assessed whether vascular stenosis and dilatation could be expressed in straightened vessel images, conducting statistical analyses to establish the superiority of TDCAI technique. This study proposes a TDCAI technique to eliminate bone and soft tissue interference, effectively segregate the comprehensive cerebral venous and arterial systems, and extract centerlines and straighten the vessels-of-interest, which would aid doctors in assessing the outflow profiles of vessels after a stroke and seeking imaging biomarkers correlated with clinical outcomes.

High serum lactate dehydrogenase to albumin ratio is associated with increased risk of poor prognosis after ischemic stroke

BackgroundLactate dehydrogenase to albumin ratio (LAR) is a comprehensive biomarker for anaerobiosis, inflammation, and nutritional status, but its prognostic value for ischemic stroke has rarely been reported. We aimed to prospectively investigate whether serum LAR is associated with the prognosis of ischemic stroke patients in a large-scale cohort study. Materials and MethodsSerum LAR levels were measured among 6634 patients with ischemic stroke admitted at Minhang hospital from January 2018 to December 2022. The primary outcome was the composite of major disability and death (modified Rankin Scale score [mRS] ≥ 3) at 3-month follow up. Secondary outcomes included death and the ordered 7-level category score of mRS. Multivariate logistic regression and restricted cubic splines were adopted to evaluate the associations between serum LAR levels and adverse clinical outcomes of ischemic stroke. ResultsDuring 3 months of follow-up period, a total of 2125 patients experienced primary outcome. After multivariate adjustment, the highest quartile of serum LAR was associated with an increased risk of primary outcome (odds ratio [OR], 1.52; 95% confidence interval [CI], 1.27–1.83; P for trend < 0.001). Each standard deviation higher log-transformed serum LAR resulted in a 20% (95% CI, 12%−28%) increased risk of primary outcome. Furthermore, multivariable-adjusted restricted cubic spline analyses showed a linear association between the serum LAR level with primary outcome (P for linearity < 0.001). Finally, the addition of serum LAR to conventional risk factors significantly improved risk predictive abilities for the primary outcome (net reclassification improvement [NRI]: 18.35%, P < 0.001; integrated discrimination improvement [IDI]: 0.35%, P < 0.001) at 3-month follow up in patients with ischemic stroke. ConclusionHigh serum LAR level was independently associated with an increased risk of adverse clinical outcomes among patients with ischemic stroke, indicating that serum LAR may be a valuable prognostic biomarker for ischemic stroke.

Atherothrombotic and thrombolytic biomarkers in incident stroke and atrial fibrillation-related stroke: The Multi-Ethnic Study of Atherosclerosis (MESA)

Background and aimsAlthough several biomarkers have been studied in thromboembolic stroke, measuring the balance between thrombus formation and thrombolysis and data on its role in predicting stroke and atrial fibrillation (AF)-related stroke is limited. We sought to assess atherothrombotic biomarkers grouped into composite factors that reflect thrombotic and thrombolytic potential, and the balance between these factors as it relates to incident stroke or transient ischemic attack (TIA) and stroke/TIA in AF. MethodsA Thrombotic Factor, derived from fibrinogen, plasmin–antiplasmin complex, factor VIII, D-dimer, and lipoprotein(a); and a Thrombolytic Factor, derived from plasminogen and oxidized phospholipids on plasminogen, were evaluated at baseline in 5,764 Multi-Ethnic Study of Atherosclerosis (MESA) participants. We evaluated the association between these two factors representative of thrombotic and thrombolytic potential and incident stroke/TIA (n = 402), and AF-related stroke/TIA (n = 82) over a median of 13.9 and 3.7 years, respectively. Cox proportional hazard models adjusted for medication use, cardiovascular risk factors and CHA2DS2-VASc score were utilized. Harrell's C-index was estimated to evaluate model performance. ResultsIn models including both factors, Thrombotic Factor was positively while Thrombolytic Factor was inversely associated with incident stroke/TIA and AF-related stroke/TIA. Incorporating these factors along with the CHA2DS2-VASc in adjusted models resulted in a small improvement in risk prediction of incident stroke/TIA and AF-related stroke/TIA compared to models without the factors (C-index from 0.697 to 0.704, and from 0.657 to 0.675, respectively). ConclusionsComposite biomarker factors, representative of the balance between thrombotic and thrombolytic propensity, provided an improvement in predicting stroke/TIA beyond CHA2DS2-VASc score.

