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

Circulating Blood Prognostic Biomarker Signatures for Hemorrhagic Cerebral Cavernous Malformations (CCMs)

Cerebral cavernous malformations (CCMs) are a neurological disorder characterized by enlarged intracranial capillaries in the brain, increasing the susceptibility to hemorrhagic strokes, a major cause of death and disability worldwide. The limited treatment options for CCMs underscore the importance of prognostic biomarkers to predict the likelihood of hemorrhagic events, aiding in treatment decisions and identifying potential pharmacological targets. This study aimed to identify blood biomarkers capable of diagnosing and predicting the risk of hemorrhage in CCM1 patients, establishing an initial set of circulating biomarker signatures. By analyzing proteomic profiles from both human and mouse CCM models and conducting pathway enrichment analyses, we compared groups to identify potential blood biomarkers with statistical significance. Specific candidate biomarkers primarily associated with metabolism and blood clotting pathways were identified. These biomarkers show promise as prognostic indicators for CCM1 deficiency and the risk of hemorrhagic stroke, strongly correlating with the likelihood of hemorrhagic cerebral cavernous malformations (CCMs). This lays the groundwork for further investigation into blood biomarkers to assess the risk of hemorrhagic CCMs.

mPR-Specific Actions Influence Maintenance of the Blood–Brain Barrier (BBB)

Cerebral cavernous malformations (CCMs) are characterized by abnormally dilated intracranial microvascular sinusoids that result in increased susceptibility to hemorrhagic stroke. It has been demonstrated that three CCM proteins (CCM1, CCM2, and CCM3) form the CCM signaling complex (CSC) to mediate angiogenic signaling. Disruption of the CSC will result in hemorrhagic CCMs, a consequence of compromised blood–brain barrier (BBB) integrity. Due to their characteristically incomplete penetrance, the majority of CCM mutation carriers (presumed CCM patients) are largely asymptomatic, but when symptoms occur, the disease has typically reached a clinical stage of focal hemorrhage with irreversible brain damage. We recently reported that the CSC couples both classic (nuclear; nPRs) and nonclassic (membrane; mPRs) progesterone (PRG)-receptors-mediated signaling within the CSC-mPRs-PRG (CmP) signaling network in nPR(−) breast cancer cells. In this report, we demonstrate that depletion of any of the three CCM genes or treatment with mPR-specific PRG actions (PRG/mifepristone) results in the disruption of the CmP signaling network, leading to increased permeability in the nPR(−) endothelial cells (ECs) monolayer in vitro. Finally, utilizing our in vivo hemizygous Ccm mutant mice models, we demonstrate that depletion of any of the three CCM genes, in combination with mPR-specific PRG actions, is also capable of leading to defective homeostasis of PRG in vivo and subsequent BBB disruption, allowing us to identify a specific panel of etiological blood biomarkers associated with BBB disruption. To our knowledge, this is the first report detailing the etiology to predict the occurrence of a disrupted BBB, an indication of early hemorrhagic events.

Machine Learning Analysis of MicroRNA Expression Data Reveals Novel Diagnostic Biomarker for Ischemic Stroke

OBJECTIVES

Ischemic stroke (IS) is one of the leading causes of morbidity and mortality worldwide. Circulating microRNAs have a potential as minimally invasive biomarkers for disease prediction, diagnosis, and prognosis. In this study, we sought to use different machine learning algorithms to identify an optimal model of microRNA by integrating the expression data of pre-selected microRNAs for discriminating patients with IS from controls.

METHODS

The expression level of microRNAs in the peripheral blood of 50 patients with IS and 50 matched controls were assessed through real-time polymerase chain reaction (qRT-PCR). Machine learning algorithms, including artificial neural network, random forest, extreme gradient boosting, and support vector machine (SVM) were employed via R 3.6.3 software to establish diagnostic models for IS.

RESULTS

The IS group had significantly increased expression levels of miR-19a (P < 0.001), miR-148a (P < 0.001), miR-320d (P = 0.003), and miR-342-3p (P < 0.001) compared with the control group. MiR-148a, miR-342-3p, miR-19a, and miR-320d yielded areas under the receiver operating characteristic curve (AUC) of 0.872, 0.844, 0.721, and 0.673, respectively, with 0.740, 0.940, 0.740, and 0.840 sensitivity and 0.920, 0.640, 0.600, and 0.440 specificity, respectively. Model miR-148a + miR-342-3p + miR-19a had the best predictive value when analyzed via SVM algorithm with AUC, sensitivity, and specificity values of 0.958, 0.937, and 0.889, respectively.

CONCLUSION

The diagnostic value of the combination of miR-148a, miR-342-3p, and miR-19a through SVM algorithm has the potential to serve as a feasible approach to promote the diagnosis of IS.

sTWEAK is a marker of early haematoma growth and leukoaraiosis in intracerebral haemorrhage

Objective

To study the association between early growth of haematoma with biomarkers of endothelial dysfunction such as leukoaraiosis (LA) and the soluble tumour necrosis factor-like weak inducer of apoptosis (sTWEAK) in patients with intracerebral haemorrhage (ICH).

Methods

This is a retrospective observational study of patients with nontraumatic ICH. Clinical and biochemical parameters were analysed. sTWEAK levels were measured by ELISA. LA was analysed in the hemisphere without haemorrhage to avoid interference with the acute injury. The main endpoint was the haematoma growth evaluated by the difference in volume between the second and the initial neuroimage. Poor functional outcome, defined as a modified Rankin Scale >2 at 3 months, was considered as secondary endpoint. Receiver operating characteristic curve analysis was performed to stablish the best cut-off for sTWEAK levels associated with haematoma growth.