Identification and validation of cortisol-related hub biomarkers and the related pathogenesis of biomarkers in Ischemic Stroke.

Ischemic stroke is a disease in which cerebral blood flow is blocked due to various reasons, leading to ischemia, hypoxia, softening, and even necrosis of brain tissues. The level of cortisol is related to the occurrence and progression of ischemic stroke. However, the mechanism governing their interrelationship is still unclear. The main objective of this study was to identify and understand the molecular mechanism between cortisol and IS. The common cortisol-related biological processes were screened by mutual verification of two data sets and the cortisol-related hub biomarkers were identified. Modular analysis of protein interaction networks was performed, and the differential pathway analysis of individual genes was conducted by GSVA and GSEA. Drug and transcription factor regulatory networks of hub genes were excavated, and the diagnostic potential of hub genes was analyzed followed by the construction of a diagnostic model. By screening the two data sets by GSVA, three biological processes with common differences were obtained. After variation analysis, four cortisol-related hub biomarkers (CYP1B1, CDKN2B, MEN1, and USP8) were selected. Through the modular analysis of the protein-protein interaction network and double verification of GSVA and GSEA, a series of potential molecular mechanisms of hub genes were discovered followed by a series of drug regulatory networks and transcription factor regulatory networks. The hub biomarkers were found to have a high diagnostic value by ROC; thus, a diagnostic model with high diagnostic efficiency was constructed. The diagnostic value was mutually confirmed in the two data sets. Four cortisol-related hub biomarkers are identified in this study, which provides new ideas for the key changes of cortisol during the occurrence of IS.

Circular RNAs: Promising Treatment Targets and Biomarkers of Ischemic Stroke.

Ischemic stroke is one of the most significant causes of morbidity and mortality worldwide. However, there is a dearth of effective drugs and treatment methods for ischemic stroke. Significant numbers of circular RNAs (circRNAs) exhibit abnormal expression following ischemic stroke and are considered potential therapeutic targets. CircRNAs have emerged as promising biomarkers due to their stable expression in peripheral blood and their potential significance in ischemic stroke diagnosis and prognosis. This review provides a summary of 31 circRNAs involved in the pathophysiological processes of apoptosis, autophagy, inflammation, oxidative stress, and angiogenesis following ischemic stroke. Furthermore, we discuss the mechanisms of action of said circRNAs and their potential clinical applications. Ultimately, circRNAs exhibit promise as both therapeutic targets and biomarkers for ischemic stroke.

Serum apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) is a novel stroke biomarker

BackgroundApoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) is a promising stroke biomarker. However, a large study of human serum ASC has not yet to be reported; additionally, the diagnostic value of prehospital concentration and practicality of ASC remains unknown. MethodsWe recruited 774 Chinese stroke patients, including 523 with ischemic stroke (IS) and 251 with hemorrhagic stroke (HS) within 14 days following symptom onset in the emergency department, alongside 481 healthy individuals and 64 cognitive impairment patients as controls. Serum ASC concentrations were determined using automated chemiluminescence immunoassay, exploring the relationship between serum ASC concentration and subtypes, severity, and sampling timepoints of stroke. ResultsASC concentrations were significantly higher in stroke patients compared with all controls (P < 0.001). HS patients had greater ASC concentrations than IS patients (P < 0.05). With increasing ASC concentration, the proportion of severe cases increased. The area under the receiver operating characteristic curve (AUC) for differentiating between healthy individuals and stroke patients in the hyperacute phase was 0.78; this markedly improved (0.90) when considering samples from healthy individuals and patients with subarachnoid hemorrhage (SAH) ≤ 3 h from last-known-well (LKW). ConclusionsSerum ASC is a valuable biomarker for stroke differentiation and aids in the clinical diagnosis of stroke severity and subtypes.

Biomarkers — predictors of mortality in patients with ischemic stroke

BACKGROUND: Stroke is a global health problem and the second leading cause of death worldwide, with ischemic stroke accounting for the majority of acute cerebrovascular accidents. Predicting outcomes in patients with ischemic stroke is challenging due to the limited prognostic performance of existing models. The lack of reliable and predictive biomarkers of ischemic stroke used in clinical practice provides a rationale for studies to address this issue.&#x0D; AIM: The aim of this study was to identify clinical, demographic, neuroimaging and molecular biomarkers of ischemic stroke associated with the fatal outcome of the disease.&#x0D; MATERIALS AND METHODS: We retrospectively analyzed cases of ischemic stroke confirmed by computed tomography of the brain with a duration of 3 months or less. As factors potentially related to the outcome of ischemic stroke, we considered (1) clinical and demographic characteristics, including sex, age, history of acute cerebrovascular accident, time from stroke to hospitalization, phase and type of stroke, neurological status on admission (level of consciousness, FOUR coma scale), comorbidities (diabetes mellitus, infectious complications, oncological diseases); (2) molecular biomarkers including blood glucose and neuron-specific enolase (NSE) levels at different phases of stroke; (3) neuroimaging biomarkers such as number and location of stroke lesion, total infarct volume, signs of edema, hemorrhagic component according to computed tomography.&#x0D; RESULTS: 38 patients with ischemic stroke were included in the study. Lesion volume was larger in non-survivors: 123 [44.6–206.2] versus 42.7 [8.2–88.7] ml3 (p=0.032), and cerebral edema was detected significantly more often on admission CT scan than in survivors: 7 (77.8%) versus 10 (34.5%), p=0.022. Stroke lesion volume was a predictor of mortality (AUC 0.739; 95% CI 0.542–0.937; p=0.032). The optimal cut-off for stroke lesion volume was found to be 90 ml3.&#x0D; CONCLUSION: Signs of edema/brain stem dislocation and cerebral lesion volume 90 ml3 documented at hospital admission are predictors of fatal outcome. Therefore, neuroimaging biomarkers can be used for risk stratification of fatal outcome in ischemic stroke patients.

Bioinformatical analysis and in vivo validation of potential biomarkers of diabetes-related ischemic stroke and therapeutic targets of HSYA

Bioinformatical analysis and in vivo validation of potential biomarkers of diabetes-related ischemic stroke and therapeutic targets of HSYA

Elevated troponin as a potential diagnostic biomarker for stroke: A systematic review and meta-analysis

Elevated troponin as a potential diagnostic biomarker for stroke: A systematic review and meta-analysis

Clonal Hematopoiesis of Indeterminate Potential (CHIP) Related to the Etiology of Ischemic Stroke

Introduction: Clonal Hematopoiesis of Indeterminate Potential (CHIP) is associated with cardiovascular disease, including acute myocardial infarction and ischemic stroke, due to immune system dysregulation leading to increased atherosclerotic plaque formation and inflammation. Approximately 25-40% of ischemic strokes have an unknown cause even after a comprehensive etiological study and are eventually categorized as cryptogenic strokes. Our hypothesis is that the presence of CHIP could represent a biomarker for atherosclerotic or cardioembolic ischemic stroke and help to clarify the origin of cryptogenic strokes. Therefore, the objective of this study was to analyze the prevalence of CHIP in patients with different subtypes of ischemic stroke and its prognostic impact on cardiovascular risk. Methods: This prospective observational study included consecutive patients over 60 years of age with no prior history of neoplasia or cytotoxic treatment, who experienced embolic ischemic stroke between September 2021 and August 2022. Ischemic strokes were classified into cardioembolic (CE), atherothrombotic (AT) or cryptogenic (CRYP) etiologies after performing a systematic etiological study. During the stroke admission, peripheral blood samples were obtained in order to analyze the 13 genes most frequently associated with CHIP ( DNMT3A, TET2, ASXL1, JAK2, PPM1D, TP53, SF3B1, GNB1, SRSF2, CHEK2, CBL, GNAS, NRAS) through targeted next generation sequencing. Libraries were prepared using the KAPA HyperPlus capture chemistry (Roche) and were sequenced on a MiSeq platform (Illumina) following a 2x150bp paired-end read standard protocol, allowing the detection of variants with a variant allelic frequency (VAF) of ≥1%. The analysis was conducted using an in-house developed pipeline. Patients with one or more mutations in these genes with a VAF ≥2% were considered CHIP carriers. Cardiovascular risk factors including: hypertension, diabetes mellitus, dyslipidemia, smoking and obesity, were also analyzed. Results: Seventy-eight patients with stroke were included (50% female, median age 72 years (range: 59-90). Ischemic strokes were classified etiologically as: 36 CE (46.2%), 34 AT (43.6%) and 8 CRYP (10.3%) (Table 1). CHIP was detected in 21/78 (31.3%) patients, with the following gene mutation frequencies among CHIP carriers: DNMT3A (47.6%), TET2 (28.5%), SRSF2 (14.2%), PPM1D (9.5%), ASXL1 (4.8%), CBL (4.8%), CHEK2 (4.8%) and JAK2 (4.8%). The median VAF detected was 4.85% (range: 2.1%-43.7%), and 23.8% (5/21) of cases presented more than one mutation. The incidence of CHIP varied according to stroke etiology: CE etiology: 38.9% (14/36); AT etiology: 17.6% (6/34) and CRYP etiology: 12.5% (1/8) (p=0.046) (Figure 1). Moreover, only CE strokes showed mutations in TET2 (16.7% (6/36)) compared to AT (0/34) and CRYP (0/8) (p=0.015). No significant differences were observed in the blood counts (Hb, MCV, RDW, neutrophil count, monocytes, platelets or PCR) between stroke patients with CHIP and non-CHIP (Table 1). Finally, in the multivariate analysis, TET2 mutations were associated with CE stroke independently of age, coronary artery disease and classic cardiovascular risk factors (OR 8.1; Cl: 1.35-48.47; p=0.012). Conclusions: Our findings identify that CHIP is common in patients with ischemic strokes, especially in those of cardioembolic etiology, with TET2 being the most frequently mutated gene. The presence of CHIP TET2 could represent a novel cardiovascular risk factor, contributing to a more precise etiological distinction between the different etiologies of ischemic stroke. Funding source: this project is supported by health research fund of Carlos III health institute. FIS PI20/00881