Results

We included 653 patients with ICH in our analysis (71.1±11.9 years, 44% women). Haematoma growth was observed in 188 patients (28.8%). sTWEAK levels ≥5600 pg/mL predicted ICH growth with a sensitivity of 84% and a specificity of 87%. sTWEAK levels ≥5600 pg/mL and the presence of LA were associated with haematoma growth (OR: 42.46; (CI 95% 22.67 to 79.52) and OR: 2.73 (CI 95% 1.39 to 5.34), respectively). Also, the presence of LA (OR: 4.31 (CI 95% 2.89 to 6.42)) and the interaction between ICH growth and sTWEAK (OR: 2.23 (CI 95% 1.40 to 3.55)) were associated with poor functional outcome at 3 months.

Conclusion

sTWEAKs, together with the presence and grade of LA, are biomarkers able to predict ICH growth and poor functional outcome in patients with ICH.

Soluble Receptors Affecting Stroke Outcomes: Potential Biomarkers and Therapeutic Tools

Soluble receptors are widely understood to be freestanding moieties formed via cleavage from their membrane-bound counterparts. They have unique structures, are found among various receptor families, and have intriguing mechanisms of generation and release. Soluble receptors’ ability to exhibit pleiotropic action by receptor modulation or by exhibiting a dual role in cytoprotection and neuroinflammation is concentration dependent and has continually mystified researchers. Here, we have compiled findings from preclinical and clinical studies to provide insights into the role of soluble/decoy receptors, focusing on the soluble cluster of differentiation 36, the soluble cluster of differentiation 163, and soluble lipoprotein-related protein 1 (sCD36, sCD163, and sLRP1, respectively) and the functions they could likely serve in the management of stroke, as they would notably regulate the bioavailability of the hemoglobin and heme after red blood cell lysis. The key roles that these soluble receptors play in inflammation, oxidative stress, and the related pharmacotherapeutic potential in improving stroke outcomes are described. The precise pleiotropic physiological functions of soluble receptors remain unclear, and further scientific investigation/validation is required to establish their respective role in diagnosis and therapy.

Blood-Based Biomarkers Are Associated with Different Ischemic Stroke Mechanisms and Enable Rapid Classification between Cardioembolic and Atherosclerosis Etiologies

Stroke is a top leading cause of death, which occurs due to interference in the blood flow of the brain. Ischemic stroke (blockage) accounts for most cases (87%) and is further subtyped into cardioembolic, atherosclerosis, lacunar, other causes, and cryptogenic strokes. The main value of subtyping ischemic stroke patients is for a better therapeutic decision-making process. The current classification methods are complex and time-consuming (hours to days). Specific blood-based biomarker measurements have promising potential to improve ischemic stroke mechanism classification. Over the past decades, the hypothesis that different blood-based biomarkers are associated with different ischemic stroke mechanisms is increasingly investigated. This review presents the recent studies that investigated blood-based biomarker characteristics differentiation between ischemic stroke mechanisms. Different blood-based biomarkers are specifically discussed (b-type natriuretic peptide, d-dimer, c-reactive protein, tumor necrosis factor-α, interleukin-6, interleukin-1β, neutrophil-lymphocyte ratio, total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein and apolipoprotein A), as well as the different cut-off values that may be useful in specific classifications for cardioembolic and atherosclerosis etiologies. Lastly, the structure of a point-of-care biosensor device is presented, as a measuring tool on-site. The information presented in this review will hopefully contribute to the major efforts to improve the care for stroke patients.

B-Type Natriuretic Peptide as a Significant Brain Biomarker for Stroke Triaging Using a Bedside Point-of-Care Monitoring Biosensor

Stroke is a widespread condition that causes 7 million deaths globally. Survivors suffer from a range of disabilities that affect their everyday life. It is a complex condition and there is a need to monitor the different signals that are associated with it. Stroke patients need to be rapidly diagnosed in the emergency department in order to allow the admission of the time-limited treatment of tissue plasminogen activator (tPA). Stroke diagnostics show the use of sophisticated technologies; however, they still contain limitations. The hidden information and technological advancements behind the utilization of biomarkers for stroke triaging are significant. Stroke biomarkers can revolutionize the way stroke patients are diagnosed, monitored, and how they recover. Different biomarkers indicate different cascades and exhibit unique expression patterns which are connected to certain pathologies in the human body. Over the past decades, B-type natriuretic peptide (BNP) and its derivative N-terminal fragment (NT-proBNP) have been increasingly investigated and highlighted as significant cardiovascular biomarkers. This work reviews the recent studies that have reported on the usefulness of BNP and NT-proBNP for stroke triaging. Their classification association is also presented, with increased mortality in stroke, correlation with cardioembolic stroke, and an indication of a second stroke recurrence. Moreover, recent scientific efforts conducted for the technological advancement of a bedside point-of-care (POC) device for BNP and NT-proBNP measurements are discussed. The conclusions presented in this review may hopefully assist in the major efforts that are currently being conducted in order to improve the care of stroke patients.

Personalized medicine-concepts, technologies, and applications in inflammatory skin diseases

The current state, tools, and applications of personalized medicine with special emphasis on inflammatory skin diseases like psoriasis and atopic dermatitis are discussed. Inflammatory pathways are outlined as well as potential targets for monoclonal antibodies and small-molecule inhibitors.