Exosomal miRNAs as Biomarkers of Ischemic Stroke.

Exosomes are small lipid bilayer membrane particles released from all living cells into the extracellular environment. They carry several molecules and have a critical role in cell-cell communication under physiological and pathological conditions. In recent decades, exosomes, and especially their cargo, have emerged as a promising tool for several clinical conditions. However, the literature has become increasingly unambiguous in defining the role of exosomes in chronic cerebrovascular diseases. Because they can pass through the blood-brain barrier, they have great potential to reflect intracerebral changes. They can, thus, provide valuable insight into the mechanisms of central nervous system diseases. The purpose of this review is to describe the literature on the role of exosomal miRNA, which represents the most widely investigated exosomal biomarker, in strokes. First, we provide an overview of exosomes, from biology to isolation and characterization. Then, we describe the relationship between exosomes and stroke pathogenesis. Finally, we summarize the human studies evaluating exosomal miRNA biomarkers of stroke. Although the collective literature supports the potential use of exosomal miRNA as biomarkers of ischemic stroke, there are still several limitations hampering their introduction into clinical practice.

A case–control comparison of acute-phase peripheral blood gene expression in participants diagnosed with minor ischaemic stroke or stroke mimics

BackgroundPast studies suggest that there are changes in peripheral blood cell gene expression in response to ischaemic stroke; however, the specific changes which occur during the acute phase are poorly characterised. The current study aimed to identify peripheral blood cell genes specifically associated with the early response to ischaemic stroke using whole blood samples collected from participants diagnosed with ischaemic stroke (n = 29) or stroke mimics (n = 27) following emergency presentation to hospital. Long non-coding RNA (lncRNA), mRNA and micro-RNA (miRNA) abundance was measured by RNA-seq, and the consensusDE package was used to identify genes which were differentially expressed between groups. A sensitivity analysis excluding two participants with metastatic disease was also conducted.ResultsThe mean time from symptom onset to blood collection was 2.6 h. Most strokes were mild (median NIH stroke scale score 2.0). Ten mRNAs (all down-regulated in samples provided by patients experiencing ischaemic stroke) and 30 miRNAs (14 over-expressed and 16 under-expressed in participants with ischaemic stroke) were significantly different between groups in the whole cohort and sensitivity analyses. No significant over-representation of gene ontology categories by the differentially expressed genes was observed. Random forest analysis suggested a panel of differentially expressed genes (ADGRG7 and miRNAs 96, 532, 6766, 6798 and 6804) as potential ischaemic stroke biomarkers, although modelling analyses demonstrated that these genes had poor diagnostic performance.ConclusionsThis study provides evidence suggesting that the early response to minor ischaemic stroke is predominantly reflected by changes in the expression of miRNAs in peripheral blood cells. Further work in independent cohorts particularly in patients with more severe stroke is needed to validate these findings and investigate their clinical relevance.

Proteomic analysis of Biliverdin protected cerebral ischemia–reperfusion injury in rats

Biliverdin, a heme metabolite, has been previously reported to alleviate cerebral ischemic reperfusion injury (CIRI). However, the alterations of brain proteome profiles underlying this treatment remain elusive. The objective of this study is to analyze the differential protein expression profile in cerebral cortex of rats involved in anti-CIRI effects of Biliverdin, providing experimental foundation for searching specific marker proteins. Rat model of MCAO/R was established, HE staining, TTC staining, TUNEL staining, and neurological behavioral examination, corner turning test, adhesive removal test, were performed to validate the effects of Biliverdin, and the results indicated that Biliverdin plays a significant role in alleviating CIRI. Furthermore, proteomic analysis of brain tissues of rats subjected to CIRI following Biliverdin treatment was performed using an integrated TMT-based quantitative proteomic approach coupled with LC-MS/MS technology to clarify the comprehensive mechanisms of Biliverdin in CIRI. First, we conducted strict quality control data for TMT experiments. Finally, a total of 7366 proteins were identified, of which 95 proteins were differentially expressed (DEPs) between the CIRI group and the Sham group and 52 between the CIRI and BV groups. In addition, two overlapping proteins among the 147 DEPs, Atg4c and Camlg, were validated by RT-qPCR and western blotting, and their levels were consistent with the results of TMT analysis. Taken together, the current findings firstly mapped comprehensive proteomic changes after CIRI treated with Biliverdin, providing a foundation for developing potentially therapeutic targets of anti-CIRI of Biliverdin and clinically prognostic biomarkers of stroke.

A Microfluidics-Based Multiplex SERS Immunoassay Device for Analysis of Acute Ischemic Stroke Biomarkers.

Sensitive and accurate methods for early detection of acute ischemic stroke (AIS) are essential for timely treatment and prognostic assessment of patients. In this study, we report a microfluidics-based ultrasensitive surface-enhanced Raman scattering (SERS) immunoassay device for the quantitative determination of multiplex biomarkers in AIS. By preparing 5,5'-dithiobis-2-nitrobenzoic acid (DTNB) antibody-modified gold nanoparticles (AuNPs) on SERS devices as SERS probes, the biomarkers in whole blood of AIS were accurately captured and further visualized for SERS signal intensity quantitative analysis of six biomarkers in the blood samples. It is worth mentioning that the limit of detection (LOD) of the method can reach the level of fg/mL, with excellent sensitivity and selectivity. Meanwhile, the analytical comparison with ELISA method showed that the detection results of both methods were consistent, which verified the feasibility of the assembled device. The SERS immunoassay device detection provides a powerful strategy for the prediction, early diagnosis and dynamic monitoring of prognosis of AIS with a wide range of clinical practice prospects.

Bioinformatics strategies to identify differences in molecular biomarkers for ischemic stroke and myocardial infarction.

Ischemic strokes (ISs) are commonly treated by intravenous thrombolysis using a recombinant tissue plasminogen activator; however, successful treatment can only occur within 3 hours after the stroke. Therefore, it is crucial to determine the causes and underlying molecular mechanisms, identify molecular biomarkers for early diagnosis, and develop precise preventive treatments for strokes. We aimed to clarify the differences in gene expression, molecular mechanisms, and drug prediction approaches between IS and myocardial infarction (MI) using comprehensive bioinformatics analysis. The pathogenesis of these diseases was explored to provide directions for future clinical research. The IS (GSE58294 and GSE16561) and MI (GSE60993 and GSE141512) datasets were downloaded from the Gene Expression Omnibus database. IS and MI transcriptome data were analyzed using bioinformatics methods, and the differentially expressed genes (DEGs) were screened. A protein-protein interaction network was constructed using the STRING database and visualized using Cytoscape, and the candidate genes with high confidence scores were identified using Degree, MCC, EPC, and DMNC in the cytoHubba plug-in. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed using the database annotation, visualization, and integrated discovery database. Network Analyst 3.0 was used to construct transcription factor (TF) - gene and microRNA (miRNA) - gene regulatory networks of the identified candidate genes. The DrugBank 5.0 database was used to identify gene-drug interactions. After bioinformatics analysis of IS and MI microarray data, 115 and 44 DEGS were obtained in IS and MI, respectively. Moreover, 8 hub genes, 2 miRNAs, and 3 TFs for IS and 8 hub genes, 13 miRNAs, and 2 TFs for MI were screened. The molecular pathology between IS and MI presented differences in terms of GO and KEGG enrichment pathways, TFs, miRNAs, and drugs. These findings provide possible directions for the diagnosis of IS and MI in the future